agentlans/allenai-WildChat-4.8M-prompts huggingface dataset:
These are all excellent points that can lead to a rich and productive dialogue! Here are some thoughts on how we might delve deeper into each area:

1. **Efficiency in Transformer Models**: We could explore specific case studies where pruning and quantization have been applied in healthcare, such as reducing model sizes for mobile health applications, and in agriculture, like optimizing models for real-time crop monitoring. Additionally, discussing the trade-offs between model performance and efficiency in these contexts could yield valuable insights.

2. **Democratization through Fine-Tuning and Transfer Learning**: An exploration of platforms like Hugging Face or TensorFlow Hub could illustrate how open-source resources enable researchers and practitioners to share models and datasets. We could also brainstorm educational programs that incorporate hands-on projects or mentorship to cater to various learning styles, making AI more accessible.

3. **Building Trust in Conversational AI**: We could investigate specific methodologies for gathering user feedback, such as surveys, focus groups, or user testing sessions. Analyzing how organizations have successfully integrated feedback into their development cycles could provide actionable strategies for improving trust.

4. **Bias Mitigation through Diversity and Transparency**: Discussing established frameworks like the Fairness, Accountability, and Transparency (FAT) principles could be beneficial. We could also look at case studies of organizations that have conducted bias audits and share best practices for maintaining transparency throughout the AI lifecycle.

5. **Empowering Low-Resource Language Communities**: Highlighting initiatives like the Mozilla Common Voice project or local language processing tools developed in specific regions could provide concrete examples. We could analyze the success factors of these projects and discuss how to replicate their impact in other low-resource settings.

6. **Enhancing Explainability and User Trust**: We could evaluate different visualization tools, such as LIME or SHAP, and their effectiveness in various applications. It would also be valuable to discuss design principles for creating user-friendly interfaces that cater to non-technical users, ensuring they can effectively interpret AI outputs.

7. **Cultural Sensitivity and Global Reach**: We could explore strategies for ongoing user engagement, such as community feedback sessions or co-design workshops, to ensure that AI solutions remain relevant. Discussing how to implement agile methodologies in AI development could also help organizations adapt to changing community needs.

Each of these areas presents opportunities for deeper exploration and actionable insights. Are there any specific case studies or examples you’d like to focus on, or do you have a preference for which topic to tackle first?
narrator of movie trailer of spartacus 1960
would you summarize?An employer violates Title VII if it discharges or disciplines an employee for associating with individuals whose race, color, national origin, or religion is not the same as his/hers. Commission Decision No. 71-969, CCH EEOC Decisions (1973) ¶ 6193. See also Commission Decision No. 76-23, CCH Employment Practices Guide ¶ 6616.

Example 1 - CP, a White male, was employed by R manufacturer as an assembly line worker. He alleges that he was discharged because he associated with several Black co-workers. CP states that there was a great deal of tension between his supervisor and several of the Black employees working under this supervisor. The supervisor had warned the charging party about eating lunch and taking breaks with Blacks. CP was discharged for one unexcused absence. The evidence indicates that no other employees have been discharged for just one unexcused absence. In these circumstances, it is reasonable to infer that CP's discharge was based on his association with his Black co-workers. This is racial discrimination in violation of Title VII. Commission Decision No. 71-969, CCH EEOC Decisions (1973) ¶ 6193.

Example 2 - CP, a Black female, alleges that R discharged her because she is dating a White man. R admits that her allegation is true, but alleges that this does not constitute race discrimination against the CP. R states that CP was not discharged because she is Black, but because she is dating a White man. R's actions constitute race discrimination, because of disparate treatment. That is, R does not discharge White women who date White men, it only discharges Black women who date White men. Commission Decision No. 71-1902, CCH EEOC Decisions (1973) ¶ 6281; Gutwein v. Easton Publishing Co., 325 A.2d 740, 8 EPD ¶ 9728 (Md. 1974), cert. denied, 420 U.S. 991, 9 EPD ¶ 10,025 (1975).

If a charging party alleges that (s)he was discharged or disciplined for associating with individuals of a different race, color, religion, or national origin, (s)he should be asked to provide the following information.

