Has learneda newlanguage inthe last yearKnows atleast threeprogramminglanguagesCan namethreedifferent LLMarchitecturesIs optimisticabout thefuture ofhuman-AIcollaborationIs excitedabout thepotential ofLLMs ineducationHassuccessfullydebugged acomplexLLMHasattended anICMLconferencebeforeHas used anLLM in alanguageother thanenglishHasexperiencewith fine-tuning a pre-trained LLMHas used anLLM tosummarizeresearchpapersHas used agenerative AImodel tocreate art ormusicHas traveledinternationallyto attend thisconferenceIs familiarwith theconcept ofpromptengineeringHas used agenerative AImodel for anon-academicpurposeHas apreferred AIresearch toolthey canrecommendHaspublishedresearch onmultilingualLLMsHascontributedto an open-source AIprojectCan explain thedifferencebetween causaland maskedlanguagemodelsHas presenteda paper onnaturallanguagegenerationIs interestedin the ethicalimplicationsof generativeAIHas experiencewith low-resourcelanguages inNLPCanrecommenda good AI ortech relatedpodcastHas collaboratedon a researchpaper withsomeone from adifferent continentHasparticipated ina hackathonfocused on AIor LLMsHas learneda newlanguage inthe last yearKnows atleast threeprogramminglanguagesCan namethreedifferent LLMarchitecturesIs optimisticabout thefuture ofhuman-AIcollaborationIs excitedabout thepotential ofLLMs ineducationHassuccessfullydebugged acomplexLLMHasattended anICMLconferencebeforeHas used anLLM in alanguageother thanenglishHasexperiencewith fine-tuning a pre-trained LLMHas used anLLM tosummarizeresearchpapersHas used agenerative AImodel tocreate art ormusicHas traveledinternationallyto attend thisconferenceIs familiarwith theconcept ofpromptengineeringHas used agenerative AImodel for anon-academicpurposeHas apreferred AIresearch toolthey canrecommendHaspublishedresearch onmultilingualLLMsHascontributedto an open-source AIprojectCan explain thedifferencebetween causaland maskedlanguagemodelsHas presenteda paper onnaturallanguagegenerationIs interestedin the ethicalimplicationsof generativeAIHas experiencewith low-resourcelanguages inNLPCanrecommenda good AI ortech relatedpodcastHas collaboratedon a researchpaper withsomeone from adifferent continentHasparticipated ina hackathonfocused on AIor LLMs

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