Hasparticipated ina hackathonfocused on AIor LLMsHas used agenerative AImodel tocreate art ormusicIs familiarwith theconcept ofpromptengineeringHas learneda newlanguage inthe last yearHasexperiencewith fine-tuning a pre-trained LLMHas apreferred AIresearch toolthey canrecommendKnows atleast threeprogramminglanguagesHaspublishedresearch onmultilingualLLMsHas used agenerative AImodel for anon-academicpurposeCan namethreedifferent LLMarchitecturesCanrecommenda good AI ortech relatedpodcastHassuccessfullydebugged acomplexLLMIs optimisticabout thefuture ofhuman-AIcollaborationHas collaboratedon a researchpaper withsomeone from adifferent continentIs interestedin the ethicalimplicationsof generativeAIHas traveledinternationallyto attend thisconferenceIs excitedabout thepotential ofLLMs ineducationHas experiencewith low-resourcelanguages inNLPCan explain thedifferencebetween causaland maskedlanguagemodelsHascontributedto an open-source AIprojectHas used anLLM tosummarizeresearchpapersIs currentlyworking on aprojectinvolving cross-lingual transferlearningHasattended anICMLconferencebeforeHas presenteda paper onnaturallanguagegenerationHasparticipated ina hackathonfocused on AIor LLMsHas used agenerative AImodel tocreate art ormusicIs familiarwith theconcept ofpromptengineeringHas learneda newlanguage inthe last yearHasexperiencewith fine-tuning a pre-trained LLMHas apreferred AIresearch toolthey canrecommendKnows atleast threeprogramminglanguagesHaspublishedresearch onmultilingualLLMsHas used agenerative AImodel for anon-academicpurposeCan namethreedifferent LLMarchitecturesCanrecommenda good AI ortech relatedpodcastHassuccessfullydebugged acomplexLLMIs optimisticabout thefuture ofhuman-AIcollaborationHas collaboratedon a researchpaper withsomeone from adifferent continentIs interestedin the ethicalimplicationsof generativeAIHas traveledinternationallyto attend thisconferenceIs excitedabout thepotential ofLLMs ineducationHas experiencewith low-resourcelanguages inNLPCan explain thedifferencebetween causaland maskedlanguagemodelsHascontributedto an open-source AIprojectHas used anLLM tosummarizeresearchpapersIs currentlyworking on aprojectinvolving cross-lingual transferlearningHasattended anICMLconferencebeforeHas presenteda paper onnaturallanguagegeneration

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