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Foundation Models for Materials Discovery: Our Investment in Orbital Materials
Fortunately, innovations in artificial intelligence have led to the emergence of foundation models, which are trained on vast amounts of data and leading to models that can be used across numerous applications. Those foundation models have the potential to enable inverse design, a method of material development that expedites the process by using the specific required properties as an input and generating the new material design as an output. This approach has the potential to revolutionize material development across industries, which is why we are excited to announce Toyota Ventures’ investment in Orbital Materials through our Frontier Fund.
The team has trained a 3D foundation model, named LINUS, for crystal structures and small molecules. Instead of screening millions of materials in hopes of finding one with a specific property, LINUS generates a material based on a given property in a single calculation. To do this, the team has developed a new version of the “transformer”, a model typically used for natural language processing, to allow the model to learn the relationships between the 3D structures of materials and their properties. Advanced materials that absorb and catalyze are crucial in various industries such as carbon capture, sustainable fuels, water treatments, biofeedstock upgrades, and battery recycling.
Covariant raises $75M for its AI-powered warehouse robots
Covariant, a startup developing warehouse robots that can be deployed faster than traditional automation hardware, has raised $75 million in funding. The company disclosed the investment today. The capital was provided as an extension to a Series C round that it had originally announced in 2021. Radical Ventures and Index Ventures co-led the new investment, while five other institutional backers contributed as well.