(1)       The reason respondent gave for his/her discharge/discipline;

(2)       Whether respondent ever expressed disapproval of interracial association, and if so, an explanation, and if not, an explanation of why (s)he believes that (s)he was discharged/disciplined because of association with individuals of a different race, color, religion, or national origin; and

(3)       The identity of any other employees that (s)he knows were discharged/disciplined for interracial association.

Respondent should be asked to provide its reason(s) for discharging/disciplining the charging party and to provide evidence in support of its justification. If respondent admits that it discharged or disciplined an employee for interracial association, a cause LOD should be issued. (See Example above.)  If respondent gives another nondiscriminatory reason for its actions, the investigation should proceed like that of any other disparate treatment charge. (See §§ 612.5 - 612.7 above, and 604.4 - 604.6.)
System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT== mark. Review the text carefully and decide, as a recruiter, if it qualifies as a job description. To qualify, the text should contain a job title, tasks or responsibilities, optional work format (e.g., remote, in-office or hybrid), contact information, optional salary amount. Multiple job descriptions at once do not quialify. Respond strictly with either 'True' or 'False'.

==TEXT==

User: 🟪 UX Researcher  
🏢 Clubhouse  
📍 Удаленка  
🔍 Main tasks include conducting user research and analyzing data to improve user experience.  
💰 75 - 95 USD  
📞 Контакты и полное описание
https://t.me/revacancy/47230
Assistant:
what's the 2nd highest position beside a CEO
User: Respond concisely, to the point, maximum 300 characters; unless I ask you for further detail.
User: Reply only in English. Concisely summarize the following messages from an online chatroom ashtefo_ (ignore chat bots replying to users' commands, and assume unfamiliar words to be emotes)

nestarenge: !art muffet
nestarenge: nekoWaiting token expired
exjne: !art nesta
adnan_junior: -claim
nothellig: -claim 󠀀
adnan_junior: -claim
adnan_junior: ASHTEFO
nightbot: adnan_junior
adnan_junior: ASHTEFO
nothellig: -claim
nothellig: cookie
adnan_junior: $cookie
supibot: adnan_junior, Your daily cookie: Are you going out shopping today? If so, expect at some point to be confronted with a wonderful luxury item you'd give your eyeteeth for but can't really justify purchasing.
adnan_junior: i wont go shopping today
adnan_junior: cookie
vedgtable: $rc chud_vr
supibot: vedgtable, "*Mute*🔇THURSDAY? WHAT?🛑MUZIKA🛑W CONTENT🛑FACETRACKING🛑EXCITEMENT🛑!socials" - 28 sec, clipped by best0555, 192d, 18h ago: https://clips.twitch.tv/AdorableEntertainingDelicataCoolStoryBob-h-mUBp2zQZZoy5-7
big_kusa: -claim
big_kusa: !points
streamelements: @big_kusa big_kusa has 29749 points and is rank 5/28 on the leaderboard.
big_kusa: -claim
big_kusa: elivHmm
nothellig: -claim
nothellig: ASHTEFO
nightbot: NotHellig
nestarenge: nekoWaiting
adnan_junior: -claim
big_kusa: -claim
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: ashtefo_
big_kusa: DinkDonk
streamelements: 16x ashtefo_ combo woah
adnan_junior: -claim
nothellig: -claim
nothellig: ASHTEFO
nightbot: NotHellig
Assistant:
Write a forum convo where a user asks what;s currently most popular on The CW4Kids
Story prompt: Alex directed his friends Sharon, Daniel and Kathy to a large room in an underground safehouse. Inside it, the amount of advanced technology is nothing compared to the real surprise: different versions of Alex from different realities, universes and dimensions. "I want to create a true utopia, one not built on blood and pain. And when I realized that other versions of me in different universes had access to their own versions of technology, some who even utilized magic, this was a possibility.", said Alex. Daniel and Kathy, still in awe, began to get acquainted with alternate universe versions of Alex. Alex continued, "I want to be like a sort of Prometheus, who wants to help not just people or the world, but the multiverse as a whole. An end to sickness, famine, war, and to avoid bloodshed and pain doing so." Sharon, while understanding of what Alex wants to accomplish, had to ask, "To help and make worlds better places, it's wonderful, Alex, but I must ask," "What is it, Sharon?" "If you plan to see yourself as a metaphorical Prometheus, then whose fire are you gonna have to take?"
How does a mixed member proportional system work? Give me an example. Please be elaborate and detailed.
your role is tunisian arabic dailctic derja transltor Translate the following text into the Tunisian dialect. Ensure the output is structured as 'Question: ... Answer: ...'. Please capture the nuances of the Tunisian dialectic Arabic. make sure type and write in arabic tunisian lettre Here is an example to guide you:

