| import streamlit as st | |
| st.title("Generative AI Resources") | |
| st.header("Generative AI & LLMs") | |
| st.write("The collection of resources to learn about GenAI.") | |
| st.subheader("Introduction to GenAI") | |
| st.markdown(""" | |
| 1. Generative AI learning path by Google: [link](https://www.cloudskillsboost.google/journeys/118) | |
| """) | |
| st.subheader("Learn about LLMs") | |
| st.markdown(""" | |
| Keywords: [LLMs, Fine-Tuning, Text Embeddings, Transformers, Attention, Self-Attenion, Multi-head Attention, Foundation Models, Pre-Training, RLHF, Deep Neural | |
| Networks, Task-Specific Models] | |
| 1. LLM Bootcamp [link](https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/") | |
| 2. Cohere: LLM University [link](https://docs.cohere.com/docs/llmu") | |
| 3. Coursera/Generative AI with LLMS [link](https://www.coursera.org/learn/generative-ai-with-llms/) | |
| 4. OpenAI Cookbook [link](https://platform.openai.com/docs/introduction) | |
| 5. LLM Interfaces [link](https://scifilogic.com/interface-for-running-local-llm/) | |
| 6. Stanford AI Index Report [link](https://aiindex.stanford.edu/report/) | |
| """) | |
| st.subheader("Prompt Engineering") | |
| st.write(""" | |
| Keywords: [Prompting, Prompt Engineering, Prompt Design, Prompt Injection/Jailbreaking, Prompt Tuning, Prompt Drifting, Prompt Patterns, | |
| System Prompt, Prompt Template, Zero-Shot/One-Shot/Few-Shot, Chain-of-Thought Prompting, RAG (Retrieval Augmented Generation), APE (Automatic Prompt | |
| Engineer), Tree of Thoughts (ToT), Adversarial Prompting, Waterfall prompting] | |
| """) | |
| st.markdown(""" | |
| 1. Coursera/Prompt Engineering for ChatGPT [link](https://www.coursera.org/learn/prompt-engineering) | |
| 2. Cohere/Constructing Prompts for the Command Model [link](https://txt.cohere.com/constructing-prompts/) | |
| 3. Cohere/Command Model Use Case Patterns [link](https://txt.cohere.com/command-usecase-patterns/) | |
| 4. DeepLearning/ChatGPT Prompt Engineering for Developers [link](https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/) | |
| 5. Cohere/Prompt Engineering [link](https://docs.cohere.com/docs/model-prompting) | |
| 6. Learn Prompting [link](https://learnprompting.org/) | |
| 7. Prompt Engineering Guide [link](https://www.promptingguide.ai/) | |
| 8. Udemy: ChatGPT Complete Guide [link](https://www.udemy.com/course/complete-ai-guide/) | |
| 9. Prompt Tips by IBM [link](https://www.ibm.com/docs/en/watsonx?topic=models-prompt-tips) | |
| 10. 12 PE Techniques [link](https://cobusgreyling.medium.com/12-prompt-engineering-techniques-644481c857aa) | |
| 11. Understanding prompts, completions, and tokens [link](https://subscription.packtpub.com/book/data/9781800563193/2/ch02lvl1sec06/understanding-prompts-completions-and-tokens) | |
| 12. Text Generation (HF) [link](https://huggingface.co/tasks/text-generation) | |
| 13. Prompt Engineering for Effective Interaction with ChatGPT [link](https://machinelearningmastery.com/prompt-engineering-for-effective-interaction-with-chatgpt/) | |
| 14. A Complete Introduction to Prompt Engineering For Large Language Models [link](https://www.mihaileric.com/posts/a-complete-introduction-to-prompt-engineering/) | |
| 15. Awesome ChatGPT Prompts [link](https://github.com/f/awesome-chatgpt-prompts) | |
