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Open data for predictive AI models of biology: $1.8 billion committed
Hraness wrote this summary from a saved copy of the source. Quotations are taken word for word from the source.
gist
Biohub, the Department of Energy, NIH, Google DeepMind, Isomorphic Labs, and Meta announce $1.8 billion in funding, data, compute, and measurement technology to expand the Virtual Biology Initiative. The goal is an open, AI-ready biological data resource for training predictive models of cells, which Biohub frames as the foundation for a virtual cell.
ideas
- Who pays. DOE commits over $500 million over five years through its Genesis Mission, NIH coordinates datasets built from over $500 million in prior federal investment, and Google DeepMind, Isomorphic Labs, and Meta add $300 million.
- Biohub’s anchor. Its founding $500 million funds cryo-electron tomography, large-scale live-tissue microscopy, and engineering tools, plus $100 million for outside research.
- The virtual cell goal. Partners want models that predict how any cell responds to an intervention, so experiments can be run digitally first.
- Shared data layer. Biohub will build common standards, identifiers, and a single access point, building on Tabula Sapiens, OpenCell, and CELLxGENE.
- A wide coalition. The Allen, Broad, and Gladstone institutes, the Human Cell Atlas, Sanger, NVIDIA, and Renaissance Philanthropy also join.
quotes
“the largest coordinated commitment to generating AI-ready biological data to date”
“the creation of a virtual cell is one of the most important challenges for the next era of science”
“We will not solve this challenge without open, experimental biological data at an unprecedented scale”