Haspublishedresearch onmultilingualLLMsHas used agenerative AImodel for anon-academicpurposeHas used agenerative AImodel tocreate art ormusicHasexperiencewith fine-tuning a pre-trained LLMHassuccessfullydebugged acomplexLLMIs excitedabout thepotential ofLLMs ineducationHas presenteda paper onnaturallanguagegenerationHas collaboratedon a researchpaper withsomeone from adifferent continentCan explain thedifferencebetween causaland maskedlanguagemodelsHas experiencewith low-resourcelanguages inNLPHas traveledinternationallyto attend thisconferenceHas used anLLM tosummarizeresearchpapersHas learneda newlanguage inthe last yearCanrecommenda good AI ortech relatedpodcastIs optimisticabout thefuture ofhuman-AIcollaborationHasparticipated ina hackathonfocused on AIor LLMsIs currentlyworking on aprojectinvolving cross-lingual transferlearningKnows atleast threeprogramminglanguagesIs interestedin the ethicalimplicationsof generativeAIHasattended anICMLconferencebeforeHascontributedto an open-source AIprojectIs familiarwith theconcept ofpromptengineeringCan namethreedifferent LLMarchitecturesHas apreferred AIresearch toolthey canrecommendHaspublishedresearch onmultilingualLLMsHas used agenerative AImodel for anon-academicpurposeHas used agenerative AImodel tocreate art ormusicHasexperiencewith fine-tuning a pre-trained LLMHassuccessfullydebugged acomplexLLMIs excitedabout thepotential ofLLMs ineducationHas presenteda paper onnaturallanguagegenerationHas collaboratedon a researchpaper withsomeone from adifferent continentCan explain thedifferencebetween causaland maskedlanguagemodelsHas experiencewith low-resourcelanguages inNLPHas traveledinternationallyto attend thisconferenceHas used anLLM tosummarizeresearchpapersHas learneda newlanguage inthe last yearCanrecommenda good AI ortech relatedpodcastIs optimisticabout thefuture ofhuman-AIcollaborationHasparticipated ina hackathonfocused on AIor LLMsIs currentlyworking on aprojectinvolving cross-lingual transferlearningKnows atleast threeprogramminglanguagesIs interestedin the ethicalimplicationsof generativeAIHasattended anICMLconferencebeforeHascontributedto an open-source AIprojectIs familiarwith theconcept ofpromptengineeringCan namethreedifferent LLMarchitecturesHas apreferred AIresearch toolthey canrecommend

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