Former OpenAI and DeepMind researchers raise whopping $300M seed to automate science, marking one of the largest early-stage funding rounds in AI research. The new startup, Periodic Labs, aims to transform how scientific discoveries are made—using AI-powered labs where robots can run experiments, gather data, and accelerate breakthroughs.
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A $300M Bet On AI Scientists
Periodic Labs emerged from stealth with a massive $300 million seed round. Backers include some of the biggest names in tech and venture capital—Andreessen Horowitz, Nvidia, Accel, DST, Elad Gil, Jeff Dean, Eric Schmidt, and Jeff Bezos.
The funding reflects growing belief that AI-driven automation can revolutionize scientific discovery, especially in fields like materials science and chemistry.
The Founders: From OpenAI And DeepMind To Automating Science
Periodic Labs was co-founded by Ekin Dogus Cubuk and Liam Fedus, two renowned AI researchers.
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Cubuk previously led the materials and chemistry team at Google Brain and DeepMind. He co-created GNoME, an AI system that discovered over 2 million new crystals in 2023—potentially paving the way for future tech breakthroughs.
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Fedus, a former VP of Research at OpenAI, played a key role in building ChatGPT and led the team that developed the world’s first trillion-parameter neural network.
Their small but elite team includes alumni from OpenAI, Google, Microsoft, and other leading AI research labs.
Automating Scientific Discovery With AI Labs
Periodic Labs’ mission is bold: to automate science itself. Instead of humans running every experiment, the company is building AI scientists that can:
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Conduct experiments through robotic labs
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Gather and analyze real-world data
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Iterate on hypotheses at scale
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Continuously improve discovery processes
By combining large language models with robotics and lab automation, Periodic Labs hopes to accelerate discoveries in superconductors, materials science, and beyond.
First Mission: Reinventing Superconductors
The startup’s initial focus is on superconductors—materials that could unlock faster, more efficient energy systems. Current superconductors require extremely low temperatures, but the team hopes to discover new compounds that perform better and consume less energy.
If successful, this could fuel advances in electronics, clean energy, and even quantum computing.
Beyond Superconductors: Building A Scientific Data Engine
Beyond inventing new materials, Periodic Labs plans to create a massive database of real-world experimental data. This dataset—generated by AI scientists running countless experiments—could become one of the most valuable resources for future discoveries.
As the company explains:
“Until now, scientific AI advances have come from models trained on the internet. At Periodic, we are building AI scientists and autonomous laboratories for them to operate.”
This $300M investment signals a major shift in how tech leaders see the future of science. Instead of relying on human researchers alone, the next era of discovery could be driven by AI scientists working around the clock, producing breakthroughs at unprecedented speed.
With Periodic Labs leading the charge, the line between artificial intelligence and human innovation is about to blur even further.
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