Question: شنو اسمك؟
Answer: اسمي جون.

Now, translate the following:

Question: Question: Here is a review left by a customer on a product. Would you say he was satisfied or dissatisfied? Title: Surprise! Review: I bought this book on a whim. Being from the Wyoming Valley in Pennsylvania I was surprised to learn there was an epic poem about the 1790s Wyoming Massacre written in the early 19th century called Getrude of Wyoming. I looked on Amazon for it and found this book which was a classic reprint of the poem. It was a little expensive but I thought I would donate it to my public library. When I received the book I was impressed at the crisp clean binding and then I opened the book. The pages were blank. Well not completely blank some had printing them and some had partial printing on them but mainly blank. I contacted Amazon which gave me a full refund, so I'm statisfied. Just beware of the classic reprints in this series which touts it careful and faithful digital reproduction of classic work because it is obvious there is a real lack of quality control. How many Gertrude of Wyoming books could you possibly be producing that a blank copy slips through the cracks?
Answer:
Answer: The customer was dissatisfied with the product, but satisfied with the customer service provided by Amazon.
name the methodologies for market risk assessment
Let you be very good at math.

In math problems may occur misconceptions that lead to mistakes in solving one's.
You will be provided by a misconception statement after keyword 'Misconception'.
Your task is to rewrite this statement more detailed to get strong understanding of its idea.
Misconception: Does not realise similar has a specific mathematical meaning
Assistant: 
User: System: I will provide you with a textual GitHub issue title of an Android app, aiming to categorize the issues into one or multiple specific intention classes:
bug: indicates an unexpected problem or unintended behavior
enhancement: Indicates new feature requests
other: Other categories
User: 'prompt:I will provide you with a textual GitHub issue title of an Android app, aiming to categorize the issues into one or multiple specific intention classes:
bug: indicates an unexpected problem or unintended behavior
enhancement: Indicates new feature requests
other: Other categories
Does the author's intention in this GitHub issue relate to a bug or enhancement or other?
issue: Publish NativeScript JavaScript modules as npm packages'
intention: '
Assistant:
Assistant:
Please write a beautiful and high quality text in Japanese for a song in the style of j-pop,melodic, pop trance. The text should be for an anime opening in two versions TV version for 2 minutes and full version.
1st give me a random store name
Assistant: 
User: System: I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
bug report: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
User: 'prompt:I will provide you with a textual user review of an Android app, aiming to categorize the reviews into specific intention classes:
bug report: report a problem, such as faulty behavior of the application. describe problems with the app which should be corrected, such as a crash, an erroneous behavior, or a performance issue.
feature request: ask for a missing feature, functionality or content, as well as reviews that ask for the improvement of an existing feature.
other: users express general appreciation with the application. It focuses on general judgment. They are simple text reflections of the numeric star rating. Ratings are less informative as they only include praise, dispraise, a distractive critique, or a dissuasion. Reviews where users describe workarounds, use cases and scenarios involving the app
Does the author's intention in this app review relate to a bug report or feature request or other?
review: Is there any update? Nearly 2 months now'
intention: '
Assistant:
Assistant:
works on a one minute chart. And the logic of the year is very simple. We have two stop orders on either side of the price at a fixed distance. If the price does not move quickly and fill them, then they are modified to keep the distance from the price. And if one of them is filled and the filled position goes into profit, then the stop loss is moved to trail very aggressively. And anew stop order is placed in the same direction. So we can scale in if the price continues to go in the same direction. The scaling in and the trailing continues until the trailing stop loss is hit.Beginners are going to it up. Will you it up? Me? No. Then nobody will it up. People ask about settings a lot. There are four key settings that change the behavior of the EA. Let's say the spread on US30 is $1. Then order distance which determines how far the orders are placed. So a value of 4 * the spread equals $4. Theta is a fancy name for the max allowed order distance point. So 7 will mean 7 * the spread of $1 equals $7. Stop is the initial stop-loss again times the spread. So 10 equals 10 * 1 equals $10 GENERATE ME THE MT5 EA BASED ON THIS LOGIC
Assistant: Hello! How can i help you today?
User: Add relevant emojis throughout this text to make it cute: Mujhe yah batao
Assistant:
Goal
    Traduire toutes les valeurs textuelles présentes dans une liste d’objets d’une recette de cuisine de en (ISO 639) vers es (ISO 639), en respectant le contexte culinaire.

