Engineers have seen AI generate designs they initially would have dismissed as broken, only to discover the designs actually outperform anything humans came up with, forcing them to rethink their own intuitions.

59:34they look at the results. And then they're getting back to us and telling us, "Hey, very impressive. The AI model came up with a design that I would have never thought would be good. If you had shown me this design like this, I would have said, 'Hey, scrap this. This is not going to work.' But actually, those designs are better than anything we could come up with. And now

59:57I need to get to get back to the dashboard to understand why it is so much better. Right? So, I need to rethink my intuition because I didn't think it could be that good as a design. Right? So, you learn as well from these models. Again, because they explore this this much richer space, they go out of bound, they go beyond your intuition. You may not to what you're saying, I

60:15think. So, that's where it becomes super interesting because then something really clicks with engineers. They become very excited because they understand that they can also learn from the model. I didn't get it better. How can I learn from it because explored new physics or new phenomena that I was not aware of when I was only working with intuition, essentially. So, there's also that. Is it possible that even trying to reverse engineer the

60:37designs themselves from the AI which >> Yeah, learning Learning from the AI's advances and its occasional leapfrogs over us is definitely a really exciting, thrilling, slightly scary part of this new future. Could you give us a little bit more intuition for like how like just how radical these moments are? And maybe a little bit hard for somebody not in the domain to to really grock it, but

61:09I'd love to try, you know, to get a little bit better sense on kind of uh are they really good optimizations or are they really like stepping out and exploring different regions of the design space that people you know, cuz I think what made move 37 qualitatively so compelling was like no human would have made that move. Like initially, I think the live the live stream commentators like thought it was

61:34a blunder, right? Um when we see these surprises in engineering like how big of a surprise are they? Are we Are we seeing like oh, that's kind of interesting. I wonder if that could work or is it like that looks, you know, kind of crazy um but in defiance of all my intuitions, it it actually does work. Just like try to help me calibrate on how big those