Has used agenerative AImodel tocreate art ormusicHas experiencewith low-resourcelanguages inNLPIs interestedin the ethicalimplicationsof generativeAIHasexperiencewith fine-tuning a pre-trained LLMHas used anLLM tosummarizeresearchpapersCan explain thedifferencebetween causaland maskedlanguagemodelsCan namethreedifferent LLMarchitecturesIs optimisticabout thefuture ofhuman-AIcollaborationHassuccessfullydebugged acomplexLLMHas used agenerative AImodel for anon-academicpurposeHas presenteda paper onnaturallanguagegenerationIs familiarwith theconcept ofpromptengineeringCanrecommenda good AI ortech relatedpodcastHas apreferred AIresearch toolthey canrecommendHas used anLLM in alanguageother thanenglishHasattended anICMLconferencebeforeHascontributedto an open-source AIprojectHaspublishedresearch onmultilingualLLMsHas learneda newlanguage inthe last yearHasparticipated ina hackathonfocused on AIor LLMsIs excitedabout thepotential ofLLMs ineducationHas collaboratedon a researchpaper withsomeone from adifferent continentHas traveledinternationallyto attend thisconferenceKnows atleast threeprogramminglanguagesHas used agenerative AImodel tocreate art ormusicHas experiencewith low-resourcelanguages inNLPIs interestedin the ethicalimplicationsof generativeAIHasexperiencewith fine-tuning a pre-trained LLMHas used anLLM tosummarizeresearchpapersCan explain thedifferencebetween causaland maskedlanguagemodelsCan namethreedifferent LLMarchitecturesIs optimisticabout thefuture ofhuman-AIcollaborationHassuccessfullydebugged acomplexLLMHas used agenerative AImodel for anon-academicpurposeHas presenteda paper onnaturallanguagegenerationIs familiarwith theconcept ofpromptengineeringCanrecommenda good AI ortech relatedpodcastHas apreferred AIresearch toolthey canrecommendHas used anLLM in alanguageother thanenglishHasattended anICMLconferencebeforeHascontributedto an open-source AIprojectHaspublishedresearch onmultilingualLLMsHas learneda newlanguage inthe last yearHasparticipated ina hackathonfocused on AIor LLMsIs excitedabout thepotential ofLLMs ineducationHas collaboratedon a researchpaper withsomeone from adifferent continentHas traveledinternationallyto attend thisconferenceKnows atleast threeprogramminglanguages

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