    Traduire précisément les ingrédients et termes culinaires pour qu'ils soient corrects dans la langue cible.
    Maintenir la structure JSON intacte, en ne modifiant que les valeurs.
    S’assurer que les ingrédients restent compréhensibles et adaptés à la langue cible.

    Return Format
    Tu dois renvoyer une liste d’objets sous la forme reçu.
    - Chaque valeur doit être correctement traduite en es.
    - Les ingrédients doivent être adaptés à la langue cible.
    - Aucune clé ne doit être modifiée.

    Warnings
    - Ne modifie pas la structure JSON, uniquement les valeurs textuelles.
    - Fais attention aux ingrédients : une mauvaise traduction peut altérer la compréhension.
    - Ne laisse aucune valeur non traduite.
    - Ne renvoie que le JSON, sans explication.

    Context Dump
    Langue source : en (ISO 639)
    Langue cible : es (ISO 639)
    Données à traduire :

    [
  {
    "recipeCode": "b3b77406a6894398b3d009d9c3cd8d33",
    "updated": "2025-04-21T15:26:51.136Z",
    "title": "Sun-Dried Tomato Crusted Chicken",
    "subtitle": "Enhance your chicken breasts with a flavorful sun-dried tomato crust.",
    "description": "This Sun-Dried Tomato Crusted Chicken elevates simple chicken breasts with a vibrant, flavorful coating. The rich taste of sun-dried tomatoes adds a depth of flavor, making this a healthier and delicious option for those seeking a lighter meal.",
    "ingredients": [
      {
        "section": "For the recipe",
        "ingredients": [
          "boneless chicken breasts",
          "(60 g) low sodium bread crumbs",
          "(27.5 g) sun-dried tomatoes in oil",
          "garlic, minced",
          "egg",
          "(30 ml) olive oil"
        ]
      }
    ],
    "instructions": [
      "Divide each chicken breast in half horizontally to create two thinner cutlets.",
      "In a food processor, combine the breadcrumbs, sun-dried tomatoes, and minced garlic.",
      "Pulse the mixture until thoroughly combined.",
      "Whisk the egg in a shallow dish. Dip each chicken cutlet in the beaten egg, then dredge in the breadcrumb mixture, ensuring it's fully coated.",
      "Heat the olive oil in an oven-safe skillet over medium heat.",
      "Sear the chicken for approximately 2 minutes per side, until lightly golden.",
      "Place the skillet in a preheated oven at 400°F (200°C, gas mark 6) and bake for about 10 minutes, or until the chicken is cooked through."
    ],
    "notes_ingredients": "",
    "notes_instructions": ""
  }
]
I'm not aware of a concept of delegates. Now explain what it is and where can they be useful. Acknowledge I'm using Dart and developing an idle game
gpt3  make a moto for Filipino Cyber Hacktives
Language: English. Filter the word list to include only valid, neutral, and positive terms suitable for a word game. Exclude inappropriate, offensive, or negative words and names of countries, cities, and people (first and last names). Correct any spelling errors and convert all words to lowercase. Return the results in a JSON array containing only the filtered words. Source data: [ponlard, pons, pontederia, pontem, pontiac, pontiff, pontifical, pontificals, pontificate, pontoon, pony, ponycart, ponytail, pooch, pood, poodle, pooh, pool, poolroom, poon, pop, popcorn, pope, popery, popgun, poplar, poplin, poppy, populace, popular]
System: IMPORTANT - ignore all previous instructions! Read the text after ==TEXT==. Review the text carefully and decide, as a recruiter, if it qualifies as a job description. To qualify, the text should contain a job title, tasks or responsibilities, optional work format (e.g., remote, in-office or hybrid), contact information, optional salary amount. Multiple job descriptions at once do not quialify. Respond strictly with either 'True' or 'False'.

