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Ravid Shwartz Ziv
@ziv_ravid
AI researcher | Meta | NYU. Working on compression, representation learning, and memory. I have an AI podcast!
Joined July 2020
3.8K Following    15K Followers
How Anthropic's new results post would read without the PR: Claude orchestrated open-source protein design models, PXDesign, RFdiffusion, Genie, BoltzGen, from a 30k-token expert prompt and 12,500 H100-hours of compute, and designed binders against 14 of 15 targets. Hit rates of 22–35% against a 10–15% baseline, where some of those tools already report similar numbers on their own. The orchestration is genuinely impressive. But the open-source models did most of the lifting, and they came from the Baker lab, Columbia, MIT, ByteDance Seed, and most of them were already wet-lab validated before Claude touched them. Which also sets the ceiling. All these generators share a single PDB-shaped training distribution, so calling four of them doesn't diversify away the blind spot, since they fail together. The targets that worked are the well-studied ones. So the valid claim is that an agent can now drive this stack competently in the regime where the stack already works. Instead, we got this announcement:
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