🔬 The Self-Driving Lab — Joseph Krause, Radical AI

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On the Science pod, we’ve been covering a lot of the ground on how AI is revolutionizing STEM, but one of our favorite off the record topics since our launch is which field is harder to accelerate: math, bio, or physics? Today we’re back in Materials Science land with Radical — Unlike biological molecules that can be represented (and predicted!) by token strings, the success of materials involve many more macro complex variables like supply chains, microstructures, and manufacturing processes. If you recall the LK99 drama of 2023, while the basic ingredients were known, part of the confusion came from the lack of disclosure around manufacturing, and therefore defeated reproducibility. There is probably no "one-shot" model capable of designing a material that works perfectly at scale.How Radical is accelerating materials discovery >10x the pace of DARPA/GE MACHJoseph Krause is a materials scientist through and through. And after spending his career watching industries stall out waiting for better materials, he founded Radical AI to do something about it.We recently sat down with Joseph to talk about Radical AI, materials discovery, self-driving labs, and the future of AI science. Joseph did not sugar coat anything: accelerating the materials discovery pipeline is a hard problem. But it’s one that he strongly believes we need to invest in, for the future of consumer products, aerospace, computing, and defense, and get them into every day use:“We count it as a discovery when you pick up your phone and there’s a new material sitting inside of it.”How does Joseph plan on accelerating the rate of discovery? To understand this, it’s important to understand why this is such a hard problem in the first place. The first thing to keep in mind is that the material that is manufactured is far more than a chemical formula going into it. The process of mixing, annealing, growing, or generating the final material can result in wildly different outcomes. The entire materials discovery process, both from early discovery to large s