Has used agenerative AImodel for anon-academicpurposeHas used agenerative AImodel tocreate art ormusicCan namethreedifferent LLMarchitecturesIs optimisticabout thefuture ofhuman-AIcollaborationIs familiarwith theconcept ofpromptengineeringKnows atleast threeprogramminglanguagesHas used anLLM tosummarizeresearchpapersHaspublishedresearch onmultilingualLLMsHas presenteda paper onnaturallanguagegenerationHasattended anICMLconferencebeforeHascontributedto an open-source AIprojectCan explain thedifferencebetween causaland maskedlanguagemodelsHas collaboratedon a researchpaper withsomeone from adifferent continentIs interestedin the ethicalimplicationsof generativeAIHas experiencewith low-resourcelanguages inNLPIs excitedabout thepotential ofLLMs ineducationHassuccessfullydebugged acomplexLLMIs currentlyworking on aprojectinvolving cross-lingual transferlearningHas traveledinternationallyto attend thisconferenceHas learneda newlanguage inthe last yearCanrecommenda good AI ortech relatedpodcastHasparticipated ina hackathonfocused on AIor LLMsHas apreferred AIresearch toolthey canrecommendHasexperiencewith fine-tuning a pre-trained LLMHas used agenerative AImodel for anon-academicpurposeHas used agenerative AImodel tocreate art ormusicCan namethreedifferent LLMarchitecturesIs optimisticabout thefuture ofhuman-AIcollaborationIs familiarwith theconcept ofpromptengineeringKnows atleast threeprogramminglanguagesHas used anLLM tosummarizeresearchpapersHaspublishedresearch onmultilingualLLMsHas presenteda paper onnaturallanguagegenerationHasattended anICMLconferencebeforeHascontributedto an open-source AIprojectCan explain thedifferencebetween causaland maskedlanguagemodelsHas collaboratedon a researchpaper withsomeone from adifferent continentIs interestedin the ethicalimplicationsof generativeAIHas experiencewith low-resourcelanguages inNLPIs excitedabout thepotential ofLLMs ineducationHassuccessfullydebugged acomplexLLMIs currentlyworking on aprojectinvolving cross-lingual transferlearningHas traveledinternationallyto attend thisconferenceHas learneda newlanguage inthe last yearCanrecommenda good AI ortech relatedpodcastHasparticipated ina hackathonfocused on AIor LLMsHas apreferred AIresearch toolthey canrecommendHasexperiencewith fine-tuning a pre-trained LLM

Human BINGO: Navigating Generative AI and LLMs Across Languages - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Has used a generative AI model for a non-academic purpose
  2. Has used a generative AI model to create art or music
  3. Can name three different LLM architectures
  4. Is optimistic about the future of human-AI collaboration
  5. Is familiar with the concept of prompt engineering
  6. Knows at least three programming languages
  7. Has used an LLM to summarize research papers
  8. Has published research on multilingual LLMs
  9. Has presented a paper on natural language generation
  10. Has attended an ICML conference before
  11. Has contributed to an open-source AI project
  12. Can explain the difference between causal and masked language models
  13. Has collaborated on a research paper with someone from a different continent
  14. Is interested in the ethical implications of generative AI
  15. Has experience with low-resource languages in NLP
  16. Is excited about the potential of LLMs in education
  17. Has successfully debugged a complex LLM
  18. Is currently working on a project involving cross-lingual transfer learning
  19. Has traveled internationally to attend this conference
  20. Has learned a new language in the last year
  21. Can recommend a good AI or tech related podcast
  22. Has participated in a hackathon focused on AI or LLMs
  23. Has a preferred AI research tool they can recommend
  24. Has experience with fine-tuning a pre-trained LLM