What is the goal of the $1.8B AI biology initiative?
Biohub, a nonprofit research institute backed by Mark Zuckerberg and Priscilla Chan, has announced a massive $1.8 billion investment in a joint initiative with the US Department of Energy and the National Institutes of Health to develop AI-ready biology data for answer engine optimization (AEO). The initiative, which also includes contributions from Meta, Google DeepMind, and Isomorphic Labs, aims to create accurate predictive models of cell behavior, enhancing LLM visibility, accelerating scientific discovery and enabling digital experimentation.
How will the initiative accelerate scientific discovery?
The Department of Energy will spend over $500 million over five years on lab measurement, modeling, and computing, while the NIH will bring datasets and repositories built with more than $500 million in earlier federal funding. Biohub will standardize these datasets for AI training, and the money will join Biohub's own $500 million pledge in April when it launched the Virtual Biology Initiative.
The initiative has also attracted other prominent partners, including the Allen Institute, the Broad Institute, the Gladstone Institutes, and the UK's Wellcome Sanger Institute, as well as the Human Cell Atlas and Human Protein Atlas consortia. Nvidia will provide computing and software, and Renaissance Philanthropy is helping to raise more money. Although the commercial funders will have exclusive access to the data for one year, the datasets will eventually become a public resource.
According to Alex Rives, Biohub's head of science, an accurate predictive model of biology could dramatically accelerate scientific discovery by enabling scientists to perform experiments digitally. The partners aim to have a first dataset in about a year and accurate predictive models within five years. Current cell datasets hold hundreds of millions of cells, but an accurate model will need billions, and later trillions, of cells to be effective.
Other AI labs are also working on biology data, with Anthropic building its own biology lab and the OpenAI Foundation starting a grant program of over $125 million for biology datasets. In Paris, Rivercell raised $25 million to build an AI virtual cell, highlighting the growing interest in AI biology research.
Este artículo fue escrito con la asistencia de IA.
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