Why You Can't Opt Out of the AI Guardrails Race

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**Austin Campbell** (0:37)
So I think one interesting point about the AI adoption thing is I wonder how much of this is going to start happening because they will be pulled along by consumers. And I say that specifically, Ram, because you raised health care.
I know tons of people who are now taking things their doctors say to them or like conditions that they have and putting it into AI and trying to get a first cut, not just from the perspective of like, hey, AI diagnose me. But before I go to a doctor, I want to understand more of what's going on here and have a vastly more informed conversation with the doctor than I would otherwise have. I think there has also been a lot of testing of doctor's claims in ways that maybe we're not there in the past. And, you know, essentially my doctor thinks this, but let me put it into AI, let me shop for a second doctor if I don't like it or don't think they're right. So I'm wondering, and I don't have an answer to this, if that behavior is already observable in the healthcare space or if we're too early in the AI adoption curve to really see the impact here. But to me, there is a possibility industries will be forced to start adopting things. Because part of what I'm seeing in healthcare in particular, and as you can tell from my hair, was a mathematician by training originally.
So if nobody was paying attention during the World Cup, apparently Anthropics Claude Fable 5 solved the Jacobian conjecture, which is for non-mathematicians, we're going to make this real simple. It's a roughly 90-year-old problem in algebraic geometry. It was proposed by Keller. And it basically was talking about how spaces behave. And what Claude was able to do was provide a counter example to the conjecture. Like it actually came up with a specific, knowable, computable counter example to the conjecture, saying this cannot possibly be true in general, because here I found a specific time where it's not true.
And that is a huge result. This is one of the 25 most important problems hanging out there unsolved in mathematics right now. How long until we're seeing that with the quality of these models with regard to like healthcare? Ram, you know, good example.
If I got cancer right now, I'm probably going to try to get it sequence to go slam it into one of these things and be like, okay, what do I do about this? Like, we may already be very close. And so I guess I'm asking the question of what is the pull function to increase the rate of adoption here?

**Ram Ahluwalia** (3:23)
Well, a doctor is using AI now for diagnostics. Doctors can get the skill level of like house now, right? So it has powerful diagnostics capabilities. So I think that that's there, but we still have so much more to go. Like the promise is still ahead of reality. Even now with the latest models, there's still opportunities for these models to improve.
The Jacobean conjecture, it's a great accomplishment for math, but what real world impact does it have? Real world impact is, we found a way to target this cancer, or here's a way you design a fusion reactor that produces that energy, or here's a way you keep your telomerase longer for aging. We still haven't seen that kind of impact, which is actually what matters in the world.

**Austin Campbell** (4:11)
I mean, have we not found some of those impacts? Now I'm shooting from the hip here, but haven't we had various results in health care already found by AI?

**Chris Perkins** (4:22)
There's some incredible protein folding. What's the consequence?

**Ram Ahluwalia** (4:28)
We've had novel stories, the guy with Australia and his dog, there's another guy who diagnosed something with his daughter. There's some novel stories that are emerging, and they have some nice local impacts, but we still have more to do.

**Chris Perkins** (4:44)
Oh, there's tons more to do, but I think the acceleration is profound. I mean, across the board, every single discipline is being impacted.