Canrecommenda good AI ortech relatedpodcastCan explain thedifferencebetween causaland maskedlanguagemodelsIs interestedin the ethicalimplicationsof generativeAIIs familiarwith theconcept ofpromptengineeringHaspublishedresearch onmultilingualLLMsHas traveledinternationallyto attend thisconferenceHassuccessfullydebugged acomplexLLMHas used agenerative AImodel for anon-academicpurposeHas learneda newlanguage inthe last yearIs currentlyworking on aprojectinvolving cross-lingual transferlearningHascontributedto an open-source AIprojectHas used agenerative AImodel tocreate art ormusicHas collaboratedon a researchpaper withsomeone from adifferent continentHas presenteda paper onnaturallanguagegenerationIs optimisticabout thefuture ofhuman-AIcollaborationHas used anLLM tosummarizeresearchpapersKnows atleast threeprogramminglanguagesHasattended anICMLconferencebeforeHas apreferred AIresearch toolthey canrecommendHas experiencewith low-resourcelanguages inNLPIs excitedabout thepotential ofLLMs ineducationHasexperiencewith fine-tuning a pre-trained LLMHasparticipated ina hackathonfocused on AIor LLMsCan namethreedifferent LLMarchitecturesCanrecommenda good AI ortech relatedpodcastCan explain thedifferencebetween causaland maskedlanguagemodelsIs interestedin the ethicalimplicationsof generativeAIIs familiarwith theconcept ofpromptengineeringHaspublishedresearch onmultilingualLLMsHas traveledinternationallyto attend thisconferenceHassuccessfullydebugged acomplexLLMHas used agenerative AImodel for anon-academicpurposeHas learneda newlanguage inthe last yearIs currentlyworking on aprojectinvolving cross-lingual transferlearningHascontributedto an open-source AIprojectHas used agenerative AImodel tocreate art ormusicHas collaboratedon a researchpaper withsomeone from adifferent continentHas presenteda paper onnaturallanguagegenerationIs optimisticabout thefuture ofhuman-AIcollaborationHas used anLLM tosummarizeresearchpapersKnows atleast threeprogramminglanguagesHasattended anICMLconferencebeforeHas apreferred AIresearch toolthey canrecommendHas experiencewith low-resourcelanguages inNLPIs excitedabout thepotential ofLLMs ineducationHasexperiencewith fine-tuning a pre-trained LLMHasparticipated ina hackathonfocused on AIor LLMsCan namethreedifferent LLMarchitectures

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