AlphaFold未能解决蛋白质折叠问题
Why AlphaFold Didn't Solve Protein Folding: The Bitter Lesson of Biology, Virtual Cells, & Curing Al...
DeepMind科学家谈AlphaFold局限，蛋白质语言模型隐藏知识，虚拟细胞如何加速药物研发
Google DeepMind的Pushmeet Salcandido解释AlphaFold突破未能解决蛋白质动力学问题。蛋白质语言模型包含关于结构、功能和进化的隐藏知识。仅扩展AI计算和数据不足以理解生物学。更好的生物数据和虚拟细胞可能解锁下一波突破，实现10-100倍更快的药物发现。
Why AlphaFold Didn't Solve Protein Folding: The Bitter Lesson of Biology, Virtual Cells, & Curing Al...
Why AlphaFold Didn't Solve Protein Folding: The Bitter Lesson of Biology, Virtual Cells, & Curing All Disease latent.space/p/biohub-deepm… @GoogleDeepMind ’s @pushmeet and @biohub ’s @salcandido explain why AlphaFold's breakthrough hasn't solved protein dynamics, why scaling AI compute and data alone isn't enough to understand biology, how protein language models contain hidden knowledge about structure, function, and evolution, why future frontier models may understand other AI systems better than humans, how better biological data and virtual cells could unlock the next wave of breakthroughs, and what it will take to achieve 10–100x faster drug discovery on the path to curing all disease. Your browser does not support the video tag. 🔗 View on Twitter 💬 1 🔄 2 ❤️ 6 👀 470 📊 3 ⚡
