What we are getting wrong about AI regulation

The Retort AI Podcast

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.com

Some 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-weights

00:00 Intro
01:19 Training Data and the Media
03:43 Norms, Power, and the Limits of Regulation
08:52 OpenAI's Business Model
12:33 Antitrust: The Essential Tool for Governing AI
17:11 Users as Afterthoughts
20:07 Depoliticizing AI
26:14 "Breaking Bad" & the AI Parallel
28:11 The "Little Tech" Agenda
31:03 Reframing the Narrative of Big Tech
32:20 "The Lean Startup" & AI's Uncertainty