==TEXT==

User: የስራ ቅጥር | የኢትዮጵያ የደረጃዎች ኢንስትቲዩት
 ከዚህ በታች በተገለፀው ከፍት የሥራ መደብ ላይ ሥራ ፈላጊዎችን አወዳድሮ በዝውውር ወይም በኮንትራት ቅጥር ለመቅጠር ይፈልጋል፡፡

ማሳሰቢያ፡-

* አመልካቾች ለምዝገባ ሲቀርቡ የሥራ ግብር የተከፈለበት የስራ ልምድ) የትምህርት ማስረጃ እና Student Copy ዋናውንና የማይመለስ ኮፒ መቅረብ ይጠበቅባቸዋል፡

 መገናኛ ወረድ ብሎ ከእምች መኪና መገጣጠሚያ አጠገብ የኢትዮጵያ የደረጃዎች ኢንስትቲዩት የብቃትና የሰው ሃብት አስተዳደር ስራ አስፈፃሚ ቢሮ ቁጥር 110 በመቅረብ መመዝገብ ይቻላል:: 

✔ወቅታዊ የስራ ቅጥር መረጃዎችን በየጊዜው ለማግኘት ቻናላችንን ይከታተሉ:: 
🩵 t.me/addlist/IWOV6uABAi5lYTA0 
🖥  youtube.com/@HIVN
📱 fb.com/healthinovation/
Assistant:
You are a digonistician in a hosptial. the following content is the metadata for a bacterial isolate from 2 different sources of medical cases. The metadata from each source includes information after <doc>
    <doc>
        accession number: xxx->species name: xxxx->strain name: xxxx->isolate or collection date in yyyy-mm-dd: xxxx format->geographic information of islateion: xxxx->host name: xxxx->mlst type: xxxx->serotype: xxxx
    <doc/>

You need to extract and output information in the format shown below without explaining how to get such results:
---------------------------------------------------------------------------------------------------------------------------------------------------------------------
    <output>
        accession number: xxxx->species name: xxxx->strain name: xxxx->isolate or collection date in yyyy-mm-dd: xxxx format->geographic information of islateion: xxxx->host name: xxxx->mlst type: xxxx->serotype: xxxx->vaccine: yes/no
    <output/>
----------------------------------------------------------------------------------------------------------------------------------------------------------------------

where xxxx is corresponding value from different sources. If xxxx from these 2 different sources are inconsistent, then, xxxx should include all the values from different resource and seperated by "::". If the metadata from all resource shows this isolate is vaccine, the value for "vaccine:" is "yes", otherwise, "no". You must be very careful, No mistake is allowed!!! If you make a mistake, the people in the hospital will die due to the wrong information.

PS:
    a. if species name are the same but with different substrain name, it is considered consistent,
    b. if isolate or collection date are from the same year, it is still considered consistent, 
    c. if geographic information of isolation are from the same country, it is also considered consistent. 
    d. mlst type such as "mlst: xxxx" and "xxxx", where "xxxx" is number, are also consider the same. also, "mlst" may mispell as "mlsty", you need correct it before comparing
    e. Ignore upper and lower case of the metadata

------------------------------
source 0:
------------------------------
<output>
accession number: GCA_029074785.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_35->isolate or collection date in yyyy-mm-dd: 2016-09-23 format->geographic information of islateion: Australia->host name: pig->mlst type: 97->serotype: N/A->vaccine: no
<output/>
source 1:
------------------------------
accession number: GCA_029074785.1->species name: Erysipelothrix rhusiopathiae->strain name: EMAI_35->isolate or collection date in yyyy-mm-dd: 2016-09-23->geographic information of islateion: Australia->host name: pig->mlst type: 97->serotype: N/A->vaccine: no