httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False asyncio - DEBUG - Using selector: KqueueSelector httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='api.gradio.app' port=443 local_address=None timeout=3 socket_options=None httpcore.connection - DEBUG - connect_tcp.started host='checkip.amazonaws.com' port=443 local_address=None timeout=3 socket_options=None asyncio - DEBUG - Using selector: KqueueSelector httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='127.0.0.1' port=7861 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'date', b'Tue, 06 Feb 2024 01:55:54 GMT'), (b'server', b'uvicorn'), (b'content-length', b'5'), (b'content-type', b'application/json')]) httpx - INFO - HTTP Request: GET http://127.0.0.1:7861/startup-events "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpx - DEBUG - load_ssl_context verify=False cert=None trust_env=True http2=False httpcore.connection - DEBUG - connect_tcp.started host='127.0.0.1' port=7861 local_address=None timeout=3 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'date', b'Tue, 06 Feb 2024 01:55:54 GMT'), (b'server', b'uvicorn'), (b'content-length', b'8752'), (b'content-type', b'text/html; charset=utf-8')]) httpx - INFO - HTTP Request: HEAD http://127.0.0.1:7861/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='checkip.amazonaws.com' port=443 local_address=None timeout=3 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.gradio.app' timeout=3 httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='checkip.amazonaws.com' timeout=3 httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='checkip.amazonaws.com' timeout=3 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 01:55:54 GMT'), (b'Server', b'Not Available'), (b'Content-Length', b'12'), (b'Connection', b'keep-alive')]) httpx - INFO - HTTP Request: GET https://checkip.amazonaws.com/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 01:55:54 GMT'), (b'Server', b'Not Available'), (b'Content-Length', b'12'), (b'Connection', b'keep-alive')]) httpx - INFO - HTTP Request: GET https://checkip.amazonaws.com/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='api.gradio.app' port=443 local_address=None timeout=5 socket_options=None httpcore.connection - DEBUG - connect_tcp.started host='api.gradio.app' port=443 local_address=None timeout=5 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.gradio.app' timeout=5 httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.gradio.app' timeout=5 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 01:55:55 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'21'), (b'Connection', b'keep-alive'), (b'Server', b'nginx/1.18.0'), (b'Access-Control-Allow-Origin', b'*')]) httpx - INFO - HTTP Request: GET https://api.gradio.app/pkg-version "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 01:55:55 GMT'), (b'Content-Type', b'text/html; charset=utf-8'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'Server', b'nginx/1.18.0'), (b'Access-Control-Allow-Origin', b'*'), (b'Content-Encoding', b'gzip')]) httpx - INFO - HTTP Request: POST https://api.gradio.app/gradio-launched-telemetry/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 01:55:55 GMT'), (b'Content-Type', b'text/html; charset=utf-8'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'Server', b'nginx/1.18.0'), (b'Access-Control-Allow-Origin', b'*'), (b'Content-Encoding', b'gzip')]) httpx - INFO - HTTP Request: POST https://api.gradio.app/gradio-initiated-analytics/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete matplotlib.pyplot - DEBUG - Loaded backend macosx version unknown. matplotlib.pyplot - DEBUG - Loaded backend agg version v2.2. root - INFO - Video ID 48L5LeQ06ww extracted from URL. urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=48L5LeQ06ww HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=48L5LeQ06ww&ei=yJHBZYz1H5Liir4PvsOx8A8&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707209784&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=AC05228C33402C0D3DD00EF16C2D3B2B5DF5BF09.90B109BD4AD3DCF5128D2A9233804583FF05744B&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID 48L5LeQ06ww. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhi my name is Willi and also go by lar I\'m a four data science and applyed math student at UC San Diego and I\'ll be pursuing a graduate degree in computer science starting at fall 2024 in this video I\'m going to apply for this AI cam data science machine learning intern for the summer of 2024 so why I\'m interesting is this position I have a deep passion for leveraging my skills in data science and machine learning to build AI power tools such as the AI teaching assistant like the job description described and also highly motivated to DW meaningful educational outcome um and also have a strong alignment with a focus on education Technologies proven by my past experiencing academic research and my P experience in undergraduate te assistant and I also have a lot of r p experience align with the job requirements so what values I can provide to this program well first with a strong Foundation need a science machine learning and web development I can bring a blend of technical expertise and educational experiences so I have work in various research lab and develop models for data analysis and engage processing I develop applications for larger language models and also find tune a lot of foundation models and also have a lot of R teaching experience such as a Time teaching system at use San Diego in computer science mathematics and data science mathematic and economic courses and also have a 100% student instructor recommendation rate which proven ability in effective teaching and mentoring students and also develop various Educational Tools such as interactive course websites for a lot of commuter science data classes and also a lot of automated grading script and some grade report script and also have tons of leadership and manip experiences I\'ve Le various research projects in a lot of classes and research groups and also mentored a lot of under class working on research project and guided them to Bridge a knowledge Gap so then I help them to fulfill all the prerequisite that they need to do research in a real setting and what I hope to achieve is to develop my skills in artificial intelligence and machine learning while making an impact in the educational technology field I would like to gain insights of challenges and opportunities in the tech education field and continue Innovative AI power teaching tools and ASP by and empower the Next Generation Tech is is doent mentoring as an extension of my teaching assistant experiences so in this U slides I would like to use my published Bela paper as an example of aligning with audience needs so basically we identify that the challenge of students struggling with text embedded in images while studying and we also recognize the limitation of chpd at that time which did not support visual input and our solution is is why don\'t we just build our own model so we built a model called bifa which is a simple multimodal LM for better handling text resal questions and accepted by triple ai24 so basically we focus on making believer adoped at reading and interpreting text embedding within images which directly address a significant need in educational sector where students often encounter the complex diagrams graph and text in visual uh various visual formats so that just as example of proven my ability uh to sense the audience need so then we can address we can uh develop project to address stakeholders um need and in this slide I would like to use b pration as the topic I choose to explain to my grandma so here\'s my version of it I\'m going to say hey Grandma imagine you\'re teaching our cat emo a new tricks Str that shaking hand with me each time it does something right you give it a trick each time if the cat makes a mistake you is guiding on how to do it better next time so in a computer brain which is called Neer Network back application is like teaching the computer to learn from its mistakes when a computer tries to solve a problem and gets it wrong back loation helps you understand where it went wrun and how to improve it it just like computer is practicing and learning just like a cat emo to get better at answering question and solving problems um in a lot of training process and in the end of the video I would like to show the result of me training my cat using similar um using similar format yeah and that\'s basically it I\'ll look forward to talk more about this opportunity in the future interview round and thank you for watching this video\n\nCandidate\'s Number of Pauses:\n1\n\nCandidate\'s Length of Video:\n5.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 401, b'Unauthorized', [(b'Date', b'Tue, 06 Feb 2024 01:56:25 GMT'), (b'Content-Type', b'application/json; charset=utf-8'), (b'Content-Length', b'301'), (b'Connection', b'keep-alive'), (b'vary', b'Origin'), (b'x-request-id', b'9349d236d017fe740d1a256d2c9b8f68'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=cbQ_GwKlP.XWlTh4ITc6MP7yjEmDM.hM4_WAlOi0iTU-1707184585-1-AVUqNW8xIJVqnbvskS1+MkMZJaf+NQ0I5jznvj9uLEhnFl4V1d9kvG2ZpcqEeg7V+AasKOvesb8TKH2l2F3jwL0=; path=/; expires=Tue, 06-Feb-24 02:26:25 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=2vtJvdd8o59bv8uIZoIZ_QR5cKwmTq_XstLFIkaNYdc-1707184585806-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'850fc6cca841823e-IAD'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 401 Unauthorized" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "401 Unauthorized" openai._base_client - DEBUG - Encountered httpx.HTTPStatusError Traceback (most recent call last): File "/Users/blake/anaconda3/lib/python3.11/site-packages/openai/_base_client.py", line 939, in _request response.raise_for_status() File "/Users/blake/anaconda3/lib/python3.11/site-packages/httpx/_models.py", line 759, in raise_for_status raise HTTPStatusError(message, request=request, response=self) httpx.HTTPStatusError: Client error '401 Unauthorized' for url 'https://api.openai.com/v1/chat/completions' For more information check: https://developer.mozilla.org/en-US/docs/Web/HTTP/Status/401 openai._base_client - DEBUG - Not retrying openai._base_client - DEBUG - Re-raising status error root - ERROR - An error occurred during the analysis: Error code: 401 - {'error': {'message': 'Incorrect API key provided: sk-8USAO***************************************PfD2. You can find your API key at https://platform.openai.com/account/api-keys.', 'type': 'invalid_request_error', 'param': None, 'code': 'invalid_api_key'}} matplotlib.pyplot - DEBUG - Loaded backend MacOSX version unknown. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False asyncio - DEBUG - Using selector: KqueueSelector httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='api.gradio.app' port=443 local_address=None timeout=3 socket_options=None httpcore.connection - DEBUG - connect_tcp.started host='checkip.amazonaws.com' port=443 local_address=None timeout=3 socket_options=None asyncio - DEBUG - Using selector: KqueueSelector httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='127.0.0.1' port=7860 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'date', b'Tue, 06 Feb 2024 02:08:10 GMT'), (b'server', b'uvicorn'), (b'content-length', b'5'), (b'content-type', b'application/json')]) httpx - INFO - HTTP Request: GET http://127.0.0.1:7860/startup-events "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpx - DEBUG - load_ssl_context verify=False cert=None trust_env=True http2=False httpcore.connection - DEBUG - connect_tcp.started host='127.0.0.1' port=7860 local_address=None timeout=3 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'date', b'Tue, 06 Feb 2024 02:08:10 GMT'), (b'server', b'uvicorn'), (b'content-length', b'8751'), (b'content-type', b'text/html; charset=utf-8')]) httpx - INFO - HTTP Request: HEAD http://127.0.0.1:7860/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='checkip.amazonaws.com' port=443 local_address=None timeout=3 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='checkip.amazonaws.com' timeout=3 httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='checkip.amazonaws.com' timeout=3 httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.gradio.app' timeout=3 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:08:10 GMT'), (b'Server', b'Not Available'), (b'Content-Length', b'12'), (b'Connection', b'keep-alive')]) httpx - INFO - HTTP Request: GET https://checkip.amazonaws.com/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='api.gradio.app' port=443 local_address=None timeout=5 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.gradio.app' timeout=5 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:08:10 GMT'), (b'Server', b'Not Available'), (b'Content-Length', b'12'), (b'Connection', b'keep-alive')]) httpx - INFO - HTTP Request: GET https://checkip.amazonaws.com/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='api.gradio.app' port=443 local_address=None timeout=5 socket_options=None httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.gradio.app' timeout=5 httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:08:10 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'21'), (b'Connection', b'keep-alive'), (b'Server', b'nginx/1.18.0'), (b'Access-Control-Allow-Origin', b'*')]) httpx - INFO - HTTP Request: GET https://api.gradio.app/pkg-version "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:08:11 GMT'), (b'Content-Type', b'text/html; charset=utf-8'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'Server', b'nginx/1.18.0'), (b'Access-Control-Allow-Origin', b'*'), (b'Content-Encoding', b'gzip')]) httpx - INFO - HTTP Request: POST https://api.gradio.app/gradio-launched-telemetry/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:08:11 GMT'), (b'Content-Type', b'text/html; charset=utf-8'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'Server', b'nginx/1.18.0'), (b'Access-Control-Allow-Origin', b'*'), (b'Content-Encoding', b'gzip')]) httpx - INFO - HTTP Request: POST https://api.gradio.app/gradio-initiated-analytics/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete matplotlib.pyplot - DEBUG - Loaded backend macosx version unknown. matplotlib.pyplot - DEBUG - Loaded backend agg version v2.2. root - INFO - Video ID 48L5LeQ06ww extracted from URL. urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=48L5LeQ06ww HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=48L5LeQ06ww&ei=nJTBZdOeG-SOlu8P4pCZUA&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707210508&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=E3DFCAECE62BE3A8F19E08431842EDE4AA89A36D.57AEEB05D673420317049ACE560D3F0FB1879A15&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID 48L5LeQ06ww. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhi my name is Willi and also go by lar I\'m a four data science and applyed math student at UC San Diego and I\'ll be pursuing a graduate degree in computer science starting at fall 2024 in this video I\'m going to apply for this AI cam data science machine learning intern for the summer of 2024 so why I\'m interesting is this position I have a deep passion for leveraging my skills in data science and machine learning to build AI power tools such as the AI teaching assistant like the job description described and also highly motivated to DW meaningful educational outcome um and also have a strong alignment with a focus on education Technologies proven by my past experiencing academic research and my P experience in undergraduate te assistant and I also have a lot of r p experience align with the job requirements so what values I can provide to this program well first with a strong Foundation need a science machine learning and web development I can bring a blend of technical expertise and educational experiences so I have work in various research lab and develop models for data analysis and engage processing I develop applications for larger language models and also find tune a lot of foundation models and also have a lot of R teaching experience such as a Time teaching system at use San Diego in computer science mathematics and data science mathematic and economic courses and also have a 100% student instructor recommendation rate which proven ability in effective teaching and mentoring students and also develop various Educational Tools such as interactive course websites for a lot of commuter science data classes and also a lot of automated grading script and some grade report script and also have tons of leadership and manip experiences I\'ve Le various research projects in a lot of classes and research groups and also mentored a lot of under class working on research project and guided them to Bridge a knowledge Gap so then I help them to fulfill all the prerequisite that they need to do research in a real setting and what I hope to achieve is to develop my skills in artificial intelligence and machine learning while making an impact in the educational technology field I would like to gain insights of challenges and opportunities in the tech education field and continue Innovative AI power teaching tools and ASP by and empower the Next Generation Tech is is doent mentoring as an extension of my teaching assistant experiences so in this U slides I would like to use my published Bela paper as an example of aligning with audience needs so basically we identify that the challenge of students struggling with text embedded in images while studying and we also recognize the limitation of chpd at that time which did not support visual input and our solution is is why don\'t we just build our own model so we built a model called bifa which is a simple multimodal LM for better handling text resal questions and accepted by triple ai24 so basically we focus on making believer adoped at reading and interpreting text embedding within images which directly address a significant need in educational sector where students often encounter the complex diagrams graph and text in visual uh various visual formats so that just as example of proven my ability uh to sense the audience need so then we can address we can uh develop project to address stakeholders um need and in this slide I would like to use b pration as the topic I choose to explain to my grandma so here\'s my version of it I\'m going to say hey Grandma imagine you\'re teaching our cat emo a new tricks Str that shaking hand with me each time it does something right you give it a trick each time if the cat makes a mistake you is guiding on how to do it better next time so in a computer brain which is called Neer Network back application is like teaching the computer to learn from its mistakes when a computer tries to solve a problem and gets it wrong back loation helps you understand where it went wrun and how to improve it it just like computer is practicing and learning just like a cat emo to get better at answering question and solving problems um in a lot of training process and in the end of the video I would like to show the result of me training my cat using similar um using similar format yeah and that\'s basically it I\'ll look forward to talk more about this opportunity in the future interview round and thank you for watching this video\n\nCandidate\'s Number of Pauses:\n1\n\nCandidate\'s Length of Video:\n5.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:08:30 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'486'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296935'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'613ms'), (b'x-request-id', b'52d465b4ea810e399e06f1877ab2b178'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=cLYhhtad9G9lsIyolzOSmtV7Qv0.gfB0BsbzGXSon4U-1707185310-1-AQgJQ2qDnR2/FU6q1/AyF9L9FER9C5yG1+fjbcSCLjRwX98ZslEntQG9V8Q+/0vbf4QeSOPzbCMadtrpwzIRHAo=; path=/; expires=Tue, 06-Feb-24 02:38:30 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=tqn1cVmmjX6SXetNEpm3K8L3j6Whvy7ya_BjrQrL54I-1707185310226-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'850fd878e91c05f6-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" matplotlib.pyplot - DEBUG - Loaded backend MacOSX version unknown. matplotlib.pyplot - DEBUG - Loaded backend agg version v2.2. root - INFO - Video ID 48L5LeQ06ww extracted from URL. urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=48L5LeQ06ww HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=48L5LeQ06ww&ei=rpTBZey_He6P2_gPz_21sAk&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707210526&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=90ABD2492A97088D77D189F5C2A49948B1F99211.EB926350868AB101F6FF2874C6BA580F9608C430&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID 48L5LeQ06ww. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhi my name is Willi and also go by lar I\'m a four data science and applyed math student at UC San Diego and I\'ll be pursuing a graduate degree in computer science starting at fall 2024 in this video I\'m going to apply for this AI cam data science machine learning intern for the summer of 2024 so why I\'m interesting is this position I have a deep passion for leveraging my skills in data science and machine learning to build AI power tools such as the AI teaching assistant like the job description described and also highly motivated to DW meaningful educational outcome um and also have a strong alignment with a focus on education Technologies proven by my past experiencing academic research and my P experience in undergraduate te assistant and I also have a lot of r p experience align with the job requirements so what values I can provide to this program well first with a strong Foundation need a science machine learning and web development I can bring a blend of technical expertise and educational experiences so I have work in various research lab and develop models for data analysis and engage processing I develop applications for larger language models and also find tune a lot of foundation models and also have a lot of R teaching experience such as a Time teaching system at use San Diego in computer science mathematics and data science mathematic and economic courses and also have a 100% student instructor recommendation rate which proven ability in effective teaching and mentoring students and also develop various Educational Tools such as interactive course websites for a lot of commuter science data classes and also a lot of automated grading script and some grade report script and also have tons of leadership and manip experiences I\'ve Le various research projects in a lot of classes and research groups and also mentored a lot of under class working on research project and guided them to Bridge a knowledge Gap so then I help them to fulfill all the prerequisite that they need to do research in a real setting and what I hope to achieve is to develop my skills in artificial intelligence and machine learning while making an impact in the educational technology field I would like to gain insights of challenges and opportunities in the tech education field and continue Innovative AI power teaching tools and ASP by and empower the Next Generation Tech is is doent mentoring as an extension of my teaching assistant experiences so in this U slides I would like to use my published Bela paper as an example of aligning with audience needs so basically we identify that the challenge of students struggling with text embedded in images while studying and we also recognize the limitation of chpd at that time which did not support visual input and our solution is is why don\'t we just build our own model so we built a model called bifa which is a simple multimodal LM for better handling text resal questions and accepted by triple ai24 so basically we focus on making believer adoped at reading and interpreting text embedding within images which directly address a significant need in educational sector where students often encounter the complex diagrams graph and text in visual uh various visual formats so that just as example of proven my ability uh to sense the audience need so then we can address we can uh develop project to address stakeholders um need and in this slide I would like to use b pration as the topic I choose to explain to my grandma so here\'s my version of it I\'m going to say hey Grandma imagine you\'re teaching our cat emo a new tricks Str that shaking hand with me each time it does something right you give it a trick each time if the cat makes a mistake you is guiding on how to do it better next time so in a computer brain which is called Neer Network back application is like teaching the computer to learn from its mistakes when a computer tries to solve a problem and gets it wrong back loation helps you understand where it went wrun and how to improve it it just like computer is practicing and learning just like a cat emo to get better at answering question and solving problems um in a lot of training process and in the end of the video I would like to show the result of me training my cat using similar um using similar format yeah and that\'s basically it I\'ll look forward to talk more about this opportunity in the future interview round and thank you for watching this video\n\nCandidate\'s Number of Pauses:\n1\n\nCandidate\'s Length of Video:\n5.