The AI startup Periodic Labs is in early discussions to raise hundreds of millions of dollars at a valuation of around $7 billion, as per Bloomberg. It is said to be a sharp leap from the $1.3 billion price tag it carried during its September seed round.
Earlier, the company secured $300 million from Andreessen Horowitz, Felicis, and Accel. The current talks are still evolving, and terms could shift.
A team built by AI insiders
Periodic Labs was founded in May 2025 in San Francisco by Liam Fedus, former vice president of research at OpenAI and a key architect of ChatGPT, alongside Ekin Dogus Cubuk, previously a research scientist at Google DeepMind.
Their mission is to leverage AI to analyse and design new materials, potentially enabling breakthroughs across sectors from energy storage to electronics. Fedus, who led the materials and chemistry team at both Google Brain and Google DeepMind, where he also founded the materials science research group.
The duo began exploring how generative AI could transform scientific discovery, envisioning a system that could integrate robotic arms for powder synthesis LLMs for reasoning and optimisation and machine learning models for rapid simulations.
Their end goal is to establish an AI lab that conducts experiments, analyses data, and improves results autonomously.
Building AI scientists for materials discovery
At its core, Periodic Labs is focused on materials science, a field that underpins industries from electronics to energy. The company’s ambition is to build AI “scientists” capable of designing experiments, alongside autonomous robotic laboratories that can execute them.
This approach also bridges a long-standing gap between research and application. By combining lab automation with AI-driven insight, Periodic Labs is not just exploring theoretical breakthroughs but pushing toward commercially viable outcomes.
What sets Periodic Labs apart is its early commercial traction. While many companies in this space remain in research mode, Periodic has already secured customers in the semiconductor industry, where the demand for new materials and faster discovery cycles is constant.
The rise of neolabs
Periodic Labs is part of a growing wave of companies often described as “neolabs”, startups combining AI models with physical experimentation. The idea is straightforward but powerful: instead of relying solely on human researchers, use AI systems to design, test, and iterate scientific experiments at speed.
In the broader AI frontier, AI researcher Richard Socher has explored funding for Recursive, a startup focused on building superintelligent, self-improving AI systems, at a $4 billion valuation. Meanwhile, Fei-Fei Li raised $1 billion for World Labs, focused on spatial intelligence and 3D world models, and Yann LeCun raised $1.03 billion for AMI Labs, which is building world models for reasoning and memory — each reflecting growing investor appetite for foundational AI bets beyond conventional large language models.
Together, neolabs like Periodic aim to shorten the time it takes to discover and refine new materials. Instead of years of trial and error, the process could move at a pace closer to software development.
The early interest from semiconductor companies suggests that this model is already resonating with industries where innovation cycles are both expensive and time-sensitive. And unlike many peers, the company is generating revenue.
