Is familiarwith theconcept ofpromptengineeringCanrecommenda good AI ortech relatedpodcastCan explain thedifferencebetween causaland maskedlanguagemodelsHas traveledinternationallyto attend thisconferenceCan namethreedifferent LLMarchitecturesHas used anLLM in alanguageother thanenglishHas learneda newlanguage inthe last yearHascontributedto an open-source AIprojectIs optimisticabout thefuture ofhuman-AIcollaborationHassuccessfullydebugged acomplexLLMHasparticipated ina hackathonfocused on AIor LLMsHas collaboratedon a researchpaper withsomeone from adifferent continentKnows atleast threeprogramminglanguagesHas used agenerative AImodel for anon-academicpurposeHaspublishedresearch onmultilingualLLMsHasexperiencewith fine-tuning a pre-trained LLMHas used agenerative AImodel tocreate art ormusicIs excitedabout thepotential ofLLMs ineducationHas presenteda paper onnaturallanguagegenerationHas apreferred AIresearch toolthey canrecommendHas experiencewith low-resourcelanguages inNLPHasattended anICMLconferencebeforeHas used anLLM tosummarizeresearchpapersIs interestedin the ethicalimplicationsof generativeAIIs familiarwith theconcept ofpromptengineeringCanrecommenda good AI ortech relatedpodcastCan explain thedifferencebetween causaland maskedlanguagemodelsHas traveledinternationallyto attend thisconferenceCan namethreedifferent LLMarchitecturesHas used anLLM in alanguageother thanenglishHas learneda newlanguage inthe last yearHascontributedto an open-source AIprojectIs optimisticabout thefuture ofhuman-AIcollaborationHassuccessfullydebugged acomplexLLMHasparticipated ina hackathonfocused on AIor LLMsHas collaboratedon a researchpaper withsomeone from adifferent continentKnows atleast threeprogramminglanguagesHas used agenerative AImodel for anon-academicpurposeHaspublishedresearch onmultilingualLLMsHasexperiencewith fine-tuning a pre-trained LLMHas used agenerative AImodel tocreate art ormusicIs excitedabout thepotential ofLLMs ineducationHas presenteda paper onnaturallanguagegenerationHas apreferred AIresearch toolthey canrecommendHas experiencewith low-resourcelanguages inNLPHasattended anICMLconferencebeforeHas used anLLM tosummarizeresearchpapersIs interestedin the ethicalimplicationsof generativeAI

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