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:08:48 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'580'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296935'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'613ms'), (b'x-request-id', b'd436c70451f7a59e40bcbceb94e921b6'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=kl.BAJUCZqqzjngNex9VfcnZY.NlKuqDDVIZKaj3Oc0-1707185328-1-AZWTgFzozKdnMfxM9cgzh7eszACjkPzzn5esbs3FMm6vACaqecz9G3yTjLUK8uYu9MmRh5r3T5anUEnHP4SqDZQ=; path=/; expires=Tue, 06-Feb-24 02:38:48 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=1v9EVph7bqPeudYNIchgeDoAo5UO.Ke.0CLT5JCZ4ns-1707185328338-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'850fd8e9addb1fd4-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" matplotlib.pyplot - DEBUG - Loaded backend MacOSX version unknown. matplotlib.pyplot - DEBUG - Loaded backend agg version v2.2. root - INFO - Video ID sSO3qWrPb98 extracted from URL. urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=sSO3qWrPb98 HTTP/1.1" 200 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=sSO3qWrPb98&ei=vJTBZYvCMYOL2_gPkc2QqAk&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707210540&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=DEEF1C89CFEBF1B3A0500E2D7380E83D21EE0C45.01D785FA7B87604DA2965B580D95CA54751A1FAC&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID sSO3qWrPb98. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhi I\'m adii and this is my video submission for the internship so for the first question about why I\'m interested in this position uh I\'m interested in this position because I have a passion for AI and for teaching I\'ve been a part of various institutions over the last few years that have allowed me to work with kids and teach them different subjects for example I worked for Camp edmo as a maker instructor where I taught stem subjects like Science and Tech and different forms of engineering to kids I also worked as a sewing counselor at stevenh Kates where I taught kids how to use sewing machines from all ages like 4 to 12 I think that those experiences have allowed me to learn how important it is to teach kids complicated subjects because they can expand their knowledge and learn a lot of new skills that they would have never had before and so I have a genuine passion for teaching children especially when it comes to stem I\'m also a statistics major and so I have a lot of background with data science and AI I have worked with large language models in the past and last quarter I was taking a data science class involving different machine learning algorithms and I found it super interesting and it has really built my passion for AI so I would really love to teach younger students about AI as well uh for the second question of what value I think I can provide I think I have a variety of skills and experience that is relevant to this position as mentioned before I have worked in camps in the past and I have a lot of experience with that I also consider myself to be very perseverant which I think is a necessary skill for this position especially when working with machine learning algorithms and AI it can be difficult but I think that when you\'re working with kids it\'s important to push through and make sure that they don\'t have someone who\'s mentoring them who might get frustrated I think that my perseverance is very good for that kind of thing I also have a variety of coursework as I mentioned that is related to AI um but beyond that I have taken a lot of classes outside of my college I have taken courses through Google on generative Ai and large language models that I think have really expanded my understanding of these things and I think that my dedication to learning outside of the class room is something that would be very positive for this role because students always learn better when they have a teacher who is knowledgeable about the field and is interested in the field and I think that I fit that criteria for the question about what I hope to achieve I hope to build a good educational tool with AI for this project I understand that it is very hard for a lot of people to get educated in this day and age I would love to see us really answer these question questions about the true capabilities of AI using education as a goal um I think that we could really put together something interesting with that and I would absolutely love to be a part of that I also want to help kids really get that better understanding of AI and I think that education is something that a lot of children are familiar with and the problems that come with education they are very familiar with and they\'ll have really interesting insights onto what we can add so I would really love to help them learn uh beyond that I am currently planning to pursue a career in data science and machine learning and so I would really love to get into this internship so that I can kind of understand that field better and get a better idea of what we can do with these Technologies so for the question about the alignment with real world needs and preferences of our audience this year I am putting together a uh conference with my team at the mental health initiative um and for that conference we are very much looking at how we can help our community and meet our community\'s needs so a variety of different things are going into place for that um to best understand what our community needs and serve our community we are getting a large group of volunteers and different people from our community to give us ideas and feedback about what they\' like to see our conference is the largest student run conference in Northern California for mental health so we have a large amount of people who have come before and who are willing to give us ideas so we\'re carefully listening to all of these ideas and putting together our project uh we also have a large group of people from different backgrounds working for us and we like to use these ideas because obviously we\'re a very diverse campus so we like to get as many ideas as possible together so we can really put together a good project um and through this process of kind of working with different people from different backgrounds and talking to different people who are volunteering for us or within the community about what we would they would like to see from us we have been able to put together caucuses reflecting self-care and disability a lot of different interesting ideas are going together and these are all reflective of what the community wants and needs to see from us uh so in that way I think that we are kind of reflecting and building on what the community needs and finally for the question about K nearest neighbor explain this to a 13-year-old uh K nearest neighbor is a supervised learning mechanism it\'s used to determine the category that something fits into based on the surrounding values so to explain this with an example assume we have a large amount of Skittles um some are red and some are blue and we know that the red skittles have slightly more sugar than the blue Skittles so uh let\'s assume we are given a new Skittle and we don\'t know what color it is but we do know the sweetness or the sugar col content of that Skittle so how we\'re going to determine what color Skittle it is is based on the colors of the surrounding Skittles and based on the sugar content of those Skittles so first we\'re going to pick our K value which is the amount of neighbors we\'re going to use um for this example let\'s do three so we\'re going to pick the three Skittles with the closest sugar level to our Skittle because we know its sugar level which is 87 but we don\'t know its actual color so we pick three Skittles two are blue one is red and the blue Skittles have 85 and 86 g of sugar respectively the red Skittle has 1.1 g of sugar now based on basic math we know that the skittle that is we have that is unidentified has closer sugar level to the blue Skittles which are 085 and 86 and our Skittle is 87 compared to the red Skittle that was 1.1 gram of sugar so we know that because it is 0.01 away from the blue Skittles we know that that is probably more likely to be a blue Skittle based on our understanding of what separates these categories so that is essentially what kers neighbor does you take the values for different categories and you use it to determine what category a new item fits into in this case the skittle all right thank you\n\nCandidate\'s Number of Pauses:\n0\n\nCandidate\'s Length of Video:\n7.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:09:04 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'1012'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296290'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'741ms'), (b'x-request-id', b'aa23c17ebb7c486fb8af24d070895aec'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=EUw3vdFRD1VnSTVgSCUmepggEM6Z6uoKffGICm5SyFY-1707185344-1-AYwGnRP9niJvFDegGciuev5BJSkz9K7ME+Mpe8uEuz2trXBTQzEUPUv2ZhskCyfsZCkgBjtgrIUwU/kn4Sdabxo=; path=/; expires=Tue, 06-Feb-24 02:39:04 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=Ipv6vdM3pxwNxPfyQIfo3BLLNiFOT6ArXlWRMip3iHE-1707185344258-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'850fd943ad895a81-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" matplotlib.pyplot - DEBUG - Loaded backend MacOSX version unknown. matplotlib.pyplot - DEBUG - Loaded backend agg version v2.2. root - INFO - Video ID UrGM6OpX_Wc extracted from URL. urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=UrGM6OpX_Wc HTTP/1.1" 200 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=UrGM6OpX_Wc&ei=05TBZZbeKc3bir4P5_qikAg&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707210563&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=782C75D46DCDBF87C48B3C37477BFED881941CF8.E5CA26EF61024F761E0807D4CA4F58946CF1E6E1&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID UrGM6OpX_Wc. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhello everyone this is wet Kosik B currently I\'m pursuing Masters in engineering data science at University of Houston I bring with me 11 years of Industry experience in Aerospace and automotive industry and especially the last six years in data science and machine learning field I would like to answer uh the answers to part one part two and part three uh to start with uh part one motivations and expectations I strongly believe in continuous learning which let me to take a pass from a professional background I mean I do have experience of 11 years I took a break from that professional experience and currently I\'m pursuing master in data s so what internship provide me and what I will be giving back to the organization to my knowledge internship provides a valuable opportunity for me to enhance my skills engage in real world projects and collaborate with the Professionals in the field of data science and Mission learning I had an opportunity of mentoring multiple people in my past organizations and at the same time I was a Mente as well so I know the valuable of internship and coming to this I believe in sharing the knowledge I believe that my background in the machine learning within the Aerospace industry can contribute valuable perspective to the team during my internship my expectations by the end of the internships are I\'ll be gaining incremental knowledge with the rear World perspective and I aspire to experience the satisfaction of learning something new and making a meaningful contribution to the organ organization that provided me this valuable opportunity uh coming to the part two like uh in the internship we play say a strong we PR a strong emphasis on ensuring that our projects right see part two is mainly about asking what I do have in the realtime experience I think I have to spend a good amount of time over here coming to this uh answer to the step two or part two I\'m fortunate to tackle real world challenges and projects in my current Ro involving the task such as creating the database model and conducting root cause analysis for the critical failures when I say current Ro I consider the recent experience as my current Ro like the recent experience with was with kin Aerospace as a databased modeling engineer so what happened is uh I came across uh multiple issues wherein I developed the database models and physics based models uh to solve the issues I\'m particularly proud of an idea I proposed which was integrated into a project and and even CH that to a issue of a patent I\'ll explain what the idea was about uh coming to the aircraft aircraft is equipped with numerous sensors of numerous sensors and these sensors capture the data and we have access to the information but many of times this information is not wisely used and it is limitedly used so we are not make we are not capitalizing the information which we have it in form of a sensus so I was thinking on how to use how to utilize this opportunity of utilizing the data so that uh some real time issues can be challenged so I went into the problem statements that we have that we faced in the aircraft and also went through the data which is available so I came up with an aircraft and uh see what is outcome like this is the revenue of the aircrafts is directly tied with the time aircraft spend in the air the wronger the aircraft is grounded the more money and aircraft carrier loses see often during the aircraft inspections if the service Engineers come to know that there is a damage in one of the damage in the component it it takes a lot of time to identify the root cause of the issue and also takes good amount of time to procure the component so what happens is in this meantime the aircraft will be in the grounding mode and it will be lost to the organization so this increases the downtime and resulting in the financial losses to aircraft so what I did is I examed the historical data collected from the aircraft sensors and devised an algorithm that anticipates the component failures in advance using the both data driven and physics based models see so I have a model which contains both the data driven and the physics based one to make it simple I have a model which contains both the data driven and physics based models and data is fed to this models and you get a pattern historical pattern which will help you to understand when this uh when this component is going to get damaged see this are uh so at the end this algorithm enables the aircraft carriers by providing the earlier insights into the potential component failures where proactively procure and replace the necessary components preventing and increase in the down time this was okay this was appreciated and uh this was appreciated the organization and patent is also given to this and coming to the step three uh or part three like uh explaining I would like to explain the back propagation neural network to a 30 year or 12 year old kid and coming to the neural networks neural network is a method that is inspired by a network of cells in the human bra it\'s a it\'s a definition uh I\'ll explain what back back propagation is for example if you\'re riding a bicycle uh you your intention is to ride the bicycle with a particular constant speed of 10 m per second 10 mil per hour so what happens is you give the throttle you apply throttle onto the bicycle padn and the bicycle starts moving so the moment you get to know that you you don\'t have you will not have any kind of sensors the only sensors is the touch sensor and the the the field you\'re going with the bicycle and the air that is attacking you so the moment you get to know that uh you\'re going faster you stop applying the you start reducing the throttle pedal position so you some kind your propagating the information that you\'re getting from the uh bicycle speed and you\'re making a correction out of this and this method the same methodology is being used in the artificial neural networks to tune the algorithm so that for a right set of combinations you\'ll get the right set of outputs\n\nCandidate\'s Number of Pauses:\n2\n\nCandidate\'s Length of Video:\n7.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:09:25 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'745'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296535'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'693ms'), (b'x-request-id', b'01676662eafb34f5a78ccc1928febb0d'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=G7yGk1PkUuoHOvytlHGottwOCLNN9Feu1lDjtR2RmSw-1707185365-1-ARusan4mok6yOhe4vh3fwaqjBI0eNj+CsMMz8L/vw/I6/J91MHxIzQkHGir4Ov2cQd+/s/RrEGSNWXVIDEWTQVE=; path=/; expires=Tue, 06-Feb-24 02:39:25 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=op.kaepfz8RNJfhyWQOp14MKbQcQqfpQeCqZXstK1kY-1707185365613-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'850fd9d138123afa-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" matplotlib.pyplot - DEBUG - Loaded backend MacOSX version unknown. matplotlib.pyplot - DEBUG - Loaded backend agg version v2.2. root - INFO - Video ID UrGM6OpX_Wc extracted from URL. httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=UrGM6OpX_Wc HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=UrGM6OpX_Wc&ei=2JTBZcPQFMiP2_gP476H4As&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707210568&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=CA7C12EA991F47CF0F4858DC6782AF5ECD3BFDB4.CC391E7E0617E82FD3C28EF7DB9C70792AFE356C&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID UrGM6OpX_Wc. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhello everyone this is wet Kosik B currently I\'m pursuing Masters in engineering data science at University of Houston I bring with me 11 years of Industry experience in Aerospace and automotive industry and especially the last six years in data science and machine learning field I would like to answer uh the answers to part one part two and part three uh to start with uh part one motivations and expectations I strongly believe in continuous learning which let me to take a pass from a professional background I mean I do have experience of 11 years I took a break from that professional experience and currently I\'m pursuing master in data s so what internship provide me and what I will be giving back to the organization to my knowledge internship provides a valuable opportunity for me to enhance my skills engage in real world projects and collaborate with the Professionals in the field of data science and Mission learning I had an opportunity of mentoring multiple people in my past organizations and at the same time I was a Mente as well so I know the valuable of internship and coming to this I believe in sharing the knowledge I believe that my background in the machine learning within the Aerospace industry can contribute valuable perspective to the team during my internship my expectations by the end of the internships are I\'ll be gaining incremental knowledge with the rear World perspective and I aspire to experience the satisfaction of learning something new and making a meaningful contribution to the organ organization that provided me this valuable opportunity uh coming to the part two like uh in the internship we play say a strong we PR a strong emphasis on ensuring that our projects right see part two is mainly about asking what I do have in the realtime experience I think I have to spend a good amount of time over here coming to this uh answer to the step two or part two I\'m fortunate to tackle real world challenges and projects in my current Ro involving the task such as creating the database model and conducting root cause analysis for the critical failures when I say current Ro I consider the recent experience as my current Ro like the recent experience with was with kin Aerospace as a databased modeling engineer so what happened is uh I came across uh multiple issues wherein I developed the database models and physics based models uh to solve the issues I\'m particularly proud of an idea I proposed which was integrated into a project and and even CH that to a issue of a patent I\'ll explain what the idea was about uh coming to the aircraft aircraft is equipped with numerous sensors of numerous sensors and these sensors capture the data and we have access to the information but many of times this information is not wisely used and it is limitedly used so we are not make we are not capitalizing the information which we have it in form of a sensus so I was thinking on how to use how to utilize this opportunity of utilizing the data so that uh some real time issues can be challenged so I went into the problem statements that we have that we faced in the aircraft and also went through the data which is available so I came up with an aircraft and uh see what is outcome like this is the revenue of the aircrafts is directly tied with the time aircraft spend in the air the wronger the aircraft is grounded the more money and aircraft carrier loses see often during the aircraft inspections if the service Engineers come to know that there is a damage in one of the damage in the component it it takes a lot of time to identify the root cause of the issue and also takes good amount of time to procure the component so what happens is in this meantime the aircraft will be in the grounding mode and it will be lost to the organization so this increases the downtime and resulting in the financial losses to aircraft so what I did is I examed the historical data collected from the aircraft sensors and devised an algorithm that anticipates the component failures in advance using the both data driven and physics based models see so I have a model which contains both the data driven and the physics based one to make it simple I have a model which contains both the data driven and physics based models and data is fed to this models and you get a pattern historical pattern which will help you to understand when this uh when this component is going to get damaged see this are uh so at the end this algorithm enables the aircraft carriers by providing the earlier insights into the potential component failures where proactively procure and replace the necessary components preventing and increase in the down time this was okay this was appreciated and uh this was appreciated the organization and patent is also given to this and coming to the step three uh or part three like uh explaining I would like to explain the back propagation neural network to a 30 year or 12 year old kid and coming to the neural networks neural network is a method that is inspired by a network of cells in the human bra it\'s a it\'s a definition uh I\'ll explain what back back propagation is for example if you\'re riding a bicycle uh you your intention is to ride the bicycle with a particular constant speed of 10 m per second 10 mil per hour so what happens is you give the throttle you apply throttle onto the bicycle padn and the bicycle starts moving so the moment you get to know that you you don\'t have you will not have any kind of sensors the only sensors is the touch sensor and the the the field you\'re going with the bicycle and the air that is attacking you so the moment you get to know that uh you\'re going faster you stop applying the you start reducing the throttle pedal position so you some kind your propagating the information that you\'re getting from the uh bicycle speed and you\'re making a correction out of this and this method the same methodology is being used in the artificial neural networks to tune the algorithm so that for a right set of combinations you\'ll get the right set of outputs\n\nCandidate\'s Number of Pauses:\n2\n\nCandidate\'s Length of Video:\n7.