DeepMind, in collaboration with Google, has developed a new deep learning tool called GNoME (Graph Networks for Materials Exploration) that has discovered 2.2 million new crystals, including 380,000 stable materials. These materials have the potential to power future technologies such as superconductors and next-generation batteries. GNoME uses artificial intelligence to predict the stability of materials, significantly increasing the speed and efficiency of discovery. The predictions made by GNoME have been independently validated by researchers globally. The research aims to accelerate materials discovery and drive down costs by leveraging AI. The findings have been published in Nature, and the predicted structures for the most stable materials have been shared with the research community.

DeepMind, in collaboration with Google, has developed a new deep learning tool called GNoME (Graph Networks for Materials Exploration) that has discovered 2.2 million new crystals, including 380,000 stable materials. These materials have the potential to power future technologies such as superconductors and next-generation batteries.

GNoME uses artificial intelligence to predict the stability of materials, significantly increasing the speed and efficiency of discovery. The predictions made by GNoME have been independently validated by researchers globally.

The research aims to accelerate materials discovery and drive down costs by leveraging AI. The findings have been published in Nature, and the predicted structures for the most stable materials have been shared with the research community.