| 16. Prompt Engineering Guide: How to Engineer the Perfect Prompts [link](https://richardbatt.co.uk/prompt-engineering-guide-how-to-engineer-the-perfect-prompts/) | |
| 17. Prompt Variables and Definitions GoogleDoc[link](https://docs.google.com/document/d/1KRo_ccokECGg-cbCYwHzLgaAJFpNLL8Xu1ZWjb4LWAU/edit) | |
| 18. 10 Essential Prompt Engineering Methods [link](https://www.topbots.com/prompt-engineering-chatgpt-llm-applications/) | |
| 19. Mastering Generative AI and Prompt Engineering: [link](https://s3.eu-central-1.amazonaws.com/up.raindrop.io/raindrop/files/623/017/898/Mastering_Generative_AI_and_Prompt_Engineering_230808_115249.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=ASIAZWICFKR6VEFG7UJT%2F20230808%2Feu-central-1%2Fs3%2Faws4_request&X-Amz-Date=20230808T220803Z&X-Amz-Expires=1800&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEO3%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEaDGV1LWNlbnRyYWwtMSJIMEYCIQDLpx1IJMkqiTN60IOb4rcuJEaISYkR2tXwjNazse0UngIhAJNfz7SWIckcECvJEWRCLcRidfBSWK5HCAedCyKDpKwGKoEECJb%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEQABoMNjY2MjYxMzQ1NDA1IgxpfjieHhFAElmqZOQq1QMQe0fqu1LXGixZQ6Tn7xeJc9BBtolNLZ0WAKWa%2F5S01NNjbcHq5NEUSPzCwsvyCSf64cF7aGtI3GhSjbNIctcLxvmLJG%2B3gAlLu6WiCTHiKDEg3uD1WrrGV%2F1qaS0uOgz1ZOcvNgoEm6NSHslSPS90CvPlqZ0gKrAUY2GoBWUGDq2eZmGWSDgpdFufjK%2BwiOG9RDaKY1nqfQ3ihih42WHexurp81JzOmpOz014Vpc7O55LnVwqxDFhUCGOsQIARc8dHc3gzuSoIbYwlhaaDswVtcfrF%2FMUPOQ94W08QPnbLFKwkl8j1TJSHxicbqQmY8FUIKJmWXMzkAGz3qU9SiukcFtfpHIFZvEVmIL8mgVXKfO%2F5hsVoxAmpDGwXOJjyjMg3TFVvL%2FcaD1qK5pbdRYhSxjRPKKqE%2FOkXXNTkUauh%2F1TZ2OoZRaZVlxYA1x4UiMmDVaiDy6fkcBDxUUOldq3XmA1xIEr9QqaJfsGajfouENahFPlBP58%2B139bLo9A6Oqv3tuYbaATtogI8pfmID6hdmuLBHQoXZBhdJ3dxXTLW0Y8fquRB4KU9c99596agpn8%2FHgaicSQnTAplh6t6oj4wApEWJn3JS%2BdgBzMryOMkA9XXznMN7KyqYGOqQBTNVcqOk%2FpeEezP6XLp9iD608k8ceWjrYMNsVM3hsRmcI8kJMMGK6BPiZrZv0Mzvz94ap6hHyYSYdeJ3YAKAKa3ZcZ9AcFQqWwXFWuGzH6UsGWP71VIEBeflPf1%2FTFjzGO75TKV29WMhY4ciFMAwLWRs74g%2BOrgscBNkmqDFnK%2B1Tw56Cse8OVhd1CwkbvFhYEX7DPF%2Bojl3f0DKHNQom8XdT9zA%3D&X-Amz-Signature=dfa2113f1cdecba590d32e05fb4e4e18da52ce1c5e698c07253ea94f29ffcaa7&X-Amz-SignedHeaders=host&x-id=GetObject) | |
| Limitations: | |
| 1. Against LLM maximalism [link](https://explosion.ai/blog/against-llm-maximalism) | |
| 2. A Categorical Archive of ChatGPT Failures [link](https://medium.com/@aliborji/a-categorical-archive-of-chatgpt-failures-2c888805d3c3) | |
| 3. 10 Essential Prompt Engineering Methods [link](https://www.topbots.com/prompt-engineering-chatgpt-llm-applications/) | |
| """) | |
| st.subheader("GenAI Tools") | |
| st.markdown(""" | |
| Chat Interfaces: | |
| 1. ChatGPT [link](https://chat.openai.com/) | |
| 2. Claude [link](https://claude.ai/) | |
| 3. Perplexity LLama: [link](https://labs.perplexity.ai/) | |
| 4. OoBabooga Web UI (diy) [link](https://github.com/oobabooga/text-generation-webui) | |
| 5. Vercel Model Comparison [link](https://sdk.vercel.ai/prompt) | |
| Front-End: | |
| 1. Databutton [link](https://www.databutton.io/) | |
| 2. Streamlit [link]() | |
| 3. Gradio [link]() | |
| Prompt Engineering: | |
| 1. Vercel AI Prompt [link](https://sdk.vercel.ai/prompt) | |
| Frameworks: | |
| 1. LangChain | |
| 2. LlamaIndex | |
| Agents: | |
| 1. Baby AGI | |
| 2. Auto GPT | |
| """) | |
| st.subheader("AI Ethics") | |
| st.markdown(""" | |
| Keywords: [Responsible AI, Constitutional AI, Data Ethics, Bias, Carbon Footprint, AI Guardrails, Sampling Bias] | |
