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Articles 143
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I wrote a thing about this.
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Nearly half a year of silence. We spent it studying one problem: how far RL can scale.
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Just before joining Anthropic, @benkuhn wrote a great post about learning to think independently: ht
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So yes, after a very long time, the article I had been talking about that Im writing since March, is
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A coworker with whom I was discussing inferencing and showed interest that I wanna start learning it
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new post! I argue that current alignment techniques might soon become obsolete (as we scale RL), and
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My 1st simple attempt at an "intuitive RL" blog series. Principles catering to a specific reader (e.
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If you are starting to move past sft into rl-style post-training, these are two really good resource
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A fun small win for automated research:
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Guys and Girl nerds, the tiny 500m-1.2B models trained for a single task are taking off cause they a
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I think this is the craziest thing I've ever read.
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@human_named_gui: had to try this.
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A few days ago, Anthropic shared this brilliant prompt.
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Anyone can simulate the future. But the simulation only matters if it’s trustworthy.
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training and inference communication collectives can be very different (though they use the same col
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Continuous self-improvement needs an ever-expanding supply of training environments (goals).
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I’m mentoring again at MATS this winter. The way I select and supervise MATS fellows is very differe
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almost a year ago, me, @scriptosis and @harish20205 were sitting on a train reading the EAGLE-3 pape
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Weekend hack: Ejipura Flyover tracker 👇
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Experimenting with pi as a minimal app-specific AI interface
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Everyone needs to understand that China’s high-tech push began long before Made in China 2025.
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The clearest article about Anthropic’s work to prevent reward hacking in RL (Chinese): https://t.co/
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very high quality and detailed content if you want to learn how to post train llm!! https://t.co/9mD
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I didn’t used to have friends btw, had to learn how to meet people like this from first principles
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