@andykonwinski: 3 take-aways from chatting w/ top AI researchers last month: - Evals are the “source code” of AI agents (48:35) - BigAI…
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Summary of three key takeaways from conversations with leading AI researchers at CAISconf, covering the importance of evaluations for AI agents, the trade-offs between industry and academia, and a novel pedagogical RL approach.
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Cached at: 06/26/26, 04:12 PM
3 take-aways from chatting w/ top AI researchers last month:
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Evals are the “source code” of AI agents (48:35)
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BigAI labs: $ + anonymous impact. Academia -> impact w/ your own individual voice (44:00)
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Pedagogical RL: agent solves problem it knows the answer to (unintuitive!); reward solutions that don’t take shortcuts, then distill them into a student model. (53:40)
Laude Institute (@LaudeInstitute): At @CAISconf last month, @andykonwinski sat down with researchers on the conference floor – @matei_zaharia @istoica05 @lateinteraction @dawnsongtweets @gneubig @pgasawa @JonSaadFalcon @heathercmiller @ryanmart3n @alexgshaw @profjoeyg @swyx and Ioannis Ioannidis – to talk
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