Can namethreedifferent LLMarchitecturesHassuccessfullydebugged acomplexLLMHas used anLLM tosummarizeresearchpapersHas traveledinternationallyto attend thisconferenceIs optimisticabout thefuture ofhuman-AIcollaborationIs familiarwith theconcept ofpromptengineeringHas learneda newlanguage inthe last yearHaspublishedresearch onmultilingualLLMsHas used agenerative AImodel tocreate art ormusicKnows atleast threeprogramminglanguagesHasparticipated ina hackathonfocused on AIor LLMsHasexperiencewith fine-tuning a pre-trained LLMHas experiencewith low-resourcelanguages inNLPHas used anLLM in alanguageother thanenglishHas collaboratedon a researchpaper withsomeone from adifferent continentIs excitedabout thepotential ofLLMs ineducationIs interestedin the ethicalimplicationsof generativeAICan explain thedifferencebetween causaland maskedlanguagemodelsHas used agenerative AImodel for anon-academicpurposeHascontributedto an open-source AIprojectHasattended anICMLconferencebeforeHas presenteda paper onnaturallanguagegenerationHas apreferred AIresearch toolthey canrecommendCanrecommenda good AI ortech relatedpodcastCan namethreedifferent LLMarchitecturesHassuccessfullydebugged acomplexLLMHas used anLLM tosummarizeresearchpapersHas traveledinternationallyto attend thisconferenceIs optimisticabout thefuture ofhuman-AIcollaborationIs familiarwith theconcept ofpromptengineeringHas learneda newlanguage inthe last yearHaspublishedresearch onmultilingualLLMsHas used agenerative AImodel tocreate art ormusicKnows atleast threeprogramminglanguagesHasparticipated ina hackathonfocused on AIor LLMsHasexperiencewith fine-tuning a pre-trained LLMHas experiencewith low-resourcelanguages inNLPHas used anLLM in alanguageother thanenglishHas collaboratedon a researchpaper withsomeone from adifferent continentIs excitedabout thepotential ofLLMs ineducationIs interestedin the ethicalimplicationsof generativeAICan explain thedifferencebetween causaland maskedlanguagemodelsHas used agenerative AImodel for anon-academicpurposeHascontributedto an open-source AIprojectHasattended anICMLconferencebeforeHas presenteda paper onnaturallanguagegenerationHas apreferred AIresearch toolthey canrecommendCanrecommenda good AI ortech relatedpodcast

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