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Post-training is the best place to work in AI right now, because cheap runs mean a far higher share of your experiments can be all-or-nothing bets.

Drawn from what Nathan Lambert said

Subjectscaling laws
What this subject means

scaling laws Whether more compute keeps buying more capability, and where the curve now bends -- pre-training, post-training, test-time.

Interesting
A private bookmark. Not a position, and never counted.

What Nathan Lambert actually said

Word for word, with the source under each one. They did not write this page.

  1. Nathan Lambert

    Research scientist at the Allen Institute for AI

    This is why you want to work in post-training because the GPU cost for training is lower. So you can make a higher percentage of your training runs YOLO runs.

    Where this was said

    Watch from 0:49:00 plays here

    ↗DeepSeek, China, OpenAI, NVIDIA, xAI, TSMC, Stargate, and AI Megaclusters | Lex Fridman Podcast #459youtube.com

    video · 5h 06m · spoken · official transcript

    All 44 korrents from this recordingthis one is 3rd

Added to korrents 3 Feb 2025 · How quotes work · Something wrong? Tell us

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