Has used agenerative AImodel for anon-academicpurposeHassuccessfullydebugged acomplexLLMHasparticipated ina hackathonfocused on AIor LLMsIs interestedin the ethicalimplicationsof generativeAIIs currentlyworking on aprojectinvolving cross-lingual transferlearningCanrecommenda good AI ortech relatedpodcastIs familiarwith theconcept ofpromptengineeringHas experiencewith low-resourcelanguages inNLPHas presenteda paper onnaturallanguagegenerationCan namethreedifferent LLMarchitecturesHasexperiencewith fine-tuning a pre-trained LLMHaspublishedresearch onmultilingualLLMsIs optimisticabout thefuture ofhuman-AIcollaborationHas collaboratedon a researchpaper withsomeone from adifferent continentHas used anLLM tosummarizeresearchpapersHasattended anICMLconferencebeforeCan explain thedifferencebetween causaland maskedlanguagemodelsHascontributedto an open-source AIprojectHas used agenerative AImodel tocreate art ormusicHas apreferred AIresearch toolthey canrecommendHas traveledinternationallyto attend thisconferenceIs excitedabout thepotential ofLLMs ineducationKnows atleast threeprogramminglanguagesHas learneda newlanguage inthe last yearHas used agenerative AImodel for anon-academicpurposeHassuccessfullydebugged acomplexLLMHasparticipated ina hackathonfocused on AIor LLMsIs interestedin the ethicalimplicationsof generativeAIIs currentlyworking on aprojectinvolving cross-lingual transferlearningCanrecommenda good AI ortech relatedpodcastIs familiarwith theconcept ofpromptengineeringHas experiencewith low-resourcelanguages inNLPHas presenteda paper onnaturallanguagegenerationCan namethreedifferent LLMarchitecturesHasexperiencewith fine-tuning a pre-trained LLMHaspublishedresearch onmultilingualLLMsIs optimisticabout thefuture ofhuman-AIcollaborationHas collaboratedon a researchpaper withsomeone from adifferent continentHas used anLLM tosummarizeresearchpapersHasattended anICMLconferencebeforeCan explain thedifferencebetween causaland maskedlanguagemodelsHascontributedto an open-source AIprojectHas used agenerative AImodel tocreate art ormusicHas apreferred AIresearch toolthey canrecommendHas traveledinternationallyto attend thisconferenceIs excitedabout thepotential ofLLMs ineducationKnows atleast threeprogramminglanguagesHas learneda newlanguage inthe last year

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