Researcher Quits: “Gambling With Our Lives,” Altman Calls for Slowdown, and Labs Race
In a Nutshell
Former AI researcher Jacob Coxin resigned from Anthropic, citing reckless development of self-improving superintelligence, while Sam Altman pointed to OpenAI's Navier-Stokes breakthrough as evidence that AI progress must slow for safety. Data quality now drives 12x compute efficiency gains versus 3.7x from architecture, with labs racing to solve math grand challenges like Millennium Prizes at collapsing costs—$500K to $20 in two years. PDoom estimates range 10-20% among alignment leads, but most speakers reject slowdowns as impractical, arguing the real risks are economic displacement, compute sovereignty, and China-US AI competition, with alignment best achieved through capabilities advancement rather than halting progress.
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Jacob Coxin, a researcher who spent three years on pre-training at both OpenAI and Anthropic, resigned this week. Coxin stated that neither company is acting responsibly in the race toward self-improving super intelligence. He called the competition "gambling with our lives." The resignation received over 100 million views. Coxin's resignation came after less than three months at Anthropic, having joined in July.
Sam Altman cited the extraordinary achievement with Navier-Stokes as an argument for slowing down AI development. Altman stated: "I did not expect a result of this magnitude to happen so soon. We've been talking a lot about the need to pace progress to ensure safety. For me, this is the strongest evidence yet for that urgency." The statement reflects the rapid progress toward AGI, with Altman noting that "We're so deep in the singularity at this point. I can't think of a single solvable, verifiable thing that I could honestly say an AI can't solve in the next year."
The podcast features five panelists: Alex Weezner Gross (in-house ASI expert), Immad Wak (CEO of Intelligent Internet), Dave Blondon (AI investor), Salem Ismael (father of organizational singularity), and Peter D. Mandis (moderator). The episode covers 18 stories across five groupings, with the through line being that machines are starting to solve science and AI alignment is currently humanity's biggest concern.
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