Has used anLLM in alanguageother thanenglishHas learneda newlanguage inthe last yearHasparticipated ina hackathonfocused on AIor LLMsIs excitedabout thepotential ofLLMs ineducationCan explain thedifferencebetween causaland maskedlanguagemodelsHas apreferred AIresearch toolthey canrecommendHas used anLLM tosummarizeresearchpapersCanrecommenda good AI ortech relatedpodcastIs familiarwith theconcept ofpromptengineeringHas collaboratedon a researchpaper withsomeone from adifferent continentHasattended anICMLconferencebeforeHascontributedto an open-source AIprojectIs interestedin the ethicalimplicationsof generativeAIHas used agenerative AImodel tocreate art ormusicHas experiencewith low-resourcelanguages inNLPHasexperiencewith fine-tuning a pre-trained LLMCan namethreedifferent LLMarchitecturesHassuccessfullydebugged acomplexLLMHas traveledinternationallyto attend thisconferenceHas used agenerative AImodel for anon-academicpurposeIs optimisticabout thefuture ofhuman-AIcollaborationHas presenteda paper onnaturallanguagegenerationKnows atleast threeprogramminglanguagesHaspublishedresearch onmultilingualLLMsHas used anLLM in alanguageother thanenglishHas learneda newlanguage inthe last yearHasparticipated ina hackathonfocused on AIor LLMsIs excitedabout thepotential ofLLMs ineducationCan explain thedifferencebetween causaland maskedlanguagemodelsHas apreferred AIresearch toolthey canrecommendHas used anLLM tosummarizeresearchpapersCanrecommenda good AI ortech relatedpodcastIs familiarwith theconcept ofpromptengineeringHas collaboratedon a researchpaper withsomeone from adifferent continentHasattended anICMLconferencebeforeHascontributedto an open-source AIprojectIs interestedin the ethicalimplicationsof generativeAIHas used agenerative AImodel tocreate art ormusicHas experiencewith low-resourcelanguages inNLPHasexperiencewith fine-tuning a pre-trained LLMCan namethreedifferent LLMarchitecturesHassuccessfullydebugged acomplexLLMHas traveledinternationallyto attend thisconferenceHas used agenerative AImodel for anon-academicpurposeIs optimisticabout thefuture ofhuman-AIcollaborationHas presenteda paper onnaturallanguagegenerationKnows atleast threeprogramminglanguagesHaspublishedresearch onmultilingualLLMs

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.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
  1. Has used an LLM in a language other than english
  2. Has learned a new language in the last year
  3. Has participated in a hackathon focused on AI or LLMs
  4. Is excited about the potential of LLMs in education
  5. Can explain the difference between causal and masked language models
  6. Has a preferred AI research tool they can recommend
  7. Has used an LLM to summarize research papers
  8. Can recommend a good AI or tech related podcast
  9. Is familiar with the concept of prompt engineering
  10. Has collaborated on a research paper with someone from a different continent
  11. Has attended an ICML conference before
  12. Has contributed to an open-source AI project
  13. Is interested in the ethical implications of generative AI
  14. Has used a generative AI model to create art or music
  15. Has experience with low-resource languages in NLP
  16. Has experience with fine-tuning a pre-trained LLM
  17. Can name three different LLM architectures
  18. Has successfully debugged a complex LLM
  19. Has traveled internationally to attend this conference
  20. Has used a generative AI model for a non-academic purpose
  21. Is optimistic about the future of human-AI collaboration
  22. Has presented a paper on natural language generation
  23. Knows at least three programming languages
  24. Has published research on multilingual LLMs