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:09:30 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'507'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296535'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'693ms'), (b'x-request-id', b'b70f298ad59fb839abcac06cb0c5d77a'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=hQ_kd6h5CcVJYoFMDJclDjWV040PxBJ85VnnEcoD2r0-1707185370-1-AZoxtzzcXb8M5ED8R3hhEvjwCiX4L7M8ThL0QlC0xIyLo1xmzmbdut4u+bERdmHeP/SOVSeNpOFBa73O+B+fvQc=; path=/; expires=Tue, 06-Feb-24 02:39:30 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=MmXxbKkHQ1zJI_1NRl6JwWsGNKWRYeUEgDa6yXMvqbo-1707185370223-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'850fd9efce783892-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" matplotlib.pyplot - DEBUG - Loaded backend MacOSX version unknown. matplotlib.pyplot - DEBUG - Loaded backend agg version v2.2. root - INFO - Video ID UrGM6OpX_Wc extracted from URL. urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=UrGM6OpX_Wc HTTP/1.1" 200 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=UrGM6OpX_Wc&ei=25TBZY-aMKPnlu8PhLKeqAQ&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707210571&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=1BCA3A8745A1E9DAFE5F208C95A01C99D6306984.E636CEDEF4B2C623693B7FF5CD26ED4F8F915456&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID UrGM6OpX_Wc. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhello everyone this is wet Kosik B currently I\'m pursuing Masters in engineering data science at University of Houston I bring with me 11 years of Industry experience in Aerospace and automotive industry and especially the last six years in data science and machine learning field I would like to answer uh the answers to part one part two and part three uh to start with uh part one motivations and expectations I strongly believe in continuous learning which let me to take a pass from a professional background I mean I do have experience of 11 years I took a break from that professional experience and currently I\'m pursuing master in data s so what internship provide me and what I will be giving back to the organization to my knowledge internship provides a valuable opportunity for me to enhance my skills engage in real world projects and collaborate with the Professionals in the field of data science and Mission learning I had an opportunity of mentoring multiple people in my past organizations and at the same time I was a Mente as well so I know the valuable of internship and coming to this I believe in sharing the knowledge I believe that my background in the machine learning within the Aerospace industry can contribute valuable perspective to the team during my internship my expectations by the end of the internships are I\'ll be gaining incremental knowledge with the rear World perspective and I aspire to experience the satisfaction of learning something new and making a meaningful contribution to the organ organization that provided me this valuable opportunity uh coming to the part two like uh in the internship we play say a strong we PR a strong emphasis on ensuring that our projects right see part two is mainly about asking what I do have in the realtime experience I think I have to spend a good amount of time over here coming to this uh answer to the step two or part two I\'m fortunate to tackle real world challenges and projects in my current Ro involving the task such as creating the database model and conducting root cause analysis for the critical failures when I say current Ro I consider the recent experience as my current Ro like the recent experience with was with kin Aerospace as a databased modeling engineer so what happened is uh I came across uh multiple issues wherein I developed the database models and physics based models uh to solve the issues I\'m particularly proud of an idea I proposed which was integrated into a project and and even CH that to a issue of a patent I\'ll explain what the idea was about uh coming to the aircraft aircraft is equipped with numerous sensors of numerous sensors and these sensors capture the data and we have access to the information but many of times this information is not wisely used and it is limitedly used so we are not make we are not capitalizing the information which we have it in form of a sensus so I was thinking on how to use how to utilize this opportunity of utilizing the data so that uh some real time issues can be challenged so I went into the problem statements that we have that we faced in the aircraft and also went through the data which is available so I came up with an aircraft and uh see what is outcome like this is the revenue of the aircrafts is directly tied with the time aircraft spend in the air the wronger the aircraft is grounded the more money and aircraft carrier loses see often during the aircraft inspections if the service Engineers come to know that there is a damage in one of the damage in the component it it takes a lot of time to identify the root cause of the issue and also takes good amount of time to procure the component so what happens is in this meantime the aircraft will be in the grounding mode and it will be lost to the organization so this increases the downtime and resulting in the financial losses to aircraft so what I did is I examed the historical data collected from the aircraft sensors and devised an algorithm that anticipates the component failures in advance using the both data driven and physics based models see so I have a model which contains both the data driven and the physics based one to make it simple I have a model which contains both the data driven and physics based models and data is fed to this models and you get a pattern historical pattern which will help you to understand when this uh when this component is going to get damaged see this are uh so at the end this algorithm enables the aircraft carriers by providing the earlier insights into the potential component failures where proactively procure and replace the necessary components preventing and increase in the down time this was okay this was appreciated and uh this was appreciated the organization and patent is also given to this and coming to the step three uh or part three like uh explaining I would like to explain the back propagation neural network to a 30 year or 12 year old kid and coming to the neural networks neural network is a method that is inspired by a network of cells in the human bra it\'s a it\'s a definition uh I\'ll explain what back back propagation is for example if you\'re riding a bicycle uh you your intention is to ride the bicycle with a particular constant speed of 10 m per second 10 mil per hour so what happens is you give the throttle you apply throttle onto the bicycle padn and the bicycle starts moving so the moment you get to know that you you don\'t have you will not have any kind of sensors the only sensors is the touch sensor and the the the field you\'re going with the bicycle and the air that is attacking you so the moment you get to know that uh you\'re going faster you stop applying the you start reducing the throttle pedal position so you some kind your propagating the information that you\'re getting from the uh bicycle speed and you\'re making a correction out of this and this method the same methodology is being used in the artificial neural networks to tune the algorithm so that for a right set of combinations you\'ll get the right set of outputs\n\nCandidate\'s Number of Pauses:\n2\n\nCandidate\'s Length of Video:\n7.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:09:34 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'875'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296535'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'693ms'), (b'x-request-id', b'abd83edcd3ccbbedae97bd1096d09706'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=hx5guOpCNRbMeNjVj7RZpgBeMV5Fh0Y2ikAlzl13Zo0-1707185374-1-AUZGWpAS94c9GyHkHWSnKZHSfngNVFm1APUt2M1u0cOj2RkGXziMxCLc19PnVZkLPgB7qcxjpI9128MpZ8Bp3q0=; path=/; expires=Tue, 06-Feb-24 02:39:34 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=7U3kCrUN2.iGBhvtS2CeJN7CV7bZBCiAD0dGAm7psIM-1707185374430-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'850fda04ad0f38dd-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" matplotlib.pyplot - DEBUG - Loaded backend MacOSX version unknown. matplotlib.pyplot - DEBUG - Loaded backend agg version v2.2. root - INFO - Video ID UrGM6OpX_Wc extracted from URL. urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=UrGM6OpX_Wc HTTP/1.1" 200 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=UrGM6OpX_Wc&ei=4JTBZe6-ENfsir4PvOqBGA&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707210576&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=3D7B88CFF2B5A69D59E94A4D4FE99424AF69DD89.5B8BCB9921A9E560C137EE1B9C606C3ED3BA7D6C&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID UrGM6OpX_Wc. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhello everyone this is wet Kosik B currently I\'m pursuing Masters in engineering data science at University of Houston I bring with me 11 years of Industry experience in Aerospace and automotive industry and especially the last six years in data science and machine learning field I would like to answer uh the answers to part one part two and part three uh to start with uh part one motivations and expectations I strongly believe in continuous learning which let me to take a pass from a professional background I mean I do have experience of 11 years I took a break from that professional experience and currently I\'m pursuing master in data s so what internship provide me and what I will be giving back to the organization to my knowledge internship provides a valuable opportunity for me to enhance my skills engage in real world projects and collaborate with the Professionals in the field of data science and Mission learning I had an opportunity of mentoring multiple people in my past organizations and at the same time I was a Mente as well so I know the valuable of internship and coming to this I believe in sharing the knowledge I believe that my background in the machine learning within the Aerospace industry can contribute valuable perspective to the team during my internship my expectations by the end of the internships are I\'ll be gaining incremental knowledge with the rear World perspective and I aspire to experience the satisfaction of learning something new and making a meaningful contribution to the organ organization that provided me this valuable opportunity uh coming to the part two like uh in the internship we play say a strong we PR a strong emphasis on ensuring that our projects right see part two is mainly about asking what I do have in the realtime experience I think I have to spend a good amount of time over here coming to this uh answer to the step two or part two I\'m fortunate to tackle real world challenges and projects in my current Ro involving the task such as creating the database model and conducting root cause analysis for the critical failures when I say current Ro I consider the recent experience as my current Ro like the recent experience with was with kin Aerospace as a databased modeling engineer so what happened is uh I came across uh multiple issues wherein I developed the database models and physics based models uh to solve the issues I\'m particularly proud of an idea I proposed which was integrated into a project and and even CH that to a issue of a patent I\'ll explain what the idea was about uh coming to the aircraft aircraft is equipped with numerous sensors of numerous sensors and these sensors capture the data and we have access to the information but many of times this information is not wisely used and it is limitedly used so we are not make we are not capitalizing the information which we have it in form of a sensus so I was thinking on how to use how to utilize this opportunity of utilizing the data so that uh some real time issues can be challenged so I went into the problem statements that we have that we faced in the aircraft and also went through the data which is available so I came up with an aircraft and uh see what is outcome like this is the revenue of the aircrafts is directly tied with the time aircraft spend in the air the wronger the aircraft is grounded the more money and aircraft carrier loses see often during the aircraft inspections if the service Engineers come to know that there is a damage in one of the damage in the component it it takes a lot of time to identify the root cause of the issue and also takes good amount of time to procure the component so what happens is in this meantime the aircraft will be in the grounding mode and it will be lost to the organization so this increases the downtime and resulting in the financial losses to aircraft so what I did is I examed the historical data collected from the aircraft sensors and devised an algorithm that anticipates the component failures in advance using the both data driven and physics based models see so I have a model which contains both the data driven and the physics based one to make it simple I have a model which contains both the data driven and physics based models and data is fed to this models and you get a pattern historical pattern which will help you to understand when this uh when this component is going to get damaged see this are uh so at the end this algorithm enables the aircraft carriers by providing the earlier insights into the potential component failures where proactively procure and replace the necessary components preventing and increase in the down time this was okay this was appreciated and uh this was appreciated the organization and patent is also given to this and coming to the step three uh or part three like uh explaining I would like to explain the back propagation neural network to a 30 year or 12 year old kid and coming to the neural networks neural network is a method that is inspired by a network of cells in the human bra it\'s a it\'s a definition uh I\'ll explain what back back propagation is for example if you\'re riding a bicycle uh you your intention is to ride the bicycle with a particular constant speed of 10 m per second 10 mil per hour so what happens is you give the throttle you apply throttle onto the bicycle padn and the bicycle starts moving so the moment you get to know that you you don\'t have you will not have any kind of sensors the only sensors is the touch sensor and the the the field you\'re going with the bicycle and the air that is attacking you so the moment you get to know that uh you\'re going faster you stop applying the you start reducing the throttle pedal position so you some kind your propagating the information that you\'re getting from the uh bicycle speed and you\'re making a correction out of this and this method the same methodology is being used in the artificial neural networks to tune the algorithm so that for a right set of combinations you\'ll get the right set of outputs\n\nCandidate\'s Number of Pauses:\n2\n\nCandidate\'s Length of Video:\n7.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:09:38 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'816'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296535'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'693ms'), (b'x-request-id', b'db2138e20bb06c530b27cd9271c5b2a8'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=Y7u9HkcL.3fuZHU6Kuybhpi71IifBiTV1jyT.ZwaMw4-1707185378-1-AQxspK1exnanLkKSUXmxBqG+wkStF3c2weqWstV7YG5ee8+S/vOXVgLJFhMrqQ44ILj6xlrHJhCYt1JsU08tMis=; path=/; expires=Tue, 06-Feb-24 02:39:38 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=LMqqws4fM0Us8.wzHLjtK9_CsId2D8amUnfvB_Glrv4-1707185378233-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'850fda1f5d410737-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" matplotlib.pyplot - DEBUG - Loaded backend MacOSX version unknown. matplotlib.pyplot - DEBUG - Loaded backend agg version v2.2. root - INFO - Video ID UrGM6OpX_Wc extracted from URL. urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=UrGM6OpX_Wc HTTP/1.1" 200 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=UrGM6OpX_Wc&ei=45TBZbrzJo2P2_gP5bW4yAs&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707210579&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=EA90BC1A4349CAAAD7FB9A99BC6D2559F0D7C896.7000473F375AD83948AD790941D65F02C2FE83F1&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID UrGM6OpX_Wc. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhello everyone this is wet Kosik B currently I\'m pursuing Masters in engineering data science at University of Houston I bring with me 11 years of Industry experience in Aerospace and automotive industry and especially the last six years in data science and machine learning field I would like to answer uh the answers to part one part two and part three uh to start with uh part one motivations and expectations I strongly believe in continuous learning which let me to take a pass from a professional background I mean I do have experience of 11 years I took a break from that professional experience and currently I\'m pursuing master in data s so what internship provide me and what I will be giving back to the organization to my knowledge internship provides a valuable opportunity for me to enhance my skills engage in real world projects and collaborate with the Professionals in the field of data science and Mission learning I had an opportunity of mentoring multiple people in my past organizations and at the same time I was a Mente as well so I know the valuable of internship and coming to this I believe in sharing the knowledge I believe that my background in the machine learning within the Aerospace industry can contribute valuable perspective to the team during my internship my expectations by the end of the internships are I\'ll be gaining incremental knowledge with the rear World perspective and I aspire to experience the satisfaction of learning something new and making a meaningful contribution to the organ organization that provided me this valuable opportunity uh coming to the part two like uh in the internship we play say a strong we PR a strong emphasis on ensuring that our projects right see part two is mainly about asking what I do have in the realtime experience I think I have to spend a good amount of time over here coming to this uh answer to the step two or part two I\'m fortunate to tackle real world challenges and projects in my current Ro involving the task such as creating the database model and conducting root cause analysis for the critical failures when I say current Ro I consider the recent experience as my current Ro like the recent experience with was with kin Aerospace as a databased modeling engineer so what happened is uh I came across uh multiple issues wherein I developed the database models and physics based models uh to solve the issues I\'m particularly proud of an idea I proposed which was integrated into a project and and even CH that to a issue of a patent I\'ll explain what the idea was about uh coming to the aircraft aircraft is equipped with numerous sensors of numerous sensors and these sensors capture the data and we have access to the information but many of times this information is not wisely used and it is limitedly used so we are not make we are not capitalizing the information which we have it in form of a sensus so I was thinking on how to use how to utilize this opportunity of utilizing the data so that uh some real time issues can be challenged so I went into the problem statements that we have that we faced in the aircraft and also went through the data which is available so I came up with an aircraft and uh see what is outcome like this is the revenue of the aircrafts is directly tied with the time aircraft spend in the air the wronger the aircraft is grounded the more money and aircraft carrier loses see often during the aircraft inspections if the service Engineers come to know that there is a damage in one of the damage in the component it it takes a lot of time to identify the root cause of the issue and also takes good amount of time to procure the component so what happens is in this meantime the aircraft will be in the grounding mode and it will be lost to the organization so this increases the downtime and resulting in the financial losses to aircraft so what I did is I examed the historical data collected from the aircraft sensors and devised an algorithm that anticipates the component failures in advance using the both data driven and physics based models see so I have a model which contains both the data driven and the physics based one to make it simple I have a model which contains both the data driven and physics based models and data is fed to this models and you get a pattern historical pattern which will help you to understand when this uh when this component is going to get damaged see this are uh so at the end this algorithm enables the aircraft carriers by providing the earlier insights into the potential component failures where proactively procure and replace the necessary components preventing and increase in the down time this was okay this was appreciated and uh this was appreciated the organization and patent is also given to this and coming to the step three uh or part three like uh explaining I would like to explain the back propagation neural network to a 30 year or 12 year old kid and coming to the neural networks neural network is a method that is inspired by a network of cells in the human bra it\'s a it\'s a definition uh I\'ll explain what back back propagation is for example if you\'re riding a bicycle uh you your intention is to ride the bicycle with a particular constant speed of 10 m per second 10 mil per hour so what happens is you give the throttle you apply throttle onto the bicycle padn and the bicycle starts moving so the moment you get to know that you you don\'t have you will not have any kind of sensors the only sensors is the touch sensor and the the the field you\'re going with the bicycle and the air that is attacking you so the moment you get to know that uh you\'re going faster you stop applying the you start reducing the throttle pedal position so you some kind your propagating the information that you\'re getting from the uh bicycle speed and you\'re making a correction out of this and this method the same methodology is being used in the artificial neural networks to tune the algorithm so that for a right set of combinations you\'ll get the right set of outputs\n\nCandidate\'s Number of Pauses:\n2\n\nCandidate\'s Length of Video:\n7.