Gary Marcus: uncertainty

Transcript context

…So let's talk about the superhuman coder milestone and let's The what? The superhuman coder milestone, the automated encoding aspects, which is not all of AIR and D, but just part of it. I'm excited to try to drill down into that and for us to try to make bets or predictions of what the next few years are going to look like, basically. So from my perspective, it feels like you have often, over the last couple of years, been pointing to limitations of LLMs that were then, like, overcome in the next year or 2. Which, I mean, there are specific examples. Yes. Right? So So like, for example, any particular set well, chess hasn't been solved. Let me clarify what I mean by specific examples, I'll come back Which is I I give, you know, on Twitter, here here's a sentence where, you know, here's a prompt and it gets a weird answer. Those are always remedied. I was told, I don't know if it's true, that that people in OpenAI actually look on social media for example, including mine, and, you know, people patch them up. The specific examples in that sense, like literally this prompt gets this weird answer, a lot of them have been solved. These more abstract things like playing chess actually have not been solved. And the more abstract problem of can I give you a game with variations on the rules? I talked about that in rebooting AI in 2019 in the first chapter. That hasn't been solved. Are you then saying that, like, for all you know, 6 months from now, the AIs will be able to solve the the legal move in chess thing? Or are you saying you're…

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