The race to find new materials with AI needs more data. Meta is giving massive amounts away for free.

"We're really firm believers that by contributing to the community and building upon open-source data models, the whole community moves further, faster," says Larry Zitnick, the lead researcher for the OMat project. Zitnick says the newOMat24 model will top the Matbench Discovery leaderboard, which ranks the best machine-learning models for materials science. Its data set will also be one of the biggest available. "Materials science is having a machine-learning revolution," says Shyue Ping Ong, a professor of nanoengineering at the University of California, San Diego, who was not involved in the project. Previously, scientists were limited to doing very accurate calculations of material properties on very small systems or doing less accurate calculations on very big systems, says Ong.