What we are getting wrong about AI regulation
The Retort AI Podcast - A podcast by Thomas Krendl Gilbert and Nathan Lambert
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Tom and Nate catch up on the rapidly evolving (and political) space of AI regulation. We cover CA SB 1047, recent policing of data scraping, presidential appointees, antitrust intention vs. implementation, FLOP thresholds, and everything else touching the future of large ML models.Nate's internet cut out, so this episode ends a little abruptly. Reach out with any questions to mail at retortai.comSome links:- night falls on the cumberlands https://en.wikipedia.org/wiki/Night_Comes_to_the_Cumberlands- hillbilly elegy https://en.wikipedia.org/wiki/Hillbilly_Elegy- wired piece on data https://www.wired.com/story/youtube-training-data-apple-nvidia-anthropic/- nate's recent piece on AI regulation https://www.interconnects.ai/p/sb-1047-and-open-weights00:00 Intro 01:19 Training Data and the Media 03:43 Norms, Power, and the Limits of Regulation08:52 OpenAI's Business Model12:33 Antitrust: The Essential Tool for Governing AI17:11 Users as Afterthoughts20:07 Depoliticizing AI 26:14 "Breaking Bad" & the AI Parallel28:11 The "Little Tech" Agenda31:03 Reframing the Narrative of Big Tech 32:20 "The Lean Startup" & AI's Uncertainty