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:09:42 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'1193'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296535'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'693ms'), (b'x-request-id', b'f965af93ed1d571f265d30b83d3aa5b8'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=Q_9u6vq637nxvl77N0SkOwHWuvbBDC.kF88vPlhPmDM-1707185382-1-AS5yUeFhluGj2k4DliwOEEdV/AsAwPAXLhmNvZ1dQ45nXp8Ikw0WZqvInxBaYHjiWd7CCzCBHJ403nq4V48TXIY=; path=/; expires=Tue, 06-Feb-24 02:39:42 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=YL8lEKDRFR311AJIbfQxo_U6zSSaW1QOxfEtGtGbWeY-1707185382580-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'850fda35abdc396a-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" matplotlib.pyplot - DEBUG - Loaded backend MacOSX version unknown. matplotlib.pyplot - DEBUG - Loaded backend agg version v2.2. root - INFO - Video ID UrGM6OpX_Wc extracted from URL. urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=UrGM6OpX_Wc HTTP/1.1" 200 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=UrGM6OpX_Wc&ei=6JTBZfalE5jDlu8P0Imj2Ag&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707210584&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=63B3C1524FF747E3AEC08735B4F5EEFCEC97200B.D58A8C4F850BC704614525F0FBCE153D1B8FB352&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID UrGM6OpX_Wc. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhello everyone this is wet Kosik B currently I\'m pursuing Masters in engineering data science at University of Houston I bring with me 11 years of Industry experience in Aerospace and automotive industry and especially the last six years in data science and machine learning field I would like to answer uh the answers to part one part two and part three uh to start with uh part one motivations and expectations I strongly believe in continuous learning which let me to take a pass from a professional background I mean I do have experience of 11 years I took a break from that professional experience and currently I\'m pursuing master in data s so what internship provide me and what I will be giving back to the organization to my knowledge internship provides a valuable opportunity for me to enhance my skills engage in real world projects and collaborate with the Professionals in the field of data science and Mission learning I had an opportunity of mentoring multiple people in my past organizations and at the same time I was a Mente as well so I know the valuable of internship and coming to this I believe in sharing the knowledge I believe that my background in the machine learning within the Aerospace industry can contribute valuable perspective to the team during my internship my expectations by the end of the internships are I\'ll be gaining incremental knowledge with the rear World perspective and I aspire to experience the satisfaction of learning something new and making a meaningful contribution to the organ organization that provided me this valuable opportunity uh coming to the part two like uh in the internship we play say a strong we PR a strong emphasis on ensuring that our projects right see part two is mainly about asking what I do have in the realtime experience I think I have to spend a good amount of time over here coming to this uh answer to the step two or part two I\'m fortunate to tackle real world challenges and projects in my current Ro involving the task such as creating the database model and conducting root cause analysis for the critical failures when I say current Ro I consider the recent experience as my current Ro like the recent experience with was with kin Aerospace as a databased modeling engineer so what happened is uh I came across uh multiple issues wherein I developed the database models and physics based models uh to solve the issues I\'m particularly proud of an idea I proposed which was integrated into a project and and even CH that to a issue of a patent I\'ll explain what the idea was about uh coming to the aircraft aircraft is equipped with numerous sensors of numerous sensors and these sensors capture the data and we have access to the information but many of times this information is not wisely used and it is limitedly used so we are not make we are not capitalizing the information which we have it in form of a sensus so I was thinking on how to use how to utilize this opportunity of utilizing the data so that uh some real time issues can be challenged so I went into the problem statements that we have that we faced in the aircraft and also went through the data which is available so I came up with an aircraft and uh see what is outcome like this is the revenue of the aircrafts is directly tied with the time aircraft spend in the air the wronger the aircraft is grounded the more money and aircraft carrier loses see often during the aircraft inspections if the service Engineers come to know that there is a damage in one of the damage in the component it it takes a lot of time to identify the root cause of the issue and also takes good amount of time to procure the component so what happens is in this meantime the aircraft will be in the grounding mode and it will be lost to the organization so this increases the downtime and resulting in the financial losses to aircraft so what I did is I examed the historical data collected from the aircraft sensors and devised an algorithm that anticipates the component failures in advance using the both data driven and physics based models see so I have a model which contains both the data driven and the physics based one to make it simple I have a model which contains both the data driven and physics based models and data is fed to this models and you get a pattern historical pattern which will help you to understand when this uh when this component is going to get damaged see this are uh so at the end this algorithm enables the aircraft carriers by providing the earlier insights into the potential component failures where proactively procure and replace the necessary components preventing and increase in the down time this was okay this was appreciated and uh this was appreciated the organization and patent is also given to this and coming to the step three uh or part three like uh explaining I would like to explain the back propagation neural network to a 30 year or 12 year old kid and coming to the neural networks neural network is a method that is inspired by a network of cells in the human bra it\'s a it\'s a definition uh I\'ll explain what back back propagation is for example if you\'re riding a bicycle uh you your intention is to ride the bicycle with a particular constant speed of 10 m per second 10 mil per hour so what happens is you give the throttle you apply throttle onto the bicycle padn and the bicycle starts moving so the moment you get to know that you you don\'t have you will not have any kind of sensors the only sensors is the touch sensor and the the the field you\'re going with the bicycle and the air that is attacking you so the moment you get to know that uh you\'re going faster you stop applying the you start reducing the throttle pedal position so you some kind your propagating the information that you\'re getting from the uh bicycle speed and you\'re making a correction out of this and this method the same methodology is being used in the artificial neural networks to tune the algorithm so that for a right set of combinations you\'ll get the right set of outputs\n\nCandidate\'s Number of Pauses:\n2\n\nCandidate\'s Length of Video:\n7.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:09:46 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'907'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296535'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'693ms'), (b'x-request-id', b'4be40d3610334e08ac3b67940b7e0afb'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=gKfBcJCLN9H5Xe3Im7281JzNByPJ0MzJFUIN9iKttD0-1707185386-1-AZ3yteSVWHWARsQYjym4US9hOb/0DlUKbmS2gS1j+wjF4JJvgkzvRRU4LTvy6L7/evZeK6jjs4dGopd7gu9ADAg=; path=/; expires=Tue, 06-Feb-24 02:39:46 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=GAUri6XfBOd4Qwwaxm21lPPHm2sldo49TgSmZH05ggs-1707185386480-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'850fda52bdde05e5-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" matplotlib.pyplot - DEBUG - Loaded backend MacOSX version unknown. matplotlib.pyplot - DEBUG - Loaded backend agg version v2.2. root - INFO - Video ID UrGM6OpX_Wc extracted from URL. urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=UrGM6OpX_Wc HTTP/1.1" 200 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=UrGM6OpX_Wc&ei=65TBZarpN7Ldir4PoIy4mAk&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707210587&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=5440E8505E7860F7B03A1D7EB9065121AAE7CEAC.C202D1F4321F9D26BAC5011E0AAC8C557AC80691&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID UrGM6OpX_Wc. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhello everyone this is wet Kosik B currently I\'m pursuing Masters in engineering data science at University of Houston I bring with me 11 years of Industry experience in Aerospace and automotive industry and especially the last six years in data science and machine learning field I would like to answer uh the answers to part one part two and part three uh to start with uh part one motivations and expectations I strongly believe in continuous learning which let me to take a pass from a professional background I mean I do have experience of 11 years I took a break from that professional experience and currently I\'m pursuing master in data s so what internship provide me and what I will be giving back to the organization to my knowledge internship provides a valuable opportunity for me to enhance my skills engage in real world projects and collaborate with the Professionals in the field of data science and Mission learning I had an opportunity of mentoring multiple people in my past organizations and at the same time I was a Mente as well so I know the valuable of internship and coming to this I believe in sharing the knowledge I believe that my background in the machine learning within the Aerospace industry can contribute valuable perspective to the team during my internship my expectations by the end of the internships are I\'ll be gaining incremental knowledge with the rear World perspective and I aspire to experience the satisfaction of learning something new and making a meaningful contribution to the organ organization that provided me this valuable opportunity uh coming to the part two like uh in the internship we play say a strong we PR a strong emphasis on ensuring that our projects right see part two is mainly about asking what I do have in the realtime experience I think I have to spend a good amount of time over here coming to this uh answer to the step two or part two I\'m fortunate to tackle real world challenges and projects in my current Ro involving the task such as creating the database model and conducting root cause analysis for the critical failures when I say current Ro I consider the recent experience as my current Ro like the recent experience with was with kin Aerospace as a databased modeling engineer so what happened is uh I came across uh multiple issues wherein I developed the database models and physics based models uh to solve the issues I\'m particularly proud of an idea I proposed which was integrated into a project and and even CH that to a issue of a patent I\'ll explain what the idea was about uh coming to the aircraft aircraft is equipped with numerous sensors of numerous sensors and these sensors capture the data and we have access to the information but many of times this information is not wisely used and it is limitedly used so we are not make we are not capitalizing the information which we have it in form of a sensus so I was thinking on how to use how to utilize this opportunity of utilizing the data so that uh some real time issues can be challenged so I went into the problem statements that we have that we faced in the aircraft and also went through the data which is available so I came up with an aircraft and uh see what is outcome like this is the revenue of the aircrafts is directly tied with the time aircraft spend in the air the wronger the aircraft is grounded the more money and aircraft carrier loses see often during the aircraft inspections if the service Engineers come to know that there is a damage in one of the damage in the component it it takes a lot of time to identify the root cause of the issue and also takes good amount of time to procure the component so what happens is in this meantime the aircraft will be in the grounding mode and it will be lost to the organization so this increases the downtime and resulting in the financial losses to aircraft so what I did is I examed the historical data collected from the aircraft sensors and devised an algorithm that anticipates the component failures in advance using the both data driven and physics based models see so I have a model which contains both the data driven and the physics based one to make it simple I have a model which contains both the data driven and physics based models and data is fed to this models and you get a pattern historical pattern which will help you to understand when this uh when this component is going to get damaged see this are uh so at the end this algorithm enables the aircraft carriers by providing the earlier insights into the potential component failures where proactively procure and replace the necessary components preventing and increase in the down time this was okay this was appreciated and uh this was appreciated the organization and patent is also given to this and coming to the step three uh or part three like uh explaining I would like to explain the back propagation neural network to a 30 year or 12 year old kid and coming to the neural networks neural network is a method that is inspired by a network of cells in the human bra it\'s a it\'s a definition uh I\'ll explain what back back propagation is for example if you\'re riding a bicycle uh you your intention is to ride the bicycle with a particular constant speed of 10 m per second 10 mil per hour so what happens is you give the throttle you apply throttle onto the bicycle padn and the bicycle starts moving so the moment you get to know that you you don\'t have you will not have any kind of sensors the only sensors is the touch sensor and the the the field you\'re going with the bicycle and the air that is attacking you so the moment you get to know that uh you\'re going faster you stop applying the you start reducing the throttle pedal position so you some kind your propagating the information that you\'re getting from the uh bicycle speed and you\'re making a correction out of this and this method the same methodology is being used in the artificial neural networks to tune the algorithm so that for a right set of combinations you\'ll get the right set of outputs\n\nCandidate\'s Number of Pauses:\n2\n\nCandidate\'s Length of Video:\n7.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:09:49 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'798'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296535'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'693ms'), (b'x-request-id', b'da177702aa99d5740840833c2a52c9c2'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=CDxwrqJxQlud2kxrV4LsrvOVIxRJznQnMyKhjV86yTk-1707185389-1-AVSLqWB8qXVTyv/bFu3xBfOxv5BmIwKcJXQ1wQaeNzTxfpnBJbUeOHjVMdd3spJ9bVqy/4B3T7hjxr+DJ3/wa9E=; path=/; expires=Tue, 06-Feb-24 02:39:49 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=B8TetmkhoiPpYaIpX8XLjSdKJdO_oGqdCIrTDQEdClA-1707185389994-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'850fda699eda0569-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" matplotlib.pyplot - DEBUG - Loaded backend MacOSX version unknown. matplotlib.pyplot - DEBUG - Loaded backend agg version v2.2. root - INFO - Video ID UrGM6OpX_Wc extracted from URL. urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=UrGM6OpX_Wc HTTP/1.1" 200 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=UrGM6OpX_Wc&ei=75TBZZy6Ie6P2_gPz_21sAk&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707210591&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=92654097A7DE122E7ACAF412325A1D49592F992E.93647DC89ABD92B06996740399562B65EE007CED&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID UrGM6OpX_Wc. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhello everyone this is wet Kosik B currently I\'m pursuing Masters in engineering data science at University of Houston I bring with me 11 years of Industry experience in Aerospace and automotive industry and especially the last six years in data science and machine learning field I would like to answer uh the answers to part one part two and part three uh to start with uh part one motivations and expectations I strongly believe in continuous learning which let me to take a pass from a professional background I mean I do have experience of 11 years I took a break from that professional experience and currently I\'m pursuing master in data s so what internship provide me and what I will be giving back to the organization to my knowledge internship provides a valuable opportunity for me to enhance my skills engage in real world projects and collaborate with the Professionals in the field of data science and Mission learning I had an opportunity of mentoring multiple people in my past organizations and at the same time I was a Mente as well so I know the valuable of internship and coming to this I believe in sharing the knowledge I believe that my background in the machine learning within the Aerospace industry can contribute valuable perspective to the team during my internship my expectations by the end of the internships are I\'ll be gaining incremental knowledge with the rear World perspective and I aspire to experience the satisfaction of learning something new and making a meaningful contribution to the organ organization that provided me this valuable opportunity uh coming to the part two like uh in the internship we play say a strong we PR a strong emphasis on ensuring that our projects right see part two is mainly about asking what I do have in the realtime experience I think I have to spend a good amount of time over here coming to this uh answer to the step two or part two I\'m fortunate to tackle real world challenges and projects in my current Ro involving the task such as creating the database model and conducting root cause analysis for the critical failures when I say current Ro I consider the recent experience as my current Ro like the recent experience with was with kin Aerospace as a databased modeling engineer so what happened is uh I came across uh multiple issues wherein I developed the database models and physics based models uh to solve the issues I\'m particularly proud of an idea I proposed which was integrated into a project and and even CH that to a issue of a patent I\'ll explain what the idea was about uh coming to the aircraft aircraft is equipped with numerous sensors of numerous sensors and these sensors capture the data and we have access to the information but many of times this information is not wisely used and it is limitedly used so we are not make we are not capitalizing the information which we have it in form of a sensus so I was thinking on how to use how to utilize this opportunity of utilizing the data so that uh some real time issues can be challenged so I went into the problem statements that we have that we faced in the aircraft and also went through the data which is available so I came up with an aircraft and uh see what is outcome like this is the revenue of the aircrafts is directly tied with the time aircraft spend in the air the wronger the aircraft is grounded the more money and aircraft carrier loses see often during the aircraft inspections if the service Engineers come to know that there is a damage in one of the damage in the component it it takes a lot of time to identify the root cause of the issue and also takes good amount of time to procure the component so what happens is in this meantime the aircraft will be in the grounding mode and it will be lost to the organization so this increases the downtime and resulting in the financial losses to aircraft so what I did is I examed the historical data collected from the aircraft sensors and devised an algorithm that anticipates the component failures in advance using the both data driven and physics based models see so I have a model which contains both the data driven and the physics based one to make it simple I have a model which contains both the data driven and physics based models and data is fed to this models and you get a pattern historical pattern which will help you to understand when this uh when this component is going to get damaged see this are uh so at the end this algorithm enables the aircraft carriers by providing the earlier insights into the potential component failures where proactively procure and replace the necessary components preventing and increase in the down time this was okay this was appreciated and uh this was appreciated the organization and patent is also given to this and coming to the step three uh or part three like uh explaining I would like to explain the back propagation neural network to a 30 year or 12 year old kid and coming to the neural networks neural network is a method that is inspired by a network of cells in the human bra it\'s a it\'s a definition uh I\'ll explain what back back propagation is for example if you\'re riding a bicycle uh you your intention is to ride the bicycle with a particular constant speed of 10 m per second 10 mil per hour so what happens is you give the throttle you apply throttle onto the bicycle padn and the bicycle starts moving so the moment you get to know that you you don\'t have you will not have any kind of sensors the only sensors is the touch sensor and the the the field you\'re going with the bicycle and the air that is attacking you so the moment you get to know that uh you\'re going faster you stop applying the you start reducing the throttle pedal position so you some kind your propagating the information that you\'re getting from the uh bicycle speed and you\'re making a correction out of this and this method the same methodology is being used in the artificial neural networks to tune the algorithm so that for a right set of combinations you\'ll get the right set of outputs\n\nCandidate\'s Number of Pauses:\n2\n\nCandidate\'s Length of Video:\n7.