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Periodic Labs Secures $300M Seed Round to Build Autonomous Labs

Swaraj Swaraj
|
Published on November 26, 2025
300M dolor seed round for Periodic Labs

With $300 million in seed capital secured, a team of former researchers from OpenAI and DeepMind is starting a company dedicated to automating scientific research. Periodic Labs hopes to establish AI laboratories that can autonomously design and execute experiments without immediate human supervision.

Andreessen Horowitz and Accel led the round, which also attracted interest from some well-known names in tech, including Nvidia, Elad Gil, Jeff Dean, Eric Schmidt, and, of course, Jeff Bezos. Given the size of this investment, confidence seems to be rising that AI will not just be a means for computer programs but also a means to speed up physical science investigation. Co-founders of Periodic Labs, with collective experience leading groups in artificial intelligence research, worked earlier leading materials and chemistry at Google Brain and DeepMind. 

Cubuk had AI systems discover more than 2 million new crystals. Before that, former OpenAI Research VP William Fedus led the projects for some of the largest neural networks ever built, including the development of ChatGPT. The startup now works on designing next-gen superconducting materials for use in energy-saving technologies, quantum computing, and advanced electronics. 

Periodic Labs

Machine-learning algorithms are expected to speed up the experimental process tremendously and churn out massive datasets that can be used to train further artificial intelligence applications when tied to automated lab platforms. According to the experts, the project stands as a metaphor for the wider trend of AI moving from pure algorithmic functioning to physical experiment. Periodic Labs is in its infancy, but it shows that the AI-experimental science nexus provides a rich developmental breeding ground. 

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The company plans to change the way research is done with its introduction of automation interfaced with state-of-the-art machine learning, and thus herald an era where it’s the artificial intelligence itself, not just another tool, doing the discovery. The scientific world will be keeping a close watch on all the attainments emerging from this ambitious approach, as the money begins to flow in and preliminary AI-driven studies start.

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