Hasexperiencewith fine-tuning a pre-trained LLMCanrecommenda good AI ortech relatedpodcastIs optimisticabout thefuture ofhuman-AIcollaborationCan namethreedifferent LLMarchitecturesHasattended anICMLconferencebeforeHas collaboratedon a researchpaper withsomeone from adifferent continentHas used agenerative AImodel tocreate art ormusicHaspublishedresearch onmultilingualLLMsIs familiarwith theconcept ofpromptengineeringHas apreferred AIresearch toolthey canrecommendKnows atleast threeprogramminglanguagesHas traveledinternationallyto attend thisconferenceHas experiencewith low-resourcelanguages inNLPIs excitedabout thepotential ofLLMs ineducationHassuccessfullydebugged acomplexLLMHasparticipated ina hackathonfocused on AIor LLMsHas learneda newlanguage inthe last yearHas used agenerative AImodel for anon-academicpurposeHas used anLLM tosummarizeresearchpapersHascontributedto an open-source AIprojectHas presenteda paper onnaturallanguagegenerationIs currentlyworking on aprojectinvolving cross-lingual transferlearningIs interestedin the ethicalimplicationsof generativeAICan explain thedifferencebetween causaland maskedlanguagemodelsHasexperiencewith fine-tuning a pre-trained LLMCanrecommenda good AI ortech relatedpodcastIs optimisticabout thefuture ofhuman-AIcollaborationCan namethreedifferent LLMarchitecturesHasattended anICMLconferencebeforeHas collaboratedon a researchpaper withsomeone from adifferent continentHas used agenerative AImodel tocreate art ormusicHaspublishedresearch onmultilingualLLMsIs familiarwith theconcept ofpromptengineeringHas apreferred AIresearch toolthey canrecommendKnows atleast threeprogramminglanguagesHas traveledinternationallyto attend thisconferenceHas experiencewith low-resourcelanguages inNLPIs excitedabout thepotential ofLLMs ineducationHassuccessfullydebugged acomplexLLMHasparticipated ina hackathonfocused on AIor LLMsHas learneda newlanguage inthe last yearHas used agenerative AImodel for anon-academicpurposeHas used anLLM tosummarizeresearchpapersHascontributedto an open-source AIprojectHas presenteda paper onnaturallanguagegenerationIs currentlyworking on aprojectinvolving cross-lingual transferlearningIs interestedin the ethicalimplicationsof generativeAICan explain thedifferencebetween causaland maskedlanguagemodels

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