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:09:53 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'393'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296535'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'693ms'), (b'x-request-id', b'c830a2584e8f026fb2f8ccef918842f3'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=sEKl8RT4qA7uTHYpRybQZkvYagXlhIiKAaUJbDGb5bA-1707185393-1-AR0FF3rlccxQeBNACz3TiMavezK7o5/SUGLlLaNKDqWcGFH2GuRPGoOqVau8uzXkEW+UpGAML4iXb3k+QJzQ9ZQ=; path=/; expires=Tue, 06-Feb-24 02:39:53 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=B_1uYT.Q4IE1Sdxjx18GQ5cg_YVAh_Ikz451vBN1P6o-1707185393736-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'850fda801c377fff-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" matplotlib.pyplot - DEBUG - Loaded backend MacOSX version unknown. matplotlib.pyplot - DEBUG - Loaded backend agg version v2.2. root - INFO - Video ID UrGM6OpX_Wc extracted from URL. urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=UrGM6OpX_Wc HTTP/1.1" 200 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=UrGM6OpX_Wc&ei=85TBZdLNK8fClu8Pu6eMuAk&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707210595&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=BC4411F24CBA33065F5C22171CD7AFAC04EA7D0B.1F8776C68FAEBACDB22FE123C4348063D265D33C&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID UrGM6OpX_Wc. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhello everyone this is wet Kosik B currently I\'m pursuing Masters in engineering data science at University of Houston I bring with me 11 years of Industry experience in Aerospace and automotive industry and especially the last six years in data science and machine learning field I would like to answer uh the answers to part one part two and part three uh to start with uh part one motivations and expectations I strongly believe in continuous learning which let me to take a pass from a professional background I mean I do have experience of 11 years I took a break from that professional experience and currently I\'m pursuing master in data s so what internship provide me and what I will be giving back to the organization to my knowledge internship provides a valuable opportunity for me to enhance my skills engage in real world projects and collaborate with the Professionals in the field of data science and Mission learning I had an opportunity of mentoring multiple people in my past organizations and at the same time I was a Mente as well so I know the valuable of internship and coming to this I believe in sharing the knowledge I believe that my background in the machine learning within the Aerospace industry can contribute valuable perspective to the team during my internship my expectations by the end of the internships are I\'ll be gaining incremental knowledge with the rear World perspective and I aspire to experience the satisfaction of learning something new and making a meaningful contribution to the organ organization that provided me this valuable opportunity uh coming to the part two like uh in the internship we play say a strong we PR a strong emphasis on ensuring that our projects right see part two is mainly about asking what I do have in the realtime experience I think I have to spend a good amount of time over here coming to this uh answer to the step two or part two I\'m fortunate to tackle real world challenges and projects in my current Ro involving the task such as creating the database model and conducting root cause analysis for the critical failures when I say current Ro I consider the recent experience as my current Ro like the recent experience with was with kin Aerospace as a databased modeling engineer so what happened is uh I came across uh multiple issues wherein I developed the database models and physics based models uh to solve the issues I\'m particularly proud of an idea I proposed which was integrated into a project and and even CH that to a issue of a patent I\'ll explain what the idea was about uh coming to the aircraft aircraft is equipped with numerous sensors of numerous sensors and these sensors capture the data and we have access to the information but many of times this information is not wisely used and it is limitedly used so we are not make we are not capitalizing the information which we have it in form of a sensus so I was thinking on how to use how to utilize this opportunity of utilizing the data so that uh some real time issues can be challenged so I went into the problem statements that we have that we faced in the aircraft and also went through the data which is available so I came up with an aircraft and uh see what is outcome like this is the revenue of the aircrafts is directly tied with the time aircraft spend in the air the wronger the aircraft is grounded the more money and aircraft carrier loses see often during the aircraft inspections if the service Engineers come to know that there is a damage in one of the damage in the component it it takes a lot of time to identify the root cause of the issue and also takes good amount of time to procure the component so what happens is in this meantime the aircraft will be in the grounding mode and it will be lost to the organization so this increases the downtime and resulting in the financial losses to aircraft so what I did is I examed the historical data collected from the aircraft sensors and devised an algorithm that anticipates the component failures in advance using the both data driven and physics based models see so I have a model which contains both the data driven and the physics based one to make it simple I have a model which contains both the data driven and physics based models and data is fed to this models and you get a pattern historical pattern which will help you to understand when this uh when this component is going to get damaged see this are uh so at the end this algorithm enables the aircraft carriers by providing the earlier insights into the potential component failures where proactively procure and replace the necessary components preventing and increase in the down time this was okay this was appreciated and uh this was appreciated the organization and patent is also given to this and coming to the step three uh or part three like uh explaining I would like to explain the back propagation neural network to a 30 year or 12 year old kid and coming to the neural networks neural network is a method that is inspired by a network of cells in the human bra it\'s a it\'s a definition uh I\'ll explain what back back propagation is for example if you\'re riding a bicycle uh you your intention is to ride the bicycle with a particular constant speed of 10 m per second 10 mil per hour so what happens is you give the throttle you apply throttle onto the bicycle padn and the bicycle starts moving so the moment you get to know that you you don\'t have you will not have any kind of sensors the only sensors is the touch sensor and the the the field you\'re going with the bicycle and the air that is attacking you so the moment you get to know that uh you\'re going faster you stop applying the you start reducing the throttle pedal position so you some kind your propagating the information that you\'re getting from the uh bicycle speed and you\'re making a correction out of this and this method the same methodology is being used in the artificial neural networks to tune the algorithm so that for a right set of combinations you\'ll get the right set of outputs\n\nCandidate\'s Number of Pauses:\n2\n\nCandidate\'s Length of Video:\n7.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 02:09:57 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'1227'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296535'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'693ms'), (b'x-request-id', b'e225dae6a4488b69296081684cfe0488'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=cWNakikx6jSsFQzYTE6TOymZEpSRMEd_QNioUlAS5UA-1707185397-1-Abgn96m76AF+vUm3S7WR0PTUE940wgvvU/2g0m2PfZ1GiC+QS7egCUQeKvJbvVnPK/ZtgMdMnPjaDWMIFYse33g=; path=/; expires=Tue, 06-Feb-24 02:39:57 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=1sLagIObs05vntgCjIErIePNs.k9YgkuDBgCBOPsfsA-1707185397985-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'850fda990dc03994-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" matplotlib.pyplot - DEBUG - Loaded backend MacOSX version unknown. asyncio - DEBUG - Using selector: KqueueSelector httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='api.gradio.app' port=443 local_address=None timeout=3 socket_options=None httpcore.connection - DEBUG - connect_tcp.started host='checkip.amazonaws.com' port=443 local_address=None timeout=3 socket_options=None asyncio - DEBUG - Using selector: KqueueSelector httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='127.0.0.1' port=7861 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'date', b'Tue, 06 Feb 2024 03:45:44 GMT'), (b'server', b'uvicorn'), (b'content-length', b'5'), (b'content-type', b'application/json')]) httpx - INFO - HTTP Request: GET http://127.0.0.1:7861/startup-events "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpx - DEBUG - load_ssl_context verify=False cert=None trust_env=True http2=False httpcore.connection - DEBUG - connect_tcp.started host='127.0.0.1' port=7861 local_address=None timeout=3 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'date', b'Tue, 06 Feb 2024 03:45:44 GMT'), (b'server', b'uvicorn'), (b'content-length', b'8752'), (b'content-type', b'text/html; charset=utf-8')]) httpx - INFO - HTTP Request: HEAD http://127.0.0.1:7861/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='checkip.amazonaws.com' port=443 local_address=None timeout=3 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='checkip.amazonaws.com' timeout=3 httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='checkip.amazonaws.com' timeout=3 httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.gradio.app' timeout=3 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 03:45:44 GMT'), (b'Server', b'Not Available'), (b'Content-Length', b'12'), (b'Connection', b'keep-alive')]) httpx - INFO - HTTP Request: GET https://checkip.amazonaws.com/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='api.gradio.app' port=443 local_address=None timeout=5 socket_options=None httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.gradio.app' timeout=5 httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 03:45:44 GMT'), (b'Server', b'Not Available'), (b'Content-Length', b'12'), (b'Connection', b'keep-alive')]) httpx - INFO - HTTP Request: GET https://checkip.amazonaws.com/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' httpcore.connection - DEBUG - connect_tcp.started host='api.gradio.app' port=443 local_address=None timeout=5 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.gradio.app' timeout=5 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 03:45:45 GMT'), (b'Content-Type', b'application/json'), (b'Content-Length', b'21'), (b'Connection', b'keep-alive'), (b'Server', b'nginx/1.18.0'), (b'Access-Control-Allow-Origin', b'*')]) httpx - INFO - HTTP Request: GET https://api.gradio.app/pkg-version "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 03:45:45 GMT'), (b'Content-Type', b'text/html; charset=utf-8'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'Server', b'nginx/1.18.0'), (b'Access-Control-Allow-Origin', b'*'), (b'Content-Encoding', b'gzip')]) httpx - INFO - HTTP Request: POST https://api.gradio.app/gradio-initiated-analytics/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 03:45:45 GMT'), (b'Content-Type', b'text/html; charset=utf-8'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'Server', b'nginx/1.18.0'), (b'Access-Control-Allow-Origin', b'*'), (b'Content-Encoding', b'gzip')]) httpx - INFO - HTTP Request: POST https://api.gradio.app/gradio-launched-telemetry/ "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "GET /v1/candidates/32de4bf3-6871-475a-a8e3-43cb1c5b276a HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=WxTXW6hzN8U HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=WxTXW6hzN8U&ei=xKvBZfSPF8iL2_gPxfWKwAg&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707216436&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=DDC54A8A0C0887B79B306948C59A860FB916A893.7C66D0EC317A50D99E92E05AC793C279B213717E&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID WxTXW6hzN8U. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhi my name is Aditya and this is my um recorded video explanation for the uh AI Camp uh summer data science machine learning intern position I\'m sorry about the delay in um submitting the video because I was not feeling well the past week or so so let\'s get down to the questions um so motivations and expectations so um the reason why I\'m interested in in this position is because I\'ve always been passionate about uh education and teaching and my understanding is that the position is partly developing tools for teaching and partly actually teaching um um students uh about AI so um so the the thing is I I believe that um education about AI in today\'s world is extremely important uh just like educating people about the internet was important in my generation but I think with AI it\'s all the more important because uh students and kids these days are going to grow up you know using a tool tools like chat GPT the way we people in my generation use the internet and using chat GPT means that um they they shouldn\'t grow up with the mindset that you know AI is all powerful or you know smarter than humans it may very well be one day for sure um but um they they shouldn\'t get you know uh lulled into a false sense of thinking that AI is um AI is basically an artificial version of a human and while that is the idea behind AI um any neural network I mean yes it is modeled or it started out as something to replicate the brain but a neural network is actually not an artificial brain the same way when a tool like chat gbt is uh like a human it does not think before it does not construct the idea of a sentence before it says the whole sentence it actually just sort of um in generative AI it basically predicts the next word based on the previous words and some data that it has has in its um uh Based on data that it has been trained on so it\'s only predicting the next word it\'s not determining what will come after that so I think M making sure that kids understand what AI actually is and how it works is important and that\'s one of the main reasons why I\'m interested in this role and um for part two about the um uh about creating a product that aligns with what people actually want um this this experience is not actually on my resume it\'s something I did in high school um with uh with a team we created uh uh we started a new club um for providing career guidance and college uh advice about applying to colleges because my school had no such thing I studied in a Regional School in India and uh as I started researching about colleges in the US uh I realized that this this kind of tool would be pretty useful so um basically we made sure that we were actually giving students what they wanted so we uh you know sent out Google forms um when when we first started the club making sure that this was something that students would actually uh want and would participate in willingly um that if we organized meetings with alumni or other people to advise them that they would participate uh that was important so um and before each meeting we would gather questions from the students and make sure that the that was what was addressed during the meeting and uh you know if um uh and we would you know contact alumni or people from specific Fields based on what the students wanted and we sent out forms for all of this to make sure that um this wasn\'t something that was just being run by the school or the administration for um just because they felt like they needed to do it but it was something that actually benefited students and it was something that actually students wanted um yeah and that there have been other experi experiences where this has happened like uh uh even at my internship at the Indian Institute of Technology um we had to build a device that could help the elderly and we we thought a lot about it and we created a sound based tracking device for that and uh um there was a lot about what the user wanted and what uh what people were looking for in that project as well um I don\'t want to expand more on that because I don\'t want to exceed the the time limit but I\'ll move on to part three um so I\'m just I\'m going to be explaining back propagation neural network to um to a 13-year-old I mean I would do this differently if it was my grandmother but uh for a 13-year-old so uh suppose um you know there\'s a robot you build a robot and you want it to um you know uh suppose there\'s like a buck buet or a bin and they you wanted to put something in the in the bin or the bucket um and the first few times you know it doesn\'t exactly put it in the bucket it puts it somewhere else and then you give it instructions on how to um you know change or improve get closer to what you want it to do so a neural network is essentially something in simple terms it\'s something you\'re you\'re using it\'s a tool that you can use to predict make predictions and so when first starts out the neural network is not going to be good it will not make uh good predictions so back propagation is essentially something that you know tells the neural network what you know uh based on what mistakes it\'s making how to correct itself so it\'s kind of like you know guiding the robot to correct itself so it gets better and better at the task that you want it to do so the more and more you train the robot the better and better it gets similarly the more and more you train the neural network the better it\'ll get at making a prediction and back propagation is what helps it uh you know uh understand it its mistakes and get closer to what you really want um and I think that\'s about it uh thank you so much and I hope to hear back from you guys soon\n\nCandidate\'s Number of Pauses:\n0\n\nCandidate\'s Length of Video:\n7.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 03:47:18 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'782'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296634'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'673ms'), (b'x-request-id', b'0c7121cf06c397f7898ec7be06a473c8'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=YVyxzWMhLx6A_u4lMqPBXxS3_BBpokRuc_TOeOo7_dQ-1707191238-1-AdjlIoGG/3mG+3ZBowckprzRL+IxXz+fdUq+20gpCyPfWKmTjzQKCBfXvZ1WX1Vb0AFKM1G9pIQQSzp/I3cFFEo=; path=/; expires=Tue, 06-Feb-24 04:17:18 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=3qb42ZYvddkwDFp8vHWg_ZzTy8gv0Y6KYhVMDLuM_Kk-1707191238683-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'8510693438fc3b86-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "POST /v1/candidates/32de4bf3-6871-475a-a8e3-43cb1c5b276a/notes HTTP/1.1" 403 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "GET /v1/candidates/32de4bf3-6871-475a-a8e3-43cb1c5b276a HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=WxTXW6hzN8U HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=WxTXW6hzN8U&ei=DazBZaitEYuw2_gPg4GZiAY&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707216509&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=675F1F91FC73B7D048488EE648449B969AF2D280.C3863DB53343D7001E0C1C2E7F1D602F0C28DF78&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID WxTXW6hzN8U. