Periodic Labs
7 statements across 1 episodes · 4 bullish · 1 bearish · 1 people on the record · first statement Nov 6, 2025 by Doge Chubuk · said 15 times in 2 episodes since 2025 · across every show →
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brought up most by Shayle Kann (15)
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2026 3 mentions in 1 episode
2025 12 mentions in 1 episode
Everything said about Periodic Labs, oldest first
Nov 6, 2025 positive
Chubuk: Superconductivity moonshot will yield independently valuable automated lab capabilities
“To discover a exciting superconductor, we probably have to develop so many capabilities on the way there that's By themselves very useful. For example, automated synthesis, automated characterization, being able to model or predict high temperature superconduc…”
Nov 6, 2025 positive
Nov 6, 2025 neutral
Nov 6, 2025 negative
Chubuk: AI cannot reason to breakthrough superconductors from training data alone
“I think it's still true that it would be difficult to just reason your way into a much better superconductor. I actually would guess that there's a law out there that we haven't discovered yet that says that you can't just look at your training set that's diff…”
Nov 6, 2025 neutral
Chubuk: GPU compute and training costs drove Periodic Labs' $300M seed
“We are going to train LLMs, we are going to use GPUs to run simulations, so that does end up being a large part of the cost. Yeah, it's funny, like, before, you know, if you asked me this question 10 years ago, I would have thought that the biggest part of the…”
Nov 6, 2025 bullish
Chubuk: Periodic Labs aims to achieve automated materials characterization soon
“I think one thing that isn't as advanced right now, but we feel like we can do pretty soon, is automated characterization itself. So, you mix powders, you put it in the, some characterization tool, you get the result out, What is the actual output? I think tha…”
Nov 6, 2025 positive
Chubuk: Minimal physical experiments carry huge information value by validating synthetic simulations
“What's interesting about scientific data is it's not just a few bits or numbers, right? Like, for example, there are certain experiments you can run where the result you get from it is just, say, three floating point numbers. But the implications of those coul…”