The Ledger
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Krause: AI models cannot qualify new aerospace alloys without physical experiments
“A model can't figure out your way through the qualification pipeline for a new alloy for a jet turbine. You have to do experiments to do that”
Krause: Materials industry is constrained by experiments, not compute
“We're not compute constraint in the materials industry. We're experiment constraint.”
Krause: China will beat the US in R&D without automated self-driving labs
“That's how I think we can compete. That's the only way we can compete. I think if we want to move forward, if we do not do that, then they will continue to win because they will outpace us on cost and they will outpace us on people.”
Krause: Most AI models will be open source in five years
“We actually think in five years, most models will be open source.”
Krause: AI models are not a moat in science, experiments are
“However, we think in science, models aren't remote, experiments are.”
Krause: No AI model can one-shot materials for iPhones or Starship
“And this is what's so hard is there is no one model that can one shot a new material that ends up in your iPhone or that ends up on Starship.”
Krause: Physical synthesis and testing are the only ground truth in materials
“In materials, the ground truth is the material itself. You have to be able to make it, you have to be able to test it and characterize it, and then you have to really, at one point, be able to see if it can go into a real application if you're going to have it…”
Krause: Radical AI made 1,200 alloys in six months, with 300 novel
“We probably made 1200 alloys in the last five or six months. 300 of those alloys are new novel, never before seen in literature. And I'd say probably 10 of those alloys had performance that Has got us very excited on where they're going to be in the industry.”
Major instrument vendors previously refused to give Radical AI data access
“A few very big tool vendors were Not too excited about self-driving labs two years ago. They were not jumping to give us, even with payment, access to the software and pulling the data. That tone has now changed.”
DeepMind, Microsoft, and Meta are building or using physical science labs
“You see people like Google DeepMind, Microsoft, other places like Meta, either building their own lab or running experiments at someone else's lab to get that data back.”
Krause: Automated Labs Run Experiments, Self-Driving Labs Run Entire Campaigns
“There's a difference between an automated lab and a self-driving lab, right? An automated lab does experiments for you, automated, without humans, and that high throughput, and that, that can be very effective. A self-driving lab runs research campaigns for yo…”
Krause: Radical AI models explore previously unpublished alloy families
“And then we have a second overlay on that chart of where our AI scientist has gone. And it's moved into elemental families or alloy families. No one has ever published on before.”
Krause: Lab synthesis is not material discovery until deployed in products
“The second you synthesize it, milestone.
The second you characterize it, milestone.
That is not a new discovery.
We count a new discovery when you pick up your phone and there's a new material sitting inside of it.
That I think is a fair claim on new discovery…”
Krause: Large Alloy Manufacturers Are Bearish on AI for Science Hype
“We do talk to a lot of companies in our field who make materials at scale in, in the alloy space who are thinking about this, and they look at it from a different lens. You know, they're not all hype on AI for science, and actually I'd say a lot of them are ki…”
Krause: Autonomous Labs Require Deep Integration, Not Just Robotic Arms
“It's not about a robot in front of a tool. Go ahead, put a robotic arm in front of a tool and then watch what happens. Everything else I just talked about will come the second you do that. Now we feel so much farther ahead from the industry on really running s…”
Krause: Radical AI enables one PhD to run 10 simultaneous alloy campaigns
“We can have one PhD in metallurgy or alloys run 10 campaigns at a time. When I was in a PhD, we had 10 scientists focused on one campaign. One research problem at a time.”
Krause: Scientific tool makers should rebuild their stacks for robots
“Their tools are built for humans. They should build them for agents and robots.”
Krause: ML engineers in science should specialize instead of switching fields
“Bring the specialization and lean into your expertise. Don't shy away from it. Don't try to become a material scientist. Be an MLE that works in material science.”
Krause: Alloy performance is primarily determined by manufacturing and post-processing
“So much of what dictates the performance of those alloys is actually in processing. How do you manufacture it? What techniques are you using post processing and manufacturing that push performance or change performance?”
Krause: The real opportunity in materials AI is closed-loop manufacturing integration
“That is what we think the true opportunity is for AI and autonomy in materials is linking those two together in a fully closed loop system.”
Krause: Heavy industries have used the same alloys for 50 years
“And there has been, you know, for the past 50 years, the same alloys used in all these industries. And the reason why is these long discovery timelines we talked about.”
Krause: Commercial airplanes still use alloys from the 1950s to 1970s
“The alloys that are in the plane I flew here on, the 19 fifties, 19 sixties, 19 seventies, they might be coated with some CMZs from the late 19 nineties.”
Krause: Hafnium prices surged 10x to 15x due to Chinese supply dominance
“Hafnium, 10 to 15 X in price, because China owns a majority of the supply chain, things like refractories, tampium, niobium.”
Krause: Radical AI developed a hafnium-free alternative to C-103 aerospace alloy
“We've worked on that problem specifically, and we have successfully done that.”
Krause: New semiconductor interconnect materials could deliver 2x to 10x+ efficiency gains
“I think you could in, in the near future with some of the systems that have been recommended today, you would see like a two to five X generally, especially when you think about integration in these materials, you need barrier layers and there's all these inte…”
Krause: Novel alloys will reach defense and space systems in 3-5 years
“I would say something on the alloy side, like aerospace, we feel good opportunity three to five year timeline. Yeah, correct. I think it'll be an application, not like manned flight. Like, I don't think it'll be a jet turbine because of the constraints there w…”
Krause: Radical AI generates all candidate materials via AI
“For generation, all of our materials are generated by our AI scientists today.”
Krause: Understanding material microstructure does not guarantee manufacturability
“Just because you understand the microstructure, just because you see and can predict crack propagation does not mean you're necessarily going to perfectly nail manufacturing.”
Krause: Science will experience a foundation model breakthrough within 2-3 years
“I think we're going to have that for science over the next two to three years. I do. Once discoveries start coming out and this field continues to mature even more.”
Krause: Radical AI's Matrix VLM boosts scientific reasoning by 5-16%
“Now we have actually seen this, and you can go read the publication, it's on archive, where the public data set that we used actually is showing improvements, like five to 16%, I believe, on general scientific reasoning.”
Krause: Aerospace alloy qualification is typically a ten-year process
“Typically a ten-year process today, you have to make a number of different ingots of material and run these kind of standardized tests on them to prove your material is usable in those systems.”
Krause: Radical AI's Robots Autonomously Transfer Samples Across Lab Tools
“The same way a human scientist would come in, you know, look at the results, take the sample out and go to the next one. Our robots do that today.”
Krause: Radical AI Custom-Built a High-Throughput Alloy Synthesis Tool
“We custom build a tool with a third party to do alloy synthesis and high throughput. That, that's, Built to do alloys. That's not built to do ceramics or polymers or any other material system today.”
Krause: DARPA and GE Aerospace synthesized 500 alloys in 12 months
“The largest alloys program was the mock program. It was run by DARPA NGE Aerospace. They did 500 alloys in about 12 months. They did a bunch of kind of AI and simulations on the front end of that, and then they synthesized 500 new alloys in that whole year.”