Gus Stocker

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73 appearances 1 recordings 1 series first heard Mar 2026 last heard 20 Mar

Gus Stocker’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 Mar 2026 with 1.

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Future of Life Institute Podcast · What AI Companies Get Wrong About Curing Cancer (with Emilia Javorsky) · 20 Mar 2026 podcast

And so we don't have anything of comparable sort of complexity and size in terms of data sets when it comes to cancer.

We don't have anything like the database we use to solve protein folding.

Yeah, I think it's worth spending a little time on just the complexity of cancer.

It's almost misleading to talk about cancer as one disease, as you might tell us why that is.

So tell us about how complex cancer is, and perhaps tell us about elephants, naked mole rats, and bowhead whales.

And so you have the complexity of the biology itself, and then you have the complexity of the medical system that's trying to intervene on that biology.

So maybe tell us about what happened in South Korea with the thyroid screening program.

So what we're describing here is cancer as a massively complex problem.

I think one response here could be, well, if it's so complex, doesn't that strengthen the case for us needing superintelligence to solve it?

Isn't it the case then that we are not smart enough, we can't process enough data to actually sort of understand this problem and solve it?

There is- Before we get to the data, so there's sort of the limit case where what we would need to simulate is the entirety of the biology of a functioning human for one week.

What about simulating one cell?

What about simulating something much smaller or something that where we're making simplifications all over the place?

Isn't that an interesting project?

Isn't that a project that might give us something useful at least?

Yeah, and so if we can't solve or if AI cannot solve the problem of cancer by finding the first principles of biology, because those perhaps do not exist, then there's the alternative path of having enough data.

Now, we've discussed some problems with getting enough data, but do you want to say more about whether we will get there, when, how long it might take for us to have enough data to really begin to be able to model cancer?

And I guess our values also begin to intrude into this conversation about what health is just because there are various trade-offs you can make.

So for example, there's a trade-off between longevity and size, if I understand things correctly.

So if you become really bulky, if you become very muscular, maybe you don't live as long.

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