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhi my name is Aditya and this is my um recorded video explanation for the uh AI Camp uh summer data science machine learning intern position I\'m sorry about the delay in um submitting the video because I was not feeling well the past week or so so let\'s get down to the questions um so motivations and expectations so um the reason why I\'m interested in in this position is because I\'ve always been passionate about uh education and teaching and my understanding is that the position is partly developing tools for teaching and partly actually teaching um um students uh about AI so um so the the thing is I I believe that um education about AI in today\'s world is extremely important uh just like educating people about the internet was important in my generation but I think with AI it\'s all the more important because uh students and kids these days are going to grow up you know using a tool tools like chat GPT the way we people in my generation use the internet and using chat GPT means that um they they shouldn\'t grow up with the mindset that you know AI is all powerful or you know smarter than humans it may very well be one day for sure um but um they they shouldn\'t get you know uh lulled into a false sense of thinking that AI is um AI is basically an artificial version of a human and while that is the idea behind AI um any neural network I mean yes it is modeled or it started out as something to replicate the brain but a neural network is actually not an artificial brain the same way when a tool like chat gbt is uh like a human it does not think before it does not construct the idea of a sentence before it says the whole sentence it actually just sort of um in generative AI it basically predicts the next word based on the previous words and some data that it has has in its um uh Based on data that it has been trained on so it\'s only predicting the next word it\'s not determining what will come after that so I think M making sure that kids understand what AI actually is and how it works is important and that\'s one of the main reasons why I\'m interested in this role and um for part two about the um uh about creating a product that aligns with what people actually want um this this experience is not actually on my resume it\'s something I did in high school um with uh with a team we created uh uh we started a new club um for providing career guidance and college uh advice about applying to colleges because my school had no such thing I studied in a Regional School in India and uh as I started researching about colleges in the US uh I realized that this this kind of tool would be pretty useful so um basically we made sure that we were actually giving students what they wanted so we uh you know sent out Google forms um when when we first started the club making sure that this was something that students would actually uh want and would participate in willingly um that if we organized meetings with alumni or other people to advise them that they would participate uh that was important so um and before each meeting we would gather questions from the students and make sure that the that was what was addressed during the meeting and uh you know if um uh and we would you know contact alumni or people from specific Fields based on what the students wanted and we sent out forms for all of this to make sure that um this wasn\'t something that was just being run by the school or the administration for um just because they felt like they needed to do it but it was something that actually benefited students and it was something that actually students wanted um yeah and that there have been other experi experiences where this has happened like uh uh even at my internship at the Indian Institute of Technology um we had to build a device that could help the elderly and we we thought a lot about it and we created a sound based tracking device for that and uh um there was a lot about what the user wanted and what uh what people were looking for in that project as well um I don\'t want to expand more on that because I don\'t want to exceed the the time limit but I\'ll move on to part three um so I\'m just I\'m going to be explaining back propagation neural network to um to a 13-year-old I mean I would do this differently if it was my grandmother but uh for a 13-year-old so uh suppose um you know there\'s a robot you build a robot and you want it to um you know uh suppose there\'s like a buck buet or a bin and they you wanted to put something in the in the bin or the bucket um and the first few times you know it doesn\'t exactly put it in the bucket it puts it somewhere else and then you give it instructions on how to um you know change or improve get closer to what you want it to do so a neural network is essentially something in simple terms it\'s something you\'re you\'re using it\'s a tool that you can use to predict make predictions and so when first starts out the neural network is not going to be good it will not make uh good predictions so back propagation is essentially something that you know tells the neural network what you know uh based on what mistakes it\'s making how to correct itself so it\'s kind of like you know guiding the robot to correct itself so it gets better and better at the task that you want it to do so the more and more you train the robot the better and better it gets similarly the more and more you train the neural network the better it\'ll get at making a prediction and back propagation is what helps it uh you know uh understand it its mistakes and get closer to what you really want um and I think that\'s about it uh thank you so much and I hope to hear back from you guys soon\n\nCandidate\'s Number of Pauses:\n0\n\nCandidate\'s Length of Video:\n7.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 03:48:31 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'901'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296634'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'673ms'), (b'x-request-id', b'f61eeb1ca26b2e4f583cc5b13af707cd'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=Ea5rd_ouhK7bMKtmTKyYqd5TGPtbsaoyP07R_K.SomM-1707191311-1-AQ9q6eznIPphJ6qFhirts1aaNjw9X1gL862OCBwz34eEah7CAygPUMzEdmbtvXvkH9qF2GdjT4Prpyo2chO2S08=; path=/; expires=Tue, 06-Feb-24 04:18:31 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=jHs2ldAL8_qTBnVC0iZjFioyCI3v4jextyfxUyM4iMY-1707191311487-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'85106afa7df5825d-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "POST /v1/candidates/32de4bf3-6871-475a-a8e3-43cb1c5b276a/notes HTTP/1.1" 403 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "GET /v1/opportunities/6cf47cfb-36df-486a-ae56-02f75a20b3bb HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=48L5LeQ06ww HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=48L5LeQ06ww&ei=X6_BZeaYDbCylu8P1pqVkAU&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707217359&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=2AFD7D6FC56AE759DFDFF37CE3C1A848C988F540.1A82D4E59508A8615DE0D5C47085DF93D3329B3A&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID 48L5LeQ06ww. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhi my name is Willi and also go by lar I\'m a four data science and applyed math student at UC San Diego and I\'ll be pursuing a graduate degree in computer science starting at fall 2024 in this video I\'m going to apply for this AI cam data science machine learning intern for the summer of 2024 so why I\'m interesting is this position I have a deep passion for leveraging my skills in data science and machine learning to build AI power tools such as the AI teaching assistant like the job description described and also highly motivated to DW meaningful educational outcome um and also have a strong alignment with a focus on education Technologies proven by my past experiencing academic research and my P experience in undergraduate te assistant and I also have a lot of r p experience align with the job requirements so what values I can provide to this program well first with a strong Foundation need a science machine learning and web development I can bring a blend of technical expertise and educational experiences so I have work in various research lab and develop models for data analysis and engage processing I develop applications for larger language models and also find tune a lot of foundation models and also have a lot of R teaching experience such as a Time teaching system at use San Diego in computer science mathematics and data science mathematic and economic courses and also have a 100% student instructor recommendation rate which proven ability in effective teaching and mentoring students and also develop various Educational Tools such as interactive course websites for a lot of commuter science data classes and also a lot of automated grading script and some grade report script and also have tons of leadership and manip experiences I\'ve Le various research projects in a lot of classes and research groups and also mentored a lot of under class working on research project and guided them to Bridge a knowledge Gap so then I help them to fulfill all the prerequisite that they need to do research in a real setting and what I hope to achieve is to develop my skills in artificial intelligence and machine learning while making an impact in the educational technology field I would like to gain insights of challenges and opportunities in the tech education field and continue Innovative AI power teaching tools and ASP by and empower the Next Generation Tech is is doent mentoring as an extension of my teaching assistant experiences so in this U slides I would like to use my published Bela paper as an example of aligning with audience needs so basically we identify that the challenge of students struggling with text embedded in images while studying and we also recognize the limitation of chpd at that time which did not support visual input and our solution is is why don\'t we just build our own model so we built a model called bifa which is a simple multimodal LM for better handling text resal questions and accepted by triple ai24 so basically we focus on making believer adoped at reading and interpreting text embedding within images which directly address a significant need in educational sector where students often encounter the complex diagrams graph and text in visual uh various visual formats so that just as example of proven my ability uh to sense the audience need so then we can address we can uh develop project to address stakeholders um need and in this slide I would like to use b pration as the topic I choose to explain to my grandma so here\'s my version of it I\'m going to say hey Grandma imagine you\'re teaching our cat emo a new tricks Str that shaking hand with me each time it does something right you give it a trick each time if the cat makes a mistake you is guiding on how to do it better next time so in a computer brain which is called Neer Network back application is like teaching the computer to learn from its mistakes when a computer tries to solve a problem and gets it wrong back loation helps you understand where it went wrun and how to improve it it just like computer is practicing and learning just like a cat emo to get better at answering question and solving problems um in a lot of training process and in the end of the video I would like to show the result of me training my cat using similar um using similar format yeah and that\'s basically it I\'ll look forward to talk more about this opportunity in the future interview round and thank you for watching this video\n\nCandidate\'s Number of Pauses:\n1\n\nCandidate\'s Length of Video:\n5.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 04:02:41 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'834'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296935'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'613ms'), (b'x-request-id', b'54ddd47942c5d244ee8a347b3f8b1c69'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=vKPtCqrZLrFACx.qwyBCZJz2y2FuummfRNO6qXPFTY8-1707192161-1-ATpA/AM67RP9q0eHbRrpa23U8t5I+FqsORQip8AUU6u9XsokcDaAwfHylS05bdGTI89xC0ne2b1hasnaXfdrDTg=; path=/; expires=Tue, 06-Feb-24 04:32:41 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=8ycTvD.rm81zHXDnNpGd9euOA3QUFfSG4hDwm.X53.w-1707192161377-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'85107fbaee3c6fd9-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "POST /v1/opportunities/6cf47cfb-36df-486a-ae56-02f75a20b3bb/notes HTTP/1.1" 400 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "GET /v1/opportunities/6cf47cfb-36df-486a-ae56-02f75a20b3bb HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=48L5LeQ06ww HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=48L5LeQ06ww&ei=va_BZdeXELvBlu8P-fi7sAk&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707217453&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=E39B3948E2EE082AE5E6C8FFADC5D3EE971884DB.33B0D4C5F0D495CD86674B2B391A22E96EB69AEB&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID 48L5LeQ06ww. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhi my name is Willi and also go by lar I\'m a four data science and applyed math student at UC San Diego and I\'ll be pursuing a graduate degree in computer science starting at fall 2024 in this video I\'m going to apply for this AI cam data science machine learning intern for the summer of 2024 so why I\'m interesting is this position I have a deep passion for leveraging my skills in data science and machine learning to build AI power tools such as the AI teaching assistant like the job description described and also highly motivated to DW meaningful educational outcome um and also have a strong alignment with a focus on education Technologies proven by my past experiencing academic research and my P experience in undergraduate te assistant and I also have a lot of r p experience align with the job requirements so what values I can provide to this program well first with a strong Foundation need a science machine learning and web development I can bring a blend of technical expertise and educational experiences so I have work in various research lab and develop models for data analysis and engage processing I develop applications for larger language models and also find tune a lot of foundation models and also have a lot of R teaching experience such as a Time teaching system at use San Diego in computer science mathematics and data science mathematic and economic courses and also have a 100% student instructor recommendation rate which proven ability in effective teaching and mentoring students and also develop various Educational Tools such as interactive course websites for a lot of commuter science data classes and also a lot of automated grading script and some grade report script and also have tons of leadership and manip experiences I\'ve Le various research projects in a lot of classes and research groups and also mentored a lot of under class working on research project and guided them to Bridge a knowledge Gap so then I help them to fulfill all the prerequisite that they need to do research in a real setting and what I hope to achieve is to develop my skills in artificial intelligence and machine learning while making an impact in the educational technology field I would like to gain insights of challenges and opportunities in the tech education field and continue Innovative AI power teaching tools and ASP by and empower the Next Generation Tech is is doent mentoring as an extension of my teaching assistant experiences so in this U slides I would like to use my published Bela paper as an example of aligning with audience needs so basically we identify that the challenge of students struggling with text embedded in images while studying and we also recognize the limitation of chpd at that time which did not support visual input and our solution is is why don\'t we just build our own model so we built a model called bifa which is a simple multimodal LM for better handling text resal questions and accepted by triple ai24 so basically we focus on making believer adoped at reading and interpreting text embedding within images which directly address a significant need in educational sector where students often encounter the complex diagrams graph and text in visual uh various visual formats so that just as example of proven my ability uh to sense the audience need so then we can address we can uh develop project to address stakeholders um need and in this slide I would like to use b pration as the topic I choose to explain to my grandma so here\'s my version of it I\'m going to say hey Grandma imagine you\'re teaching our cat emo a new tricks Str that shaking hand with me each time it does something right you give it a trick each time if the cat makes a mistake you is guiding on how to do it better next time so in a computer brain which is called Neer Network back application is like teaching the computer to learn from its mistakes when a computer tries to solve a problem and gets it wrong back loation helps you understand where it went wrun and how to improve it it just like computer is practicing and learning just like a cat emo to get better at answering question and solving problems um in a lot of training process and in the end of the video I would like to show the result of me training my cat using similar um using similar format yeah and that\'s basically it I\'ll look forward to talk more about this opportunity in the future interview round and thank you for watching this video\n\nCandidate\'s Number of Pauses:\n1\n\nCandidate\'s Length of Video:\n5.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 04:04:15 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'744'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296935'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'613ms'), (b'x-request-id', b'14cb6685e92351251bc410c851151842'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=TuRuJy7RevAIsMpR7rKLZIu3TxajjZK8SG7O5TFisro-1707192255-1-AWp05RgS0bfyEdqBm2xfleH/FXmvLuapfjZIkCMTYDMHB5WtYV0oP4ajGsblZ67QqYbMVotZMVOoEO3ml3HBnok=; path=/; expires=Tue, 06-Feb-24 04:34:15 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=HTwrl2OBMtqRmGIHuG.H8F_sUTWOuGUZbSkz0edYNOY-1707192255218-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'85108205ebcb81e5-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "POST /v1/opportunities/6cf47cfb-36df-486a-ae56-02f75a20b3bb/notes HTTP/1.1" 201 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "GET /v1/opportunities/ae7154ba-9b7c-4e4b-bdbd-6ec8ee5a133f HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=1tS8aAm-tng HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=1tS8aAm-tng&ei=u7DBZeHEC8y9ir4PgJWZ4AI&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707217707&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=AE1FD9875163CB4FDDD5E1DB280F545B619FD783.9DF7016BAE0BCBBDD49BD7AFB413004E679828AF&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID 1tS8aAm-tng. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhi this is Ling currently I am a master of data science students at Columbia my fascination with data science began with my love for puzzles and storytelling through data disos at AI cam caught my eye because it merges my academic interest with practical impactful work um the chance to dive into a machine learning projects especially in educational and feels like the perfect next step in my journey so that\'s the reason why interested in disos and um given my background where I have you know emerged with a lot of complex data analysis and machine learning projects I bring a strong analytical mindset and an act for simplifying complex com Concepts um my work like forecasting inventory demands using time series models has Haun my ability to not only analyze the data but to visualize it compelling ensuring insights are accessible and actionable so with my academic background and also with my you know professional experience I think I am a very good candidate that can feed this position um during this internship or during this position I am to blend my theoretical knowledge with real world applications contributing to projects that have tangible impact I\'m exciting about it learning curve and opportunity to collaborate like with like-minded peers and mentors helping to merge not just a better data scientist but a contributor to the aam\'s mission um for part two I\'m going to mention about like World alignment um reflecting on real world alignment during my internship at Academia I was part of a team taxed with improving supply chain efficiency recognizing the disconnect between our data models and on ground realities of in Inventory management I initiate a collaborative review with the supply chain Department by integrating their firsthand experiences and challenges into our models we tailored our solutions to better meet the actual needs enhancing both efficiency and stakeholders satisfaction so I think that is one real word alignment that I have done recently for part three I\'m going to choose the option one which is for um the back propagation so um imagine you\'re teaching your pad a new trick like fetching each time your pad attempts the trick you give feedback right if the trick is performed correctly you give a trit if not no trit your pad then tries different approaches based on your feedback improving with each attempt back propagation in your networks Works similarly it\'s like the networks way of learning this mistakes adjusting his approach each time to get better at taex is in learning so I think um this is end of my video thank you\n\nCandidate\'s Number of Pauses:\n0\n\nCandidate\'s Length of Video:\n3.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 04:08:29 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'1192'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'297405'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'519ms'), (b'x-request-id', b'aeeea92dbe09e91e71f03bed3a6f5945'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=uuLeeA4DD3jsTuietk20Phvflw1RDNm0mNiw7ksTrjE-1707192509-1-AZiQp5FVPf5CQf5VUNJJ6/H+x3jQeA0kImDv6DDhR4s4z/LRYlCsebqcla0v5WLC/Mmj3wEXSivTcvlhZYtMEq0=; path=/; expires=Tue, 06-Feb-24 04:38:29 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=dkUXTGmPOS7TfX5XC50ng.gJvlz9nAIaCSKwCijhjRc-1707192509760-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'85108839ff9756ec-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "POST /v1/opportunities/ae7154ba-9b7c-4e4b-bdbd-6ec8ee5a133f/notes HTTP/1.1" 201 None httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete werkzeug - INFO - WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on http://127.0.0.1:5000 werkzeug - INFO - Press CTRL+C to quit werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 werkzeug - INFO - WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on http://127.0.0.1:5000 werkzeug - INFO - Press CTRL+C to quit werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 werkzeug - INFO - WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on http://127.0.0.1:5000 werkzeug - INFO - Press CTRL+C to quit werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:04:59] "GET / HTTP/1.1" 404 - werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:04:59] "GET /favicon.ico HTTP/1.1" 404 - werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:05:12] "GET / HTTP/1.1" 404 - werkzeug - INFO - WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on http://127.0.0.1:5000 werkzeug - INFO - Press CTRL+C to quit werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 fsevents - DEBUG - NativeEvent(path="/Users/blake/LeverVideoAutomation/main.py", inode=118504279, flags=10800, id=11391382): is_file, is_renamed fsevents - DEBUG - NativeEvent(path="/Users/blake/LeverVideoAutomation/app.py", inode=118504279, flags=10800, id=11391383): is_file, is_renamed fsevents - DEBUG - Destination event for rename is NativeEvent(path="/Users/blake/LeverVideoAutomation/app.py", inode=118504279, flags=10800, id=11391383) fsevents - DEBUG - queue_event fsevents - DEBUG - queue_event fsevents - DEBUG - queue_event werkzeug - INFO - * Detected change in '/Users/blake/LeverVideoAutomation/main.py', reloading werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - INFO - WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on http://127.0.0.1:5000 werkzeug - INFO - Press CTRL+C to quit werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 werkzeug - INFO - WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on http://127.0.0.1:5000 werkzeug - INFO - Press CTRL+C to quit werkzeug - INFO - WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on http://127.0.0.1:5000 werkzeug - INFO - Press CTRL+C to quit werkzeug - INFO - WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on http://127.0.0.1:5002 werkzeug - INFO - Press CTRL+C to quit werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:14:03] "GET / HTTP/1.1" 404 - werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:14:03] "GET /favicon.ico HTTP/1.1" 404 - werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:14:15] "GET / HTTP/1.1" 404 - werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:15:50] "GET / HTTP/1.1" 404 - werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:15:56] "GET / HTTP/1.1" 404 - werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:18:28] "GET / HTTP/1.1" 404 - werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:18:57] "GET /webhook HTTP/1.1" 405 - werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:18:59] "GET /webhook HTTP/1.1" 405 - werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:19:06] "GET /webhook HTTP/1.1" 405 - werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:19:08] "GET /webhook HTTP/1.1" 405 - urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "GET /v1/opportunities/8d573b04-aea4-475a-a0ec-909ac925bd71 HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=eiOdKv0gyQM HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=eiOdKv0gyQM&ei=gcHBZerALfvkir4Ppf2ukAo&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707222001&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=58B885C52F34CCEA9BD72E2A45CF079F2281E8F7.717F80521BDB8313EC676027ACAF4403B4A50E26&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID eiOdKv0gyQM. