Is currentlyworking on aprojectinvolving cross-lingual transferlearningHas used anLLM tosummarizeresearchpapersHas used agenerative AImodel tocreate art ormusicKnows atleast threeprogramminglanguagesHas collaboratedon a researchpaper withsomeone from adifferent continentCan explain thedifferencebetween causaland maskedlanguagemodelsHascontributedto an open-source AIprojectHas used agenerative AImodel for anon-academicpurposeHassuccessfullydebugged acomplexLLMHasattended anICMLconferencebeforeCanrecommenda good AI ortech relatedpodcastIs excitedabout thepotential ofLLMs ineducationHas presenteda paper onnaturallanguagegenerationHasexperiencewith fine-tuning a pre-trained LLMHas experiencewith low-resourcelanguages inNLPHas traveledinternationallyto attend thisconferenceCan namethreedifferent LLMarchitecturesHaspublishedresearch onmultilingualLLMsIs optimisticabout thefuture ofhuman-AIcollaborationIs familiarwith theconcept ofpromptengineeringHas learneda newlanguage inthe last yearHasparticipated ina hackathonfocused on AIor LLMsHas apreferred AIresearch toolthey canrecommendIs interestedin the ethicalimplicationsof generativeAIIs currentlyworking on aprojectinvolving cross-lingual transferlearningHas used anLLM tosummarizeresearchpapersHas used agenerative AImodel tocreate art ormusicKnows atleast threeprogramminglanguagesHas collaboratedon a researchpaper withsomeone from adifferent continentCan explain thedifferencebetween causaland maskedlanguagemodelsHascontributedto an open-source AIprojectHas used agenerative AImodel for anon-academicpurposeHassuccessfullydebugged acomplexLLMHasattended anICMLconferencebeforeCanrecommenda good AI ortech relatedpodcastIs excitedabout thepotential ofLLMs ineducationHas presenteda paper onnaturallanguagegenerationHasexperiencewith fine-tuning a pre-trained LLMHas experiencewith low-resourcelanguages inNLPHas traveledinternationallyto attend thisconferenceCan namethreedifferent LLMarchitecturesHaspublishedresearch onmultilingualLLMsIs optimisticabout thefuture ofhuman-AIcollaborationIs familiarwith theconcept ofpromptengineeringHas learneda newlanguage inthe last yearHasparticipated ina hackathonfocused on AIor LLMsHas apreferred AIresearch toolthey canrecommendIs interestedin the ethicalimplicationsof generativeAI

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