Nathan Lambert

Headlines · 2

1. 2d
   Trillium's Nathan Lambert says RSI hype oversells AI and distillation bans backfire

   In an a16z podcast conversation with partner Lisha Li, Trillium founder Nathan Lambert pushed back on industry hype around recursive self-improvement (RSI), arguing the truth sits between marketing and fear and that his real worry is frontier labs' own unhardened infrastructure. He frames model progress as a function of compute, data and talent, saying Chinese labs are not short on talent but are constrained by compute, which makes open-weight releases a pragmatic route to visibility and market access, citing Moonshot AI and Zhipu as examples. He also says existing public research does not convince him that distillation is the decisive factor behind fast followers, doubts that banning it would work and expects such moves to do more harm than good, while promising Trillium will publish its open SFT and mid-training stack, task sets and experiment trajectories so outsiders can verify what RSI can actually do.

   36氪 人工智能 · 🔥 0
2. 5d
   Trillium Labs pushes high-stakes AI research into the open

   Trillium Labs, a nonprofit co-founded by Nathan Lambert and Tom Zick, aims to move high-stakes AI research — on topics such as self-improvement, agents and model behavior — out of closed frontier labs by sharing experimental details so outside researchers can inspect and reproduce results. Lambert argues that leading systems, especially models from OpenAI and Anthropic, are typically available only through apps or APIs, leaving outsiders unable to understand how they are built or how they actually behave, and that long-term enclosure by a few labs weakens the community's ability to evaluate new ideas and propose alternatives. On the same day, Geoffrey Hinton and other leading AI researchers published a paper warning of a possible 'intelligence explosion' and calling on policymakers to require standardized disclosure by AI companies; Trillium Labs researchers had also worked with Meta, the University of Washington and MIT on a Context Language Models architecture.

   科技新报 · 🔥 0

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