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