Is familiarwith theconcept ofpromptengineeringHas traveledinternationallyto attend thisconferenceHas used anLLM tosummarizeresearchpapersHasparticipated ina hackathonfocused on AIor LLMsHas used agenerative AImodel for anon-academicpurposeIs interestedin the ethicalimplicationsof generativeAIIs optimisticabout thefuture ofhuman-AIcollaborationHasexperiencewith fine-tuning a pre-trained LLMHassuccessfullydebugged acomplexLLMHas learneda newlanguage inthe last yearCanrecommenda good AI ortech relatedpodcastHasattended anICMLconferencebeforeIs excitedabout thepotential ofLLMs ineducationHas presenteda paper onnaturallanguagegenerationHas experiencewith low-resourcelanguages inNLPHascontributedto an open-source AIprojectHas apreferred AIresearch toolthey canrecommendCan explain thedifferencebetween causaland maskedlanguagemodelsHas used agenerative AImodel tocreate art ormusicIs currentlyworking on aprojectinvolving cross-lingual transferlearningKnows atleast threeprogramminglanguagesHaspublishedresearch onmultilingualLLMsCan namethreedifferent LLMarchitecturesHas collaboratedon a researchpaper withsomeone from adifferent continentIs familiarwith theconcept ofpromptengineeringHas traveledinternationallyto attend thisconferenceHas used anLLM tosummarizeresearchpapersHasparticipated ina hackathonfocused on AIor LLMsHas used agenerative AImodel for anon-academicpurposeIs interestedin the ethicalimplicationsof generativeAIIs optimisticabout thefuture ofhuman-AIcollaborationHasexperiencewith fine-tuning a pre-trained LLMHassuccessfullydebugged acomplexLLMHas learneda newlanguage inthe last yearCanrecommenda good AI ortech relatedpodcastHasattended anICMLconferencebeforeIs excitedabout thepotential ofLLMs ineducationHas presenteda paper onnaturallanguagegenerationHas experiencewith low-resourcelanguages inNLPHascontributedto an open-source AIprojectHas apreferred AIresearch toolthey canrecommendCan explain thedifferencebetween causaland maskedlanguagemodelsHas used agenerative AImodel tocreate art ormusicIs currentlyworking on aprojectinvolving cross-lingual transferlearningKnows atleast threeprogramminglanguagesHaspublishedresearch onmultilingualLLMsCan namethreedifferent LLMarchitecturesHas collaboratedon a researchpaper withsomeone from adifferent continent

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