Canrecommenda good AI ortech relatedpodcastHas learneda newlanguage inthe last yearHasparticipated ina hackathonfocused on AIor LLMsHas used anLLM tosummarizeresearchpapersHascontributedto an open-source AIprojectHas apreferred AIresearch toolthey canrecommendHassuccessfullydebugged acomplexLLMHasexperiencewith fine-tuning a pre-trained LLMIs excitedabout thepotential ofLLMs ineducationCan explain thedifferencebetween causaland maskedlanguagemodelsHas traveledinternationallyto attend thisconferenceKnows atleast threeprogramminglanguagesHas presenteda paper onnaturallanguagegenerationIs familiarwith theconcept ofpromptengineeringHasattended anICMLconferencebeforeHas used agenerative AImodel for anon-academicpurposeHas used agenerative AImodel tocreate art ormusicIs optimisticabout thefuture ofhuman-AIcollaborationIs interestedin the ethicalimplicationsof generativeAICan namethreedifferent LLMarchitecturesHas experiencewith low-resourcelanguages inNLPHas used anLLM in alanguageother thanenglishHas collaboratedon a researchpaper withsomeone from adifferent continentHaspublishedresearch onmultilingualLLMsCanrecommenda good AI ortech relatedpodcastHas learneda newlanguage inthe last yearHasparticipated ina hackathonfocused on AIor LLMsHas used anLLM tosummarizeresearchpapersHascontributedto an open-source AIprojectHas apreferred AIresearch toolthey canrecommendHassuccessfullydebugged acomplexLLMHasexperiencewith fine-tuning a pre-trained LLMIs excitedabout thepotential ofLLMs ineducationCan explain thedifferencebetween causaland maskedlanguagemodelsHas traveledinternationallyto attend thisconferenceKnows atleast threeprogramminglanguagesHas presenteda paper onnaturallanguagegenerationIs familiarwith theconcept ofpromptengineeringHasattended anICMLconferencebeforeHas used agenerative AImodel for anon-academicpurposeHas used agenerative AImodel tocreate art ormusicIs optimisticabout thefuture ofhuman-AIcollaborationIs interestedin the ethicalimplicationsof generativeAICan namethreedifferent LLMarchitecturesHas experiencewith low-resourcelanguages inNLPHas used anLLM in alanguageother thanenglishHas collaboratedon a researchpaper withsomeone from adifferent continentHaspublishedresearch onmultilingualLLMs

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