Canrecommenda good AI ortech relatedpodcastHas learneda newlanguage inthe last yearIs familiarwith theconcept ofpromptengineeringIs excitedabout thepotential ofLLMs ineducationIs currentlyworking on aprojectinvolving cross-lingual transferlearningKnows atleast threeprogramminglanguagesHas used agenerative AImodel tocreate art ormusicHas used agenerative AImodel for anon-academicpurposeHas used anLLM tosummarizeresearchpapersHasattended anICMLconferencebeforeCan namethreedifferent LLMarchitecturesHasexperiencewith fine-tuning a pre-trained LLMHas presenteda paper onnaturallanguagegenerationHas collaboratedon a researchpaper withsomeone from adifferent continentIs optimisticabout thefuture ofhuman-AIcollaborationHas traveledinternationallyto attend thisconferenceCan explain thedifferencebetween causaland maskedlanguagemodelsHassuccessfullydebugged acomplexLLMHasparticipated ina hackathonfocused on AIor LLMsHas experiencewith low-resourcelanguages inNLPIs interestedin the ethicalimplicationsof generativeAIHascontributedto an open-source AIprojectHaspublishedresearch onmultilingualLLMsHas apreferred AIresearch toolthey canrecommendCanrecommenda good AI ortech relatedpodcastHas learneda newlanguage inthe last yearIs familiarwith theconcept ofpromptengineeringIs excitedabout thepotential ofLLMs ineducationIs currentlyworking on aprojectinvolving cross-lingual transferlearningKnows atleast threeprogramminglanguagesHas used agenerative AImodel tocreate art ormusicHas used agenerative AImodel for anon-academicpurposeHas used anLLM tosummarizeresearchpapersHasattended anICMLconferencebeforeCan namethreedifferent LLMarchitecturesHasexperiencewith fine-tuning a pre-trained LLMHas presenteda paper onnaturallanguagegenerationHas collaboratedon a researchpaper withsomeone from adifferent continentIs optimisticabout thefuture ofhuman-AIcollaborationHas traveledinternationallyto attend thisconferenceCan explain thedifferencebetween causaland maskedlanguagemodelsHassuccessfullydebugged acomplexLLMHasparticipated ina hackathonfocused on AIor LLMsHas experiencewith low-resourcelanguages inNLPIs interestedin the ethicalimplicationsof generativeAIHascontributedto an open-source AIprojectHaspublishedresearch onmultilingualLLMsHas apreferred AIresearch toolthey canrecommend

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