"The nonprofit biomedical research institute Biohub, co-founded by Mark Zuckerberg and his wife, announced a partnership with the U.S. government, Google DeepMind, Isomorphic Labs, and Meta to build an open dataset for AI biology research, with a total scale of approximately $1.8 billion. Check out the breakdown: 1) Meta, Google DeepMind, and Isomorphic Labs are collectively contributing around $300 million; 2) The U.S. Department of Energy will invest over $500 million in the next five years; 3) NIH (National Institutes of Health) will coordinate the use of previously funded federal data assets, involving over $500 million in historical investments; 4) Biohub already committed $500 million back in April this year. Why this matters: One of the biggest bottlenecks in AI drug development has always been the lack of high-quality experimental data. While current large models can process massive amounts of text and structured data, the real biological world—cell states, gene expression, protein changes, drug reactions, and dynamic data under different experimental conditions—is still far from sufficient. This collaboration aims to leverage automated experiments, measurements, and model training to create higher-quality datasets. It represents a potential long-term opportunity: the core bottleneck of AI drug research may gradually shift from model computational power to verifiable experimental data and automated experimental capabilities. This also ties perfectly with what Freda Duan discussed earlier: AI is turning failed experiments into valuable training data, and wet labs are transitioning from "making drugs" to "making data." DNA synthesis, protein production, and CROs (Contract Research Organizations) might become the first beneficiaries—the "shovel sellers" of this new era. #AI #Biotech #DrugDiscovery #Biohub #Meta #GoogleDeepMind #IsomorphicLabs #NIH #Innovation #DataScience