Hasattended anICMLconferencebeforeKnows atleast threeprogramminglanguagesCan explain thedifferencebetween causaland maskedlanguagemodelsIs optimisticabout thefuture ofhuman-AIcollaborationCan namethreedifferent LLMarchitecturesIs familiarwith theconcept ofpromptengineeringHas experiencewith low-resourcelanguages inNLPIs currentlyworking on aprojectinvolving cross-lingual transferlearningHas used agenerative AImodel for anon-academicpurposeIs excitedabout thepotential ofLLMs ineducationHas presenteda paper onnaturallanguagegenerationHas apreferred AIresearch toolthey canrecommendHascontributedto an open-source AIprojectHas learneda newlanguage inthe last yearHaspublishedresearch onmultilingualLLMsHassuccessfullydebugged acomplexLLMHas traveledinternationallyto attend thisconferenceHas collaboratedon a researchpaper withsomeone from adifferent continentIs interestedin the ethicalimplicationsof generativeAIHas used agenerative AImodel tocreate art ormusicHasexperiencewith fine-tuning a pre-trained LLMHas used anLLM tosummarizeresearchpapersHasparticipated ina hackathonfocused on AIor LLMsCanrecommenda good AI ortech relatedpodcastHasattended anICMLconferencebeforeKnows atleast threeprogramminglanguagesCan explain thedifferencebetween causaland maskedlanguagemodelsIs optimisticabout thefuture ofhuman-AIcollaborationCan namethreedifferent LLMarchitecturesIs familiarwith theconcept ofpromptengineeringHas experiencewith low-resourcelanguages inNLPIs currentlyworking on aprojectinvolving cross-lingual transferlearningHas used agenerative AImodel for anon-academicpurposeIs excitedabout thepotential ofLLMs ineducationHas presenteda paper onnaturallanguagegenerationHas apreferred AIresearch toolthey canrecommendHascontributedto an open-source AIprojectHas learneda newlanguage inthe last yearHaspublishedresearch onmultilingualLLMsHassuccessfullydebugged acomplexLLMHas traveledinternationallyto attend thisconferenceHas collaboratedon a researchpaper withsomeone from adifferent continentIs interestedin the ethicalimplicationsof generativeAIHas used agenerative AImodel tocreate art ormusicHasexperiencewith fine-tuning a pre-trained LLMHas used anLLM tosummarizeresearchpapersHasparticipated ina hackathonfocused on AIor LLMsCanrecommenda good AI ortech relatedpodcast

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