Andrew White

speaker

993 appearances 1 recordings 1 series first heard Jan 2026 last heard 28 Jan

Andrew White’s voice in public audio — every appearance, attributed to the second.

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Recordings per month over the last 12 months — 1 in all, peaking in Jan 2026 with 1.

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Latent Space: The AI Engineer Podcast · 🔬 Automating Science: World Models, Scientific Taste, Agent Loops — Andrew White · 28 Jan 2026 podcast

Or uh in in and you know, you want to know what the real modern dark arts are, the like AI resistant area of the world is like uh medicinal chemistry, that is like the spot.

Where like you know there's so much superstitious.

So much

Exactly.

And I remember this is uh talking to somebody who worked at a CRO and they're like, Oh, whenever like Company X orders anything, we never put boron on any of the compounds because they hate boron because there was one program that was killed because there was a boron on you know somewhere in the core and it led to some toxic side effects.

So no boron for this company.

This company, they like love things to be fluorinated or something because they love think it's great for um the admite properties, right?

And so there's like all this this this stuff where you read.

reach the point where you're at, I don't know, human bias level or human disagreement level.

And I think we're getting to that point in data analysis.

And so of course you will see then that if I take the broad data from a paper and I analyze it myself, I will get a different conclusion.

One of the cool tricks you can do is this back to this brute force thing, is that I can go to our agent and I can run it a hundred times and I can take the consensus like analysis.

Or I can say even if you make these three different choices in your data analysis, you get the same conclusion, right?

Or this conclusion is somehow s sensitive to those choices.

And then you can there's even like words, it's like epistemic versus aleatory uncertainty, right?

Is like this is aleatoric, which means like I think it's noise.

From the data, or this is epistemic uncertainty, which means like I think there's some choices that are being made, there's some model differences that lead to the disagreement.

Anyway, but there's like but there's like a Donald Rumsfeld formulation of this as well of like the known unknowns and yeah, it was it's aleatoric epistemic uh uh uh debate there.

How do you I would say first of all that fifty percent is actually pretty good because it's rare that experiments in the lab are actually coin tosses, right?

They're usually a lot more outcomes than you know than than binary.

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