Former OpenAI and DeepMind researchers raise whopping $300M seed to automate science | TechCrunch
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Former OpenAI and DeepMind researchers raise whopping $300M seed to automate science | TechCrunch
"Periodic Labs came out of stealth on Tuesday with a war chest of $300 million as a seed round, backed by a tech industry's who's who: Andreessen Horowitz, DST, Nvidia, Accel, Elad Gil, Jeff Dean, Eric Schmidt, and Jeff Bezos. Periodic Labs was founded by Ekin Dogus Cubuk and Liam Fedus. Cubuk led the materials and chemistry team at Google Brain and DeepMind, where one of his projects was, for instance, an AI tool called GNoME."
"That tool discovered over 2 million new crystals in 2023, materials that could one day be used to power new generations of technology, researchers say. Fedus is a former VP of Research at OpenAI, and one of the researchers who helped create ChatGPT. He also led the team that created the first trillion-parameter neural network. Its small team is likewise filled with researchers who have worked on other major AI and materials science projects who have worked on other major AI and materials science projects."
"The goal of Periodic Labs is nothing less than to automate scientific discovery, creating AI scientists, the company says. This means building labs where robots conduct physical experiments, collect data, iterate, and try again, learning and improving as they go. The lab's first goal is to invent new superconductors that it hopes perform better and possibly require less energy than existing superconducting materials."
Periodic Labs launched with a $300 million seed round from leading tech investors and was founded by Ekin Dogus Cubuk and Liam Fedus. Cubuk brings materials and chemistry leadership from Google Brain and DeepMind, including work on an AI tool called GNoME that discovered over two million crystals. Fedus brings deep generative-model expertise from OpenAI, including work on ChatGPT and trillion-parameter models. A small, experienced research team aims to create AI scientists that run robotic labs to perform physical experiments, collect and curate real-world data, iterate autonomously, and prioritize discovering new materials, starting with superconductors.
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