Periodic Labs

Is that part of what you want? I think a lot of it and even the lab part

of it, like for instance, like we have a company that is not biology in the hard science part called periodic labs.

We keep talking about these AI models that they can do amazing things.

But you know, one thing that we found out is that when it comes to the physical world, one of the things that is missing is how do you even test if this works? Let's say that the AI model came up with a new element, like we have a new superconductor or we have a new chip material, like you can do things a hundred times cheaper, like how much of an impact it would have? Great.

But I'm struggling to see how you can get $100 billion of spend in a domain like this just because... very quickly you're not in a situation where you're like we have a shortage of ideas it's like we have a shortage of capital that we can put and and point at these different experiments does that make sense

yeah so one thing that i think we can sort of point to is there's there's two domains right when you think about science right there's discovery and there's engineering and everyone always talks about the discovery side of things but actually the bulk of the spend is on the engineering side of things and you have to get really good at the engineering before you can discover something and bring it to market When you look at, for example, Periodic Labs, they are a company that's specifically focused in this realm.

Most of their work is on engineering, increasing the engineering velocity.

of these materials.

Very few companies are in there.

I mean, we have companies like Periodic Labs.

They're doing something insanely difficult.

They basically said, look, a lot of AI is focused on experiments and data, but there is one area that we do not have data and has never been captured, which is physical experiments.

although there are many companies that are getting in that direction, and I'm very excited about that as a direction.

More generally, one that comes to mind is Periodic Labs.

I've got a ton of respect for what they're doing.

They're literally giving Claude Code a run semiconductor experiment tool.

So adding like a place in the physical world that they could test out some of their ideas.

And then of course there are these great companies like Periodic Labs that have robots working to kind of revolutionize material science.

If you think about it, reservoir is kind of the same thing, but for ag tech, like you're building, the real world laboratory for AI systems being able to interact with the real world and to really help farmers and grow food.

Yeah, I think there are a lot of similarities.

Musk and Zuckerberg talk extensively in public about the need for America to invest in developing small modular nuclear reactors as a result.

Periodic Labs claims to have discovered a new superconducting material while Isomorphic Labs doses a patient for the first time.

Oregon becomes the second state to run a pilot program for AI to renew prescriptions.

Heading.

It's up to you, of course, but I will try to focus on six elements you might not have caught from the viral release video and announcement.

So is it all a distraction, though, from physical science breakthroughs like those promised by Periodic Labs, or the coding supremacy of Claude 4.5 Sonnet? Depends who you ask, but let's get started.

First, a quick one, one detail that many may have missed.

There are actually two Sora 2s.

So everything has to get wrapped up into that vision.

But Sora 2 seems more like a side quest that might add XP, but isn't directly on course.

Much more on course for me would be something like Periodic Labs.

I mentioned in my last video how exploration and experimentation is one of the last big blockers toward a singularity, if you will.

Thanks.

Liam and Doge are the co-founders of a company called Periodic Labs.

How many people here are aware of Periodic Labs? The kids are paying attention.

Let's just start with between when, so you were part of the, you helped set up the post-training team at OpenAI and you were there for the ChatGPT moment, which arguably you and the team there kind of helped shape that continuous post-training loop.

And then Doge on your side, you had worked on Genome over at DeepMind.

A control can make a wrong answer easier to act on.

Periodic Labs has a less familiar version of the same problem.

Researchers synthesize a material, then use X-ray diffraction to learn what they made.

The patterns can be noisy.