Isomorphic Labs

Um, and, and from everything I've heard, he's been kind of somewhat checked out for a while anyway.

So they started this Isomorphic Labs, which is basically to do like synthetic biology on the side that's like invested and owned by Google but isn't really part of Google.

And he kind of maybe cares more about that.

Um, yeah.

Yeah.

Isomorphic Labs.

So Balazs' former employer-

Yeah

... has funded Isomorphic Labs.

Yeah, yeah.

We gotta throw one in there.

So this sovereign, his daughter-in-law just happens to be in front.

One of the companies that they've invested in is a company called Isomorphic Labs, a drug discovery company founded by Nobel laureate Demis Abasis, using frontier AI to design and develop new medicines.

So there we have him talking about we need this database, and now his daughter-in-law is funding these companies.

The investment was announced in May 2026 as a part of a larger fundraise.

It is.

And you have isomorphic labs and Schrodinger showcasing absolutely incredible mind bending structural design ambitions.

It is impressive scale, undoubtedly.

But again, the guidebook warns us not to confuse input with output.

This is actually a paper, Jaderberg et al.

He's now running Isomorphic Labs.

But back in the, whatever this was, 2016 or '17 era, Jaderberg was working on could you do backprop without having to have weight, you know, perfect symmetry? Could you do a local version? I mean, if you could scale up something like that even, which doesn't really have neuroscience except at a very inspirational level, that somehow the brain does this and there must be some clever thing.

Even without connectomes and so on, I think just slightly shifting the priorities of research from passing ex- you know, next eval to what if we could do this in a local learning way, meta-learn to learn, et cetera.

What they say is he's stepping away from the day-to-day CEO position and moving into a chairmanship role.

but he's also keeping his chief scientist title at Alphabet and beginning to build our isomorphic labs, which is the AI of the real world, as it's fashioned.

So rather than saying, I'm out, we've done everything we need, I'm going to be a CEO somewhere else, he's actually saying something slightly different.

And Google's sort of said to him, I guess, what's your next challenge, Dennis? We'd like to help you with that.

Some of them have made more deliberate moves in the direction of life sciences than others.

Um, I mean, for that matter, Alphabet, Google's parent company, owns several drug companies, including Isomorphic Labs, which is one of the better generative chemistry companies.

What do you view your relationship or potential relationship with these organizations? Are they potential customers? Maybe they're existing customers.

You can blink twice if that's true.

Uh, you know, they, they've been innovators.

There are a number of other companies.

Isomorphic Labs is probably another one that has a lot of the upstream automated.

They like to talk about once you get to clinical development, uh, you're now just moving at the speed of traffic, right? That's a very human element.

Nobel Prize-winning AlphaFold was a big advance for understanding the building blocks of life, but it has yet to actually produce a new drug.

Isomorphic Labs, founded to build on AlphaFold, is expecting its first trials, originally planned for last year by the end of this year.

In February, the company wrote that true drug discovery will require highly accurate predictive models across an expansive range of biochemical properties and interactions.

Georgescu says the space needs a sanity check, that existing models do not have the data to capture the complexity of human biology.

When you put it like that, you can see why they are so optimistic.

And the success of that project spawned a whole new company, right? Isomorphic Labs.

Yes.

Isomorphic Labs aims to take the predictive power of AI that worked for proteins and apply it to the entire drug design process.

We're talking about using AI to design novel chemical compounds from scratch, predicting exactly how they will bind to a disease, and predicting their toxicity, all within a computer simulation.

Just bypassing the lab work?