Is familiarwith theconcept ofpromptengineeringIs excitedabout thepotential ofLLMs ineducationHas apreferred AIresearch toolthey canrecommendHas used agenerative AImodel tocreate art ormusicHassuccessfullydebugged acomplexLLMHas presenteda paper onnaturallanguagegenerationCan explain thedifferencebetween causaland maskedlanguagemodelsCan namethreedifferent LLMarchitecturesHasexperiencewith fine-tuning a pre-trained LLMHas used anLLM tosummarizeresearchpapersIs currentlyworking on aprojectinvolving cross-lingual transferlearningHascontributedto an open-source AIprojectIs optimisticabout thefuture ofhuman-AIcollaborationKnows atleast threeprogramminglanguagesIs interestedin the ethicalimplicationsof generativeAIHaspublishedresearch onmultilingualLLMsHas used agenerative AImodel for anon-academicpurposeCanrecommenda good AI ortech relatedpodcastHas traveledinternationallyto attend thisconferenceHasattended anICMLconferencebeforeHas experiencewith low-resourcelanguages inNLPHasparticipated ina hackathonfocused on AIor LLMsHas collaboratedon a researchpaper withsomeone from adifferent continentHas learneda newlanguage inthe last yearIs familiarwith theconcept ofpromptengineeringIs excitedabout thepotential ofLLMs ineducationHas apreferred AIresearch toolthey canrecommendHas used agenerative AImodel tocreate art ormusicHassuccessfullydebugged acomplexLLMHas presenteda paper onnaturallanguagegenerationCan explain thedifferencebetween causaland maskedlanguagemodelsCan namethreedifferent LLMarchitecturesHasexperiencewith fine-tuning a pre-trained LLMHas used anLLM tosummarizeresearchpapersIs currentlyworking on aprojectinvolving cross-lingual transferlearningHascontributedto an open-source AIprojectIs optimisticabout thefuture ofhuman-AIcollaborationKnows atleast threeprogramminglanguagesIs interestedin the ethicalimplicationsof generativeAIHaspublishedresearch onmultilingualLLMsHas used agenerative AImodel for anon-academicpurposeCanrecommenda good AI ortech relatedpodcastHas traveledinternationallyto attend thisconferenceHasattended anICMLconferencebeforeHas experiencewith low-resourcelanguages inNLPHasparticipated ina hackathonfocused on AIor LLMsHas collaboratedon a researchpaper withsomeone from adifferent continentHas 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. Is familiar with the concept of prompt engineering
  2. Is excited about the potential of LLMs in education
  3. Has a preferred AI research tool they can recommend
  4. Has used a generative AI model to create art or music
  5. Has successfully debugged a complex LLM
  6. Has presented a paper on natural language generation
  7. Can explain the difference between causal and masked language models
  8. Can name three different LLM architectures
  9. Has experience with fine-tuning a pre-trained LLM
  10. Has used an LLM to summarize research papers
  11. Is currently working on a project involving cross-lingual transfer learning
  12. Has contributed to an open-source AI project
  13. Is optimistic about the future of human-AI collaboration
  14. Knows at least three programming languages
  15. Is interested in the ethical implications of generative AI
  16. Has published research on multilingual LLMs
  17. Has used a generative AI model for a non-academic purpose
  18. Can recommend a good AI or tech related podcast
  19. Has traveled internationally to attend this conference
  20. Has attended an ICML conference before
  21. Has experience with low-resource languages in NLP
  22. Has participated in a hackathon focused on AI or LLMs
  23. Has collaborated on a research paper with someone from a different continent
  24. Has learned a new language in the last year