"For one, he said, robotic arms that could handle powder synthesis - the process of mixing and creating new materials - had recently proved themselves reliable. For another, machine learning simulations had become efficient and accurate enough to model complex physical systems such as those needed to develop new materials. And, third, LLMs now had powerful reasoning capabilities - in part through the work of Fedus and his team at OpenAI."
"Stitched together, the picture was clear: a simulation could theoretically discover new compounds, a robot could mix the materials, and an LLM could analyze the results and suggest course corrections. AI-automated material science was ready to be built. In fact, Cubuk was one of the researchers who published a groundbreaking paper in 2023 documenting a precursor Google research project. The team built a fully automated, robotic-powered lab and created 41 novel compounds "
Liam Fedus and Ekin Dogus Cubuk launched a startup with a $300 million seed round to build AI-driven materials discovery. The company originated from a seven-month-old conversation about combining recent advances. Robotic arms for powder synthesis achieved reliable performance. Machine learning simulations became efficient and accurate enough to model complex physical systems. Large language models developed stronger reasoning capabilities, enabling analysis and experimental guidance. The intended pipeline uses simulations to propose compounds, robots to synthesize materials, and LLMs to analyze results and suggest course corrections. Prior work demonstrated a fully automated robotic lab that produced 41 novel compounds.
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