Mark Zuckerberg's Biohub has partnered with the U.S. government, Google, and Meta to build open data for AI models of biology, bringing total commitments to $1.8 billion.
In a statement released Wednesday, Biohub said that the initiative brings together the Department of Energy (DOE), the National Institutes of Health (NIH), Google DeepMind, Isomorphic Labs, and Meta to develop the technologies and datasets needed to build predictive models of life.
The organizations are collectively committing $1.8 billion in funding, data, computing resources, and new measurement technologies, according to the statement.
Specifically, DOE is set to invest more than $500 million over five years, while NIH will coordinate the contribution of relevant datasets and knowledge bases developed through over $500 million in prior federal investment, according to the statement.
Google DeepMind, Isomorphic Labs, and Meta are collectively investing in $300 million in the initiative to "create the technologies and multi-modal datasets needed to build predictive models of life," the statement said.
Biological AI
The initiative is designed to build and deliver the foundational measurements to train AI models for the global scientific community to predict and answer biological questions digitally, according to the statement. That would accelerate the path to "new ways of preventing and treating diseases," the project said.
"The result will be an open resource for the research community that provides the foundation for greater understanding and ultimately treatment of human diseases," Biohub said.
Biohub - a philanthropic venture founded by Meta CEO Mark Zuckerberg and his wife, Priscilla Chan - launched its five-year "Virtual Biology Initiative" in April. It aims to galvanize a global effort to create the technologies and multi-modal datasets needed to build predictive models of life.
Biohub has committed $500 million to anchor the work. It said $400 million would support large-scale data generation and the development of technologies for measuring, imaging, and engineering biology. The remaining $100 million will fund research conducted outside Biohub.
"An accurate predictive model of biology could dramatically accelerate scientific discovery by enabling scientists to perform experiments digitally," said Biohub Head of Science Alex Rives.
"Because of this potential, the creation of a virtual cell is one of the most important challenges for the next era of science," Rives added.