Q as long as it achieves its end goal? I mean, you know, I think the argument is, um, you know, planes for air travel are prime example of just brute force. There's nothing that they do that's close to what a bird innately knows how to do, yet it works amazingly well, in fact, you know, much better than a bird. So does it, does it matter how it's done?
A It only depends, I mean, it matters depending on what your problem is. So, If your problem is a closed problem, like Go or chess, where the rules haven't changed, there's a limited number of options, then you can use brute force. I mean, you can either use the kind of brute force that, um, you know, Deep Blue used and just searched through a lot of positions, or there's a more nuanced version of, of brute force in AlphaGo, um, which combines Monte Carlo Tree Search, which is kind of classical AI technique, um, with Deep Learning to do the pattern recognition, um, but still uses an awful lot of data there, and so it's still, as you say, it's an extension. Um, of brute force. But it's an empirical question in each domain about whether that will get you far enough, and it mostly depends on how open-ended the problem is and how many outlier cases there are. So you already, I think, get into trouble with driving. So, you know, people thought that by now we would have driverless cars. If you go back to, like, 2012, um, I wrote a piece in The New Yorker, and I thought that it would, you know, they were legal in three states, and I wrote this thing about, um, what would happen if a school bus went out of control, and I thought, you know, um, You know, do you save the, the children in the school bus, or do you save yourself? I, I thought that, you know, by 2020 maybe we would have drive…
AI assessment note: “it matters depending on what your problem is.”