Can namethreedifferent LLMarchitecturesHas presenteda paper onnaturallanguagegenerationHascontributedto an open-source AIprojectHas collaboratedon a researchpaper withsomeone from adifferent continentIs interestedin the ethicalimplicationsof generativeAIHasattended anICMLconferencebeforeHaspublishedresearch onmultilingualLLMsHasexperiencewith fine-tuning a pre-trained LLMHas learneda newlanguage inthe last yearHassuccessfullydebugged acomplexLLMHas apreferred AIresearch toolthey canrecommendIs optimisticabout thefuture ofhuman-AIcollaborationCanrecommenda good AI ortech relatedpodcastIs currentlyworking on aprojectinvolving cross-lingual transferlearningIs familiarwith theconcept ofpromptengineeringKnows atleast threeprogramminglanguagesHas traveledinternationallyto attend thisconferenceHas used agenerative AImodel for anon-academicpurposeHasparticipated ina hackathonfocused on AIor LLMsCan explain thedifferencebetween causaland maskedlanguagemodelsHas used anLLM tosummarizeresearchpapersHas used agenerative AImodel tocreate art ormusicIs excitedabout thepotential ofLLMs ineducationHas experiencewith low-resourcelanguages inNLPCan namethreedifferent LLMarchitecturesHas presenteda paper onnaturallanguagegenerationHascontributedto an open-source AIprojectHas collaboratedon a researchpaper withsomeone from adifferent continentIs interestedin the ethicalimplicationsof generativeAIHasattended anICMLconferencebeforeHaspublishedresearch onmultilingualLLMsHasexperiencewith fine-tuning a pre-trained LLMHas learneda newlanguage inthe last yearHassuccessfullydebugged acomplexLLMHas apreferred AIresearch toolthey canrecommendIs optimisticabout thefuture ofhuman-AIcollaborationCanrecommenda good AI ortech relatedpodcastIs currentlyworking on aprojectinvolving cross-lingual transferlearningIs familiarwith theconcept ofpromptengineeringKnows atleast threeprogramminglanguagesHas traveledinternationallyto attend thisconferenceHas used agenerative AImodel for anon-academicpurposeHasparticipated ina hackathonfocused on AIor LLMsCan explain thedifferencebetween causaland maskedlanguagemodelsHas used anLLM tosummarizeresearchpapersHas used agenerative AImodel tocreate art ormusicIs excitedabout thepotential ofLLMs ineducationHas experiencewith low-resourcelanguages inNLP

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