Is excitedabout thepotential ofLLMs ineducationIs familiarwith theconcept ofpromptengineeringHaspublishedresearch onmultilingualLLMsHas used agenerative AImodel tocreate art ormusicHascontributedto an open-source AIprojectIs interestedin the ethicalimplicationsof generativeAIHas experiencewith low-resourcelanguages inNLPCan namethreedifferent LLMarchitecturesHasattended anICMLconferencebeforeIs currentlyworking on aprojectinvolving cross-lingual transferlearningHas used anLLM tosummarizeresearchpapersHas apreferred AIresearch toolthey canrecommendKnows atleast threeprogramminglanguagesHas traveledinternationallyto attend thisconferenceHas used agenerative AImodel for anon-academicpurposeIs optimisticabout thefuture ofhuman-AIcollaborationHasexperiencewith fine-tuning a pre-trained LLMCan explain thedifferencebetween causaland maskedlanguagemodelsHas presenteda paper onnaturallanguagegenerationCanrecommenda good AI ortech relatedpodcastHasparticipated ina hackathonfocused on AIor LLMsHas learneda newlanguage inthe last yearHassuccessfullydebugged acomplexLLMHas collaboratedon a researchpaper withsomeone from adifferent continentIs excitedabout thepotential ofLLMs ineducationIs familiarwith theconcept ofpromptengineeringHaspublishedresearch onmultilingualLLMsHas used agenerative AImodel tocreate art ormusicHascontributedto an open-source AIprojectIs interestedin the ethicalimplicationsof generativeAIHas experiencewith low-resourcelanguages inNLPCan namethreedifferent LLMarchitecturesHasattended anICMLconferencebeforeIs currentlyworking on aprojectinvolving cross-lingual transferlearningHas used anLLM tosummarizeresearchpapersHas apreferred AIresearch toolthey canrecommendKnows atleast threeprogramminglanguagesHas traveledinternationallyto attend thisconferenceHas used agenerative AImodel for anon-academicpurposeIs optimisticabout thefuture ofhuman-AIcollaborationHasexperiencewith fine-tuning a pre-trained LLMCan explain thedifferencebetween causaland maskedlanguagemodelsHas presenteda paper onnaturallanguagegenerationCanrecommenda good AI ortech relatedpodcastHasparticipated ina hackathonfocused on AIor LLMsHas learneda newlanguage inthe last yearHassuccessfullydebugged acomplexLLMHas collaboratedon a researchpaper withsomeone from adifferent continent

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