Gary Marcus拆解Anthropic的蛋白质设计宣传，告诉你Claude真实贡献和开源模型的作用。
Gary Marcus指出Anthropic最新宣传过度夸大Claude在蛋白质设计中的作用。Claude通过30k令牌专家提示和12,500 H100小时计算资源协调了PXDesign、RFdiffusion等开源模型，对15个目标中的14个设计了结合蛋白，命中率达22-35%，高于10-15%的基线。这些开源模型主要来自Baker实验室、哥伦比亚大学、MIT和字节跳动种子团队，多数已在湿实验室验证过。Marcus强调这些模型共享单一PDB形状的训练分布，无法通过组合消除盲点，且成功的目标都是已被充分研究的。
I am so tired of the PR.
I am so tired of the PR. Ravid Shwartz Ziv @ziv_ravid 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: 🔗 View Quoted Tweet 💬 2 🔄 1 ❤️ 16 👀 2155 📊 3 ⚡