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhi I\'m rja dongre currently a graduate student in data science at Vara poly Technic Institute I thank you for giving me this opportunity to express myself I\'ll be answering the questions sequentially starting with the motivations and the expectations being an international graduate student I can totally empathize with the burden of taking on substantial loans to complete one\'s education therefore when I came across AI camp and its mission to educate high school students and introduce UC them to the world of AI in the formative years I was highly impressed it also compelled me to think if I had been given such an opportunity to interact with like-minded people and learn from industry experts at such a young age my career trajectory would have been completely different I\'m a strong believer that knowledge shared is knowledge gained therefore with the Advent of AI and a plethora of online learning tools that are available I think there should be some changes in the teaching methodologies as well as well therefore if given a chance I would like to incorporate innovative ideas while developing the AI teaching tool for AI cam for example just like one shoe doesn\'t fit all one teaching method might not be suitable for all the student young minds have a very unique way of thinking in the developmental phase and thus they should have a very personalized way of learning which caters to their specific needs AI cam culminates my passion for teaching and my experience in machine learning and data science to develop an AI tool that aids the learning process all the while growing and learning from industry according to me teaching should be done in a way that not only imparts knowledge but also creates an impact being a part of a rotary club I was fortunate enough to get an opportunity to teach underprivileged children the experience was not only rewarding but also fulfilling when I could see that I shine with the happiness of getting to learn something new this made me pursue teaching further when I conducted various workshops on python during my tenure at LTI mry this helped my colleagues who had no coding experience to learn a new programming language and also take on projects in the similar door the projects I have worked on and the courses which I have taken like machine learning statistics and natural language processing have equipped me with the necessary skill set to be a part of this noble cause and I believe that this collaboration would be mutually beneficial to both AI Cam and to me I think that an internship is not only an opportunity to get to work on industry project and to interact with Brilliant Minds but also to broaden my horizons and gain New Perspectives I look forward to many brainstorming sessions discussing new ideas interacting and learning with young minds and most importantly being a part of the wonderful AI cam Community I strongly believe that education aims to solve real world problems keeping this in mind all of my projects aim to make people\'s lives easy or to create social impact one of my project dealt with the agriculture landscape of India in India 58% of the population depend on agriculture for their livelihood one such project was during my research based internship at Indian Institute of tropical meteorology wherein I implemented a methodology to predict rainfall at a higher resolution using lower resolution data using deep learning techniques like super resolution CNN the model was primarily used to make localized climate predictions that is to predict rainfall in regions where very sparse meteorological data is available such areas are mostly affected by climate change the model was used to make regional level projections in such areas and which help the farmers significantly to maximize their yield now I\'ll be explaining back propagation to a 13year old soan I\'ll assume that you are a 13year old so please bear with me and I assure you that by the end of this video you\'ll understand what back propagation is now imagine it is your summer vacation and your you\'re learning basketball for the first time you master all your courage stand in front of the hoop aim for it and shoot but you miss it now you do some crazy computations in your brain and come up with the idea that you should apply more Force now you try with more Force but the ball goes over the hook again you do some crazy computations in your brain and apply a bit less Force than the previous attempt and correct your posture a bit and then attempt to throw the ball again this time you make it now this entire scenario can be devised as a beautiful analogy with neural networks and back propagation I just threw two jgun at you but don\'t be intimidated by jgun Jons are just some words that PhD students use to sound smarter think of neural networks as a system which is trying to learn a task just like your brain does the input to the neural network would be the goal that is to shoot the ball into the hoop and the output would be success or failure now what happened when you missed the shot you took a step back analyzed what went wrong corrected your mistakes and tried the again now this is exactly what happens in neural networks when it fails to do a task it goes back sees what went wrong learns from its mistakes and corrects it and it does this iteratively till it achieves its goal and this my friend is back propagation so next time when someone asks you what is back propagation you don\'t run backwards but explain them what it is thank you\n\nCandidate\'s Number of Pauses:\n0\n\nCandidate\'s Length of Video:\n5.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 05:20:03 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'761'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296670'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'665ms'), (b'x-request-id', b'fa0b76db84c2518c26180420bba67463'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=cBgMDQttnugs2nF7Vk4krQ09_3QalsvgOgIZayjVunY-1707196803-1-AccDOUkdQ00sE4UQksBSoVxpoIeX7CHrRQlt/0kuTam7mzjsSPJvfc1b08EbQfUKeuQMnSi00pvARvGupLQQlLc=; path=/; expires=Tue, 06-Feb-24 05:50:03 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=FPCGR3s1fM3agXajHhuzhKPdD1wJ1R_pEcUsoKlNDio-1707196803826-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'8510f112ab8c8298-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "POST /v1/opportunities/8d573b04-aea4-475a-a0ec-909ac925bd71/notes HTTP/1.1" 201 None werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:20:05] "POST /webhook HTTP/1.1" 200 - urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "GET /v1/opportunities/4ddf796c-4e59-4db0-a6c9-c4d81ab5852f HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=iVNXX_PV4bc HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=iVNXX_PV4bc&ei=OcLBZdGPIfaEybgPyPGs-A0&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707222185&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=A6038B9A33D4DC5E89E07A14D5108271684FB509.0AC9C5551B30D3E746CA79B2E5491E8189AD1EA1&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID iVNXX_PV4bc. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhi everyone my name is Alex I\'m a third year undergraduate student at us Davis and I\'m mayoring in computer science and this is my video interview for a c so I hope you guys like it uh so we\'ll go with the first question why am I interested into this position so my answer to that is because I\'m really interested into working with the students and teenagers that would like to know a little bit more about Ai and machine learning in applications and its possible impacts in the future as we know uh AI is taking uh more important role by the time in basically in our everyday lives and in our world so I would like to spread as much knowledge as I can on how to use these really useful tools and how should be be uh cautious about it but in the same time what could be the best way to use it um yeah for the second question what values uh do I think I can provide so the first thing that I think I can provide is a lot of experience working handson on machine learning applications from my previous internship experiences I also I think I can provide a lot of experience on working with the students uh that require some patience and I\'ve been working I work as a tutor at my community College uh and I successfully toured them to succeed in their uh courses at my community college in their programming courses uh data structures Java programming uh specifically those kind of courses and in terms of mentorship I\'m currently working as a student outre outre ambassador at E Davis where I\'m mentoring students that would like to transfer to the University of California uh and providing tips and getting through getting them through this hard process and for the question what do I hope to achieve so one of the things that I would like to achieve hopefully is after the summer program after training those students I would like to see them succeed getting into the universities they want studying what they actually really want to study and hopefully see them in future research on hearing from then I think that would be uh the most rewarding part of this intership so I will go ahead with part two which is uh a time when I ensured that the work that me and my team are doing aligns with uh with what the people want so I think a good example for that would be for one of the projects that I work as a research intern at Stanford libraries uh the project itself uh was to well the idea the idea the initial idea was to make the stanf for archives more accessible to the people and give spread the knowledge about the police brutality in California against black people uh since even though we know California is one of the most liberal states uh there\'s very knowledge about the police brutality and statistics about this so that was a prate itself and we were kind of free to think in which way we would like to go through this so even though this is a nonprofit project stord is a nonprofit organization I try to put myself from the customer view from the people uh basically how would they actually would like to interact with this St for archives so what I thought would be the the best way was with a question answering but since instead of giving them all the information all at once I thought that the most interactive way with the people uh would be by this since in that way we would be giving information that the people actually want if they\'re interested in something they just need to ask the question answer Bo and the question answer Bo will make sure to give an accurate answer about that uh so well after after thata we start working on the project it took us around like 3 months I would say but it ended up successful it was presented to several universities and activists and people interested into into the history history at black Stanford uh they were really interested into knowing more about this application and well currently it it is available publicly you guys can use it it\'s uploaded on huging face so it\'s and it\'s also open source all the code that uh we wrote It\'s only there so uh for the third part I will go with the second choice which is explaining the K nearest neighbors to a 13-year-old student so from my so I believe at that age I was really interested into video games video consoles so I will use that for my for my explanation I think that could be a good idea um so the first thing the way I would start is like imagine uh imagine a map itself and You and Your Friends Are pled in that map and you\'re trying to choose which video of console you want to buy and you have three options you have Xbox PlayStation and Nintendo and it\'s F console uh games console sorry has its own exclusive games for example for PlayStation there\'s God of War for Xbox there\'s Forza for Nintendo Super Mario [Music] so you because you actually are in between you won the world of God of War but in the same time you really like forsa you cannot choose you\'re in the middle and all of your friends are pled in map so some of them they decided to go play to buy PlayStation because they really like God of War some of them they bought Xbox because they like their exclusive game but there are also some friends in the middle uh kind of in the middle probably more in one side than another but they are almost in the middle and so the term k stands for the number of friends that you would like to ask what bit what game conso did they buy right so you ask you decide to ask three friends the number K would be three so you as the first one he liked a little bit more God of War so he decided to buy PlayStation but but he also liked for up but he ended up buying PlayStation there the second one and the same he liked both games but he ended up buying PlayStation in the end and just the third one he bought uh he bought Xbox but he also liked a little bit God of War so he was a little between but he ended up buying Xbox so in this case the majority wins so you would end up by PlayStation because your nearest neighbors your the three friends that you asked two of them the majority decided to buy PlayStation so this algorithm you would have not buying uh Playstation so that\'s how K aors Works uh and I think this is the end of my video interview so thank you so much for giving the me the opportunity and I hope to hear from you soon thank you\n\nCandidate\'s Number of Pauses:\n3\n\nCandidate\'s Length of Video:\n8.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 05:23:07 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'642'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296480'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'703ms'), (b'x-request-id', b'd9577b3af37c2c0cb00c1664fc833666'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=ANBcyeo8Z5xgMVYyRwe_7bQgufhSwR4l2DAWewVwbuM-1707196987-1-AcKVaaJOE77LVKw6sCPEw5UYLm2JyTCxQP09c8lf2bsIZ8UEzBdbcRBnUhnMd1ImsE5rO/p+tuLaCF7GKk0GO4Q=; path=/; expires=Tue, 06-Feb-24 05:53:07 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=2GYRZKCmnNCSrwCspKH_4bss8mvp5ZXky4pdlBcrEEg-1707196987759-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'8510f5905f4507e4-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "POST /v1/opportunities/4ddf796c-4e59-4db0-a6c9-c4d81ab5852f/notes HTTP/1.1" 201 None werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:23:08] "POST /webhook HTTP/1.1" 200 - httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete fsevents - DEBUG - NativeEvent(path="/Users/blake/LeverVideoAutomation/helpers.py", inode=118503927, flags=11400, id=11495242): is_file, is_inode_meta_mod, is_modified fsevents - DEBUG - queue_event werkzeug - INFO - * Detected change in '/Users/blake/LeverVideoAutomation/helpers.py', reloading httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - INFO - WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on http://127.0.0.1:5002 werkzeug - INFO - Press CTRL+C to quit werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "GET /v1/opportunities/6d7de2ed-56be-4b49-b294-689ef939364d HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=sSO3qWrPb98 HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=sSO3qWrPb98&ei=asPBZeS6AumN2_gP3Pq-wAk&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707222490&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=5C846BA19AA3EE46F4ADDF05AA42705318C0694F.E3F86B12622C218BEA517AE2191E1CC914BAA32A&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID sSO3qWrPb98. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhi I\'m adii and this is my video submission for the internship so for the first question about why I\'m interested in this position uh I\'m interested in this position because I have a passion for AI and for teaching I\'ve been a part of various institutions over the last few years that have allowed me to work with kids and teach them different subjects for example I worked for Camp edmo as a maker instructor where I taught stem subjects like Science and Tech and different forms of engineering to kids I also worked as a sewing counselor at stevenh Kates where I taught kids how to use sewing machines from all ages like 4 to 12 I think that those experiences have allowed me to learn how important it is to teach kids complicated subjects because they can expand their knowledge and learn a lot of new skills that they would have never had before and so I have a genuine passion for teaching children especially when it comes to stem I\'m also a statistics major and so I have a lot of background with data science and AI I have worked with large language models in the past and last quarter I was taking a data science class involving different machine learning algorithms and I found it super interesting and it has really built my passion for AI so I would really love to teach younger students about AI as well uh for the second question of what value I think I can provide I think I have a variety of skills and experience that is relevant to this position as mentioned before I have worked in camps in the past and I have a lot of experience with that I also consider myself to be very perseverant which I think is a necessary skill for this position especially when working with machine learning algorithms and AI it can be difficult but I think that when you\'re working with kids it\'s important to push through and make sure that they don\'t have someone who\'s mentoring them who might get frustrated I think that my perseverance is very good for that kind of thing I also have a variety of coursework as I mentioned that is related to AI um but beyond that I have taken a lot of classes outside of my college I have taken courses through Google on generative Ai and large language models that I think have really expanded my understanding of these things and I think that my dedication to learning outside of the class room is something that would be very positive for this role because students always learn better when they have a teacher who is knowledgeable about the field and is interested in the field and I think that I fit that criteria for the question about what I hope to achieve I hope to build a good educational tool with AI for this project I understand that it is very hard for a lot of people to get educated in this day and age I would love to see us really answer these question questions about the true capabilities of AI using education as a goal um I think that we could really put together something interesting with that and I would absolutely love to be a part of that I also want to help kids really get that better understanding of AI and I think that education is something that a lot of children are familiar with and the problems that come with education they are very familiar with and they\'ll have really interesting insights onto what we can add so I would really love to help them learn uh beyond that I am currently planning to pursue a career in data science and machine learning and so I would really love to get into this internship so that I can kind of understand that field better and get a better idea of what we can do with these Technologies so for the question about the alignment with real world needs and preferences of our audience this year I am putting together a uh conference with my team at the mental health initiative um and for that conference we are very much looking at how we can help our community and meet our community\'s needs so a variety of different things are going into place for that um to best understand what our community needs and serve our community we are getting a large group of volunteers and different people from our community to give us ideas and feedback about what they\' like to see our conference is the largest student run conference in Northern California for mental health so we have a large amount of people who have come before and who are willing to give us ideas so we\'re carefully listening to all of these ideas and putting together our project uh we also have a large group of people from different backgrounds working for us and we like to use these ideas because obviously we\'re a very diverse campus so we like to get as many ideas as possible together so we can really put together a good project um and through this process of kind of working with different people from different backgrounds and talking to different people who are volunteering for us or within the community about what we would they would like to see from us we have been able to put together caucuses reflecting self-care and disability a lot of different interesting ideas are going together and these are all reflective of what the community wants and needs to see from us uh so in that way I think that we are kind of reflecting and building on what the community needs and finally for the question about K nearest neighbor explain this to a 13-year-old uh K nearest neighbor is a supervised learning mechanism it\'s used to determine the category that something fits into based on the surrounding values so to explain this with an example assume we have a large amount of Skittles um some are red and some are blue and we know that the red skittles have slightly more sugar than the blue Skittles so uh let\'s assume we are given a new Skittle and we don\'t know what color it is but we do know the sweetness or the sugar col content of that Skittle so how we\'re going to determine what color Skittle it is is based on the colors of the surrounding Skittles and based on the sugar content of those Skittles so first we\'re going to pick our K value which is the amount of neighbors we\'re going to use um for this example let\'s do three so we\'re going to pick the three Skittles with the closest sugar level to our Skittle because we know its sugar level which is 87 but we don\'t know its actual color so we pick three Skittles two are blue one is red and the blue Skittles have 85 and 86 g of sugar respectively the red Skittle has 1.1 g of sugar now based on basic math we know that the skittle that is we have that is unidentified has closer sugar level to the blue Skittles which are 085 and 86 and our Skittle is 87 compared to the red Skittle that was 1.1 gram of sugar so we know that because it is 0.01 away from the blue Skittles we know that that is probably more likely to be a blue Skittle based on our understanding of what separates these categories so that is essentially what kers neighbor does you take the values for different categories and you use it to determine what category a new item fits into in this case the skittle all right thank you\n\nCandidate\'s Number of Pauses:\n0\n\nCandidate\'s Length of Video:\n7.