Dwarkesh Patel: uncertainty

Transcript context

…Has to be a machine that takes its input. Like first it takes an input argument, decides what it believes in light of it, which is kind of like saying was it compelling? But second, it needs to take 4 of those and then say here’s what I believe in light of all four, even though there’s a different estimation strategies that produce different numbers and that’s like a lot of our life is saying like well, here’s a simple thing that seems reasonable. And here’s a simple thing that seems reasonable. What are you doing? There’s supposed to be a simple thing that unifies them both. And the obstruction to getting that is understanding what happens when these principles are slightly intention and how do we deal? Yeah, that seems super interesting. We’ll see what other applications it has. I don’t know, like computer security and code checking. If you can actually say this is how safe we think a code is. In a very formal way, my guess is we’re not going to add I mean, this is both a blessing and a curse. It’s a curse. And you’re like, well, that’s sad. Your thing is not that useful, but a blessing and not useful things are easier. My guess is we’re not going to add that much value in most of these domains. Most of the difficulty comes from a lot of code that you’d want to verify. Not all of it, but a significant part. It’s just like the difficulty of formalizing the proof is like the hard part and actually getting all of that to go through and we’re not going to help even the tiniest bit with that, I think. So this would be more helpful if you have code that uses simulations, you want to verify some property of a controller that involves some numerical error or whatever you need to control the effects of that error. That’s where you start saying like, well, heuristically, if the errors are independent, blah, blah, blah.…

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