| 1. MS Responsible AI Standard: [link](https://blogs.microsoft.com/wp-content/uploads/prod/sites/5/2022/06/Microsoft-Responsible-AI-Standard-v2-General-Requirements-3.pdf) | |
| 2. Compliance: SOC 2 | |
| 3. Anthropic/Constitutional AI: [link to paper](https://arxiv.org/pdf/2212.08073.pdf) | |
| 4. Should we trust web scraped data? [link to paper](https://arxiv.org/pdf/2308.02231.pdf) | |
| 5. Open Voice Network [link](https://openvoicenetwork.org/) | |
| """) | |
| st.subheader("People to follow") | |
| st.markdown(""" | |
| 1. Andrew Ng - Coursera/DeepLearning.ai | |
| 2. Harrison Chase - LangChain Founder | |
| 3. Luis Serrano [link](https://serrano.academy/) | |
| """) | |
| st.subheader("Models") | |
| st.markdown(""" | |
| 1. OpenAI - GPT-3.5/GPT-4 - ChatGPT | |
| 2. Google - ?? - Bard | |
| 3. Anthropic - Claude2 - Claude | |
| 4. Cohere - Coral | |
| 5. Meta - Lambda - ?? | |
| 6. HuggingFace - ?? | |
| 7. AI21 Studio - Jurassic-2 [link](https://www.ai21.com/) | |
| 8. OpenAssistant [link](https://open-assistant.io/) | |
| """) | |
| st.subheader("Training & Evaluation") | |
| st.markdown(""" | |
| 1. HuggingFace/LLM Leadership Board [link](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) | |
| 2. Stanford/Evaluating LLMs Paper [link](https://stanford-cs324.github.io/winter2022/projects/CS324_P1.pdf) | |
| 3. Prolific [link](https://www.prolific.co/) | |
| """) | |
| st.subheader("Case Studies") | |
| st.markdown(""" | |
| 1. AI21 Case Studies: [link](https://www.ai21.com/category/case-study) | |
| """) | |
| st.header("Conversational AI & Chatbots") | |
| st.subheader("Live Chatbots Collection") | |
| st.markdown(""" | |
| 1. HP Virtual Agent [link](https://virtualagent.hpcloud.hp.com/) | |
| 2. Vodafone - TOBi [link](https://www.vodafone.co.uk/contact-us/) | |
| 3. CDI Global - Cee [link](https://cdisglobal.com/) | |
| 4. Bank of America - Erica [link](https://promotions.bankofamerica.com/digitalbanking/mobilebanking/erica) | |
| """) | |
| st.subheader("Conversational Banking") | |
| st.markdown(""" | |
| 1. Action AI [link1](https://action.ai/banking-in-the-metaverse/), [link2](https://action.ai/banking/), [link3](https://action.ai/the-good-the-bad-and-bank-branch-closures/) | |
| 2. Aimultiple [link](https://research.aimultiple.com/conversational-banking/) | |
| 3. Sinch [link](https://www.sinch.com/blog/conversational-banking/) | |
| """) | |
| st.subheader("Other") | |
| st.markdown(""" | |
| 1. Chatbot Metrics/KPIs/OKRs | |
| 2. Chatbot Localisation/Multi-language chatbots | |
| 3. Conversation Design | |
| 4. Tools: DialogFlow, Microsoft Bot Framework, IBM Watson; | |
| 5. Channels: Web, Messangers, Telephony. | |
| 6. Cases: [CDI Global](https://cdisglobal.com/cases/) | |
| 7. Cases [Boost AI](https://www.boost.ai/case-studies) | |
| 8. Cases [Kore AI](https://kore.ai/chatbot-case-studies/) | |
| 9. Cases [Poly AI](https://poly.ai/case-studies/) | |
| 10. Initial Model of Trust in Chatbots [link](https://www.duo.uio.no/bitstream/handle/10852/74147/An+initial+model+of+trust+in+chatbots+for+customer+service+-+authors+version.pdf?sequence=1) | |
| 11. Stanford NLP Course [link](https://www.youtube.com/watch?v=rmVRLeJRkl4&list=PLoROMvodv4rOSH4v6133s9LFPRHjEmbmJ&index=1&ab_channel=StanfordOnline) | |
| """) | |
| st.markdown('***') | |
| st.markdown("Move to Furo: [link](https://pradyunsg.me/furo/reference/admonitions/)") |