What Nathan Lambert thinks about neural networks

@nathan-lambert · 55 positions · On ppll ↗

Machine-learning researcher on open language models; writes the Interconnects newsletter and the RLHF Book, after leading post-training at Ai2.

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Only Nathan Lambert on neural networks. See everyone on neural networks

1 dated position, 2025, in their own words. Our reading of what Nathan Lambert has said — not written or endorsed by them.

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1. 3 Feb 2025

   Our readingThe Bitter Lesson is misread as being about scale; it is about refusing to add human priors, because a clever specific fix always loses to a simple scalable one.

   Their wordsThe scale word gets a lot of attention in this. The interpretation that I use is effectively to avoid adding the human priors to your learning process. And if you read the original essay, this is what it talks about is how researchers will try to come up with clever solutions to their specific problem that might get them small gains in the short term while simply enabling these deep learning systems to work efficiently, and for these bigger problems in the long term might be more likely to scale and continue to drive success.

   ↗DeepSeek, China, OpenAI, NVIDIA, xAI, TSMC, Stargate, and AI Megaclusters | Lex Fridman Podcast #459youtube.com 2nd of 44 in this recording