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 05:28:12 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'808'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296290'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'741ms'), (b'x-request-id', b'cb4a6d81016c5ee5f6c6afcac64a7e29'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=_Sx8cONZBn__qsvUbHeJdsKWDU0ICkX.R7Ku9Xel7Rw-1707197292-1-AemTsG0F7bJ/PNOJN9aZ27rzHCYb8+53vGiHkOwKvl68I8YMD4gBW7Ky6uP8xjUCe4cRtIbEOy612bu8ZyXK/tI=; path=/; expires=Tue, 06-Feb-24 05:58:12 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=LPLpqDyIOtmd74f9RsxIKX40qFjSfO_139_lpNJRbWo-1707197292577-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'8510fcff2e7307f0-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "POST /v1/opportunities/6d7de2ed-56be-4b49-b294-689ef939364d/notes HTTP/1.1" 201 None werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:28:14] "POST /webhook HTTP/1.1" 200 - urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "GET /v1/opportunities/3201de0a-e7e4-41f0-a616-cc3996c2b888 HTTP/1.1" 200 None root - ERROR - Invalid URL provided. urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "POST /v1/opportunities/3201de0a-e7e4-41f0-a616-cc3996c2b888/notes HTTP/1.1" 201 None werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:29:10] "POST /webhook HTTP/1.1" 200 - fsevents - DEBUG - NativeEvent(path="/Users/blake/LeverVideoAutomation/helpers.py", inode=118503927, flags=11400, id=11505945): is_file, is_inode_meta_mod, is_modified fsevents - DEBUG - queue_event werkzeug - INFO - * Detected change in '/Users/blake/LeverVideoAutomation/helpers.py', reloading httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 fsevents - DEBUG - NativeEvent(path="/Users/blake/LeverVideoAutomation/app.py", inode=118504279, flags=11400, id=11506258): is_file, is_inode_meta_mod, is_modified fsevents - DEBUG - queue_event werkzeug - INFO - * Detected change in '/Users/blake/LeverVideoAutomation/app.py', reloading werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 werkzeug - INFO - WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on http://127.0.0.1:5002 werkzeug - INFO - Press CTRL+C to quit werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "GET /v1/opportunities/3201de0a-e7e4-41f0-a616-cc3996c2b888 HTTP/1.1" 200 None root - ERROR - No video URL found for opportunityId 3201de0a-e7e4-41f0-a616-cc3996c2b888 werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:44:22] "POST /webhook HTTP/1.1" 404 - urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "GET /v1/opportunities/6cf47cfb-36df-486a-ae56-02f75a20b3bb HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /watch?v=48L5LeQ06ww HTTP/1.1" 200 None urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): www.youtube.com:443 urllib3.connectionpool - DEBUG - https://www.youtube.com:443 "GET /api/timedtext?v=48L5LeQ06ww&ei=lMfBZYqCFemP2_gPztG-6A0&caps=asr&opi=112496729&xoaf=5&hl=en&ip=0.0.0.0&ipbits=0&expire=1707223556&sparams=ip,ipbits,expire,v,ei,caps,opi,xoaf&signature=9C8FEBBD32C93A605B809D7D5AC688068EBF692A.966B46A9817367ACF2A80BE13F16CA6C6E9C22BE&key=yt8&kind=asr&lang=en HTTP/1.1" 200 None root - INFO - Transcript retrieved successfully for video ID 48L5LeQ06ww. httpx - DEBUG - load_ssl_context verify=True cert=None trust_env=True http2=False httpx - DEBUG - load_verify_locations cafile='/Users/blake/anaconda3/lib/python3.11/site-packages/certifi/cacert.pem' openai._base_client - DEBUG - Request options: {'method': 'post', 'url': '/chat/completions', 'files': None, 'json_data': {'messages': [{'role': 'system', 'content': 'You are a helpful assistant.'}, {'role': 'user', 'content': 'Candidate\'s Transcript:\nhi my name is Willi and also go by lar I\'m a four data science and applyed math student at UC San Diego and I\'ll be pursuing a graduate degree in computer science starting at fall 2024 in this video I\'m going to apply for this AI cam data science machine learning intern for the summer of 2024 so why I\'m interesting is this position I have a deep passion for leveraging my skills in data science and machine learning to build AI power tools such as the AI teaching assistant like the job description described and also highly motivated to DW meaningful educational outcome um and also have a strong alignment with a focus on education Technologies proven by my past experiencing academic research and my P experience in undergraduate te assistant and I also have a lot of r p experience align with the job requirements so what values I can provide to this program well first with a strong Foundation need a science machine learning and web development I can bring a blend of technical expertise and educational experiences so I have work in various research lab and develop models for data analysis and engage processing I develop applications for larger language models and also find tune a lot of foundation models and also have a lot of R teaching experience such as a Time teaching system at use San Diego in computer science mathematics and data science mathematic and economic courses and also have a 100% student instructor recommendation rate which proven ability in effective teaching and mentoring students and also develop various Educational Tools such as interactive course websites for a lot of commuter science data classes and also a lot of automated grading script and some grade report script and also have tons of leadership and manip experiences I\'ve Le various research projects in a lot of classes and research groups and also mentored a lot of under class working on research project and guided them to Bridge a knowledge Gap so then I help them to fulfill all the prerequisite that they need to do research in a real setting and what I hope to achieve is to develop my skills in artificial intelligence and machine learning while making an impact in the educational technology field I would like to gain insights of challenges and opportunities in the tech education field and continue Innovative AI power teaching tools and ASP by and empower the Next Generation Tech is is doent mentoring as an extension of my teaching assistant experiences so in this U slides I would like to use my published Bela paper as an example of aligning with audience needs so basically we identify that the challenge of students struggling with text embedded in images while studying and we also recognize the limitation of chpd at that time which did not support visual input and our solution is is why don\'t we just build our own model so we built a model called bifa which is a simple multimodal LM for better handling text resal questions and accepted by triple ai24 so basically we focus on making believer adoped at reading and interpreting text embedding within images which directly address a significant need in educational sector where students often encounter the complex diagrams graph and text in visual uh various visual formats so that just as example of proven my ability uh to sense the audience need so then we can address we can uh develop project to address stakeholders um need and in this slide I would like to use b pration as the topic I choose to explain to my grandma so here\'s my version of it I\'m going to say hey Grandma imagine you\'re teaching our cat emo a new tricks Str that shaking hand with me each time it does something right you give it a trick each time if the cat makes a mistake you is guiding on how to do it better next time so in a computer brain which is called Neer Network back application is like teaching the computer to learn from its mistakes when a computer tries to solve a problem and gets it wrong back loation helps you understand where it went wrun and how to improve it it just like computer is practicing and learning just like a cat emo to get better at answering question and solving problems um in a lot of training process and in the end of the video I would like to show the result of me training my cat using similar um using similar format yeah and that\'s basically it I\'ll look forward to talk more about this opportunity in the future interview round and thank you for watching this video\n\nCandidate\'s Number of Pauses:\n1\n\nCandidate\'s Length of Video:\n5.0 minutes\n\nIntroduction:\nYou are tasked with evaluating a candidate\'s interview transcript for a highly competitive position that demands not only technical expertise but also a strong alignment with our educational mission, leadership qualities, and a collaborative spirit. This evaluation requires a rigorous, critical analysis. Additionally, assess the presentation’s duration and pacing, as the ability to convey information effectively within a constrained timeframe and with minimal unnecessary pauses is crucial. We expect assessors to employ a stringent standard, focusing on identifying any shortcomings, gaps in knowledge, or areas for improvement. Our aim is to ensure only the highest caliber candidates progress, reflecting our no-tolerance policy for mediocrity. Your assessment should be blunt and uncompromising, providing clear justifications for each score based on the candidate\'s responses without inferring unstated intentions.\n\nCompany Mission:\nWe believe that education is the most valuable asset anyone can have, and we founded this camp to help students get ready for the real world.\n\nAt AI Camp, we want to open doors for our students by teaching them real-world skills that they wouldn\'t find in their traditional classrooms to prepare them for opportunities in the technology field.\n\nDetailed Rubric for Evaluation:\n\nAlignment to Mission and Desire to Join (Max 5 Points)\n(0-1 Points): Exhibits little or no understanding or alignment with the mission. Fails to mention an interest in teaching, or reasons for joining are unclear, purely self-interested, or unrelated to the educational goals of the organization.\n(2 Points): Shows a basic alignment with the mission with a mention of teaching but lacks depth, passion, or a clear understanding of how teaching aligns with the organization\'s goals. Interest in teaching may be mentioned but not elaborated upon.\n(3 Points): Indicates a general interest in teaching and some alignment with the mission. Mentions a desire to join with an understanding of the importance of education but falls short of demonstrating a strong personal commitment to teaching or the organization\'s specific educational goals.\n(4 Points): Demonstrates a strong alignment with the mission with a clear, articulated interest in teaching. Shows a desire to join that goes beyond the basics, with some explanation of how their teaching can contribute meaningfully to the organization\'s goals.\n(5 Points): Demonstrates an exceptional and passionate alignment with the mission, clearly and enthusiastically articulating a strong desire to teach and contribute meaningfully to the organization\'s goals. Shows a deep understanding of the importance of education and how their specific skills and interests in teaching can significantly advance the mission.\n\nDesire to Learn (Max 5 Points)\n(0-1 Points): Displays no interest in learning from the mentoring experience, treating it as just another job.\n(2-3 Points): Recognizes the value of learning but does not prioritize it as a key motivation.\n(4-5 Points): Strongly motivated by a desire to learn from experiences as a mentor, viewing it as a central driving factor.\n\nTechnical Explanation (KNN or Back Propagation) and Tone (Max 10 Points)\n(0-2 Points): Provides an unclear or incorrect technical explanation with a monotone or difficult-to-follow delivery.\n(3-6 Points): Offers a basic technical explanation with some engagement and occasional tone changes, showing an understanding of the subject.\n(7-8 Points): Gives a competent technical explanation, maintaining an engaging tone and showing enthusiasm for the topic.\n(9-10 Points): Excels with a clear, accurate, and engaging explanation, demonstrating exceptional enthusiasm and making the subject accessible and interesting to all listeners.\n\nConfidence (Max 4 Points)\n(0-1 Points): Demonstrates noticeable uncertainty, with significant hesitations or pauses.\n(2 Points): Shows a level of confidence with occasional hesitations.\n(3-4 Points): Exudes confidence throughout the presentation, without any noticeable hesitations.\n\nComprehensibility (Max 4 Points)\n(0-1 Points): Utilizes overly technical language or inaccuracies, hindering comprehension.\n(2 Points): Generally understandable to those with a technical background, despite the prevalence of jargon.\n(3-4 Points): Communicates effectively, using relatable analogies that make the material comprehensible to audiences of all ages.\n\nEffort (Max 5 Points)\n(0-1 Points): Demonstrates minimal effort, failing to meet basic expectations.\n(2-3 Points): Meets basic expectations with a simple presentation, showing little beyond the minimum.\n(4-5 Points): Surpasses expectations with a passionate and innovative presentation, incorporating novel elements that enrich the experience significantly.\n\nLeadership and Product Strategy (Max 6 Points)\n(0-2 Points): Shows little to no leadership or strategic vision, lacking clarity in product direction.\n(3-4 Points): Displays some leadership qualities and understanding of product strategy, but lacks a compelling vision.\n(5-6 Points): Demonstrates strong leadership and a clear, innovative strategy for product development, aligning with organizational goals.\n\nCollaboration and Understanding Customer Needs (Max 6 Points)\n(0-2 Points): Limited collaboration with teams and understanding of customer needs.\n(3-4 Points): Adequate collaboration skills and a basic grasp of customer needs.\n(5-6 Points): Excellent collaboration with cross-functional teams and a deep understanding of customer needs, driving product development effectively.\n\nPresentation Length (Max 3 Points)\n(0 Points): The presentation significantly exceeds the ideal duration or is significantly under the ideal duration, lasting longer than 7 minutes or less than 2 minutes, indicating potential inefficiency in communication.\n(1 Point): The presentation is slightly over the ideal duration, lasting between 5 to 7 minutes, suggesting minor pacing issues.\n(2 Points): The presentation is within the ideal duration of 4 to 5 minutes, reflecting effective communication and time management skills.\n(3 Points): The presentation is not only within the ideal duration but also efficiently utilizes the time to convey the message concisely and effectively.\n\nPauses and Pacing (Max 2 Points)\n(0 Points): The presentation contains excessive unnecessary pauses, disrupting the flow and indicating potential nervousness or lack of preparation.\n(1 Point): The presentation has a moderate number of pauses, but they occasionally disrupt the flow of information.\n(2 Points): The presentation has minimal pauses, contributing to a smooth flow of information and demonstrating confidence and preparation.\n\nConclusion:\nSum the scores for a total out of 50. Please be precise with your total. Based on the total score:\n\n0-39 Points: Does not qualify for an interview.\n40-50 Points: Qualifies for an interview, demonstrating strong potential.\n\nModified Concluding Instructions for You (the AI):\n\nEvaluate the candidate\'s performance based on the total score and the assessment of their strengths and weaknesses in time management, presentation efficiency, and communication effectiveness. You should then decide the candidate\'s suitability for further interviews. Your decision should be:\n\n"Yes" if the candidate meets or exceeds the required criteria for an interview.\n"No" if the candidate does not meet the necessary criteria for an interview.\n\nYour output must be strictly one of these two options (Yes or No), ensuring a clear and direct conclusion based on the evaluation criteria provided.'}], 'model': 'gpt-4'}} httpcore.connection - DEBUG - connect_tcp.started host='api.openai.com' port=443 local_address=None timeout=5.0 socket_options=None httpcore.connection - DEBUG - connect_tcp.complete return_value= httpcore.connection - DEBUG - start_tls.started ssl_context= server_hostname='api.openai.com' timeout=5.0 httpcore.connection - DEBUG - start_tls.complete return_value= httpcore.http11 - DEBUG - send_request_headers.started request= httpcore.http11 - DEBUG - send_request_headers.complete httpcore.http11 - DEBUG - send_request_body.started request= httpcore.http11 - DEBUG - send_request_body.complete httpcore.http11 - DEBUG - receive_response_headers.started request= httpcore.http11 - DEBUG - receive_response_headers.complete return_value=(b'HTTP/1.1', 200, b'OK', [(b'Date', b'Tue, 06 Feb 2024 05:45:59 GMT'), (b'Content-Type', b'application/json'), (b'Transfer-Encoding', b'chunked'), (b'Connection', b'keep-alive'), (b'access-control-allow-origin', b'*'), (b'Cache-Control', b'no-cache, must-revalidate'), (b'openai-model', b'gpt-4-0613'), (b'openai-organization', b'ai-camp-7'), (b'openai-processing-ms', b'1449'), (b'openai-version', b'2020-10-01'), (b'strict-transport-security', b'max-age=15724800; includeSubDomains'), (b'x-ratelimit-limit-requests', b'10000'), (b'x-ratelimit-limit-tokens', b'300000'), (b'x-ratelimit-remaining-requests', b'9999'), (b'x-ratelimit-remaining-tokens', b'296935'), (b'x-ratelimit-reset-requests', b'6ms'), (b'x-ratelimit-reset-tokens', b'613ms'), (b'x-request-id', b'6b332f5f9a82fd0c4f3abfb0b1cd0886'), (b'CF-Cache-Status', b'DYNAMIC'), (b'Set-Cookie', b'__cf_bm=DfJsStTwN0ISSn3MMbxqi76P63lEEKuOUTcpyDDquPM-1707198359-1-Aad34d1EZLPu3Jg8UgFH3U3I+h2U246AwXwccOP53daJiVGxG3Bu6zdD5EQOa/y9A6YyXCcEZPL8Hbo0GjBLye0=; path=/; expires=Tue, 06-Feb-24 06:15:59 GMT; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Set-Cookie', b'_cfuvid=X573PiYE_gW87v4uhEQ8NucsM9W1F9FGKMJushxmehs-1707198359169-0-604800000; path=/; domain=.api.openai.com; HttpOnly; Secure; SameSite=None'), (b'Server', b'cloudflare'), (b'CF-RAY', b'8511170748cd6ffe-IAD'), (b'Content-Encoding', b'br'), (b'alt-svc', b'h3=":443"; ma=86400')]) httpx - INFO - HTTP Request: POST https://api.openai.com/v1/chat/completions "HTTP/1.1 200 OK" httpcore.http11 - DEBUG - receive_response_body.started request= httpcore.http11 - DEBUG - receive_response_body.complete httpcore.http11 - DEBUG - response_closed.started httpcore.http11 - DEBUG - response_closed.complete openai._base_client - DEBUG - HTTP Request: POST https://api.openai.com/v1/chat/completions "200 OK" root - INFO - Sending analysis result to Lever for candidate ID 6cf47cfb-36df-486a-ae56-02f75a20b3bb urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "POST /v1/opportunities/6cf47cfb-36df-486a-ae56-02f75a20b3bb/notes HTTP/1.1" 201 None root - INFO - Successfully sent analysis result to Lever for candidate ID 6cf47cfb-36df-486a-ae56-02f75a20b3bb werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:46:00] "POST /webhook HTTP/1.1" 200 - fsevents - DEBUG - NativeEvent(path="/Users/blake/LeverVideoAutomation/app.py", inode=118504279, flags=11400, id=11571624): is_file, is_inode_meta_mod, is_modified fsevents - DEBUG - queue_event werkzeug - INFO - * Detected change in '/Users/blake/LeverVideoAutomation/app.py', reloading httpcore.connection - DEBUG - close.started httpcore.connection - DEBUG - close.complete werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 fsevents - DEBUG - NativeEvent(path="/Users/blake/LeverVideoAutomation/app.py", inode=118504279, flags=11400, id=11572292): is_file, is_inode_meta_mod, is_modified fsevents - DEBUG - queue_event werkzeug - INFO - * Detected change in '/Users/blake/LeverVideoAutomation/app.py', reloading werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 fsevents - DEBUG - NativeEvent(path="/Users/blake/LeverVideoAutomation/helpers.py", inode=118503927, flags=11400, id=11572333): is_file, is_inode_meta_mod, is_modified fsevents - DEBUG - queue_event werkzeug - INFO - * Detected change in '/Users/blake/LeverVideoAutomation/helpers.py', reloading werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 werkzeug - INFO - WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on http://127.0.0.1:5002 werkzeug - INFO - Press CTRL+C to quit werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "GET /v1/opportunities/3201de0a-e7e4-41f0-a616-cc3996c2b888 HTTP/1.1" 200 None root - ERROR - Unable to process video URL for opportunityId 3201de0a-e7e4-41f0-a616-cc3996c2b888 werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:51:05] "POST /webhook HTTP/1.1" 200 - fsevents - DEBUG - NativeEvent(path="/Users/blake/LeverVideoAutomation/app.py", inode=118504279, flags=11400, id=11581211): is_file, is_inode_meta_mod, is_modified fsevents - DEBUG - queue_event werkzeug - INFO - * Detected change in '/Users/blake/LeverVideoAutomation/app.py', reloading werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 werkzeug - INFO - WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead. * Running on http://127.0.0.1:5002 werkzeug - INFO - Press CTRL+C to quit werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 urllib3.connectionpool - DEBUG - Starting new HTTPS connection (1): api.lever.co:443 urllib3.connectionpool - DEBUG - https://api.lever.co:443 "GET /v1/opportunities/3201de0a-e7e4-41f0-a616-cc3996c2b888 HTTP/1.1" 200 None root - ERROR - Unable to process video URL for opportunityId 3201de0a-e7e4-41f0-a616-cc3996c2b888 werkzeug - INFO - 127.0.0.1 - - [05/Feb/2024 23:52:17] "POST /webhook HTTP/1.1" 200 - fsevents - DEBUG - NativeEvent(path="/Users/blake/LeverVideoAutomation/app.py", inode=118504279, flags=11400, id=11583166): is_file, is_inode_meta_mod, is_modified fsevents - DEBUG - queue_event werkzeug - INFO - * Detected change in '/Users/blake/LeverVideoAutomation/app.py', reloading werkzeug - INFO - * Restarting with watchdog (fsevents) werkzeug - WARNING - * Debugger is active! werkzeug - INFO - * Debugger PIN: 103-046-891 fsevents - DEBUG - NativeEvent(path="/Users/blake/LeverVideoAutomation/.DS_Store", inode=118520969, flags=11400, id=11650647): is_file, is_inode_meta_mod, is_modified fsevents - DEBUG - queue_event