Andrej Karpathy: belief

Transcript context

…To the extent you’re willing to say, what is the thing you hope will be released this year or next year? I’m building the first course. I want to have a really, really good course, the obvious state-of-the-art destination you go to to learn, AI in this case. That’s just what I’m familiar with, so it’s a really good first product to get to be really good at it. So that’s what I’m building. Nanochat, which you briefly mentioned, is a capstone project of LLM101N, which is a class that I’m building. That’s a really big piece of it. But now I have to build out a lot of the intermediates, and then I have to hire a small team of TAs and so on and build the entire course. One more thing that I would say is that many times, when people think about education, they think more about what I would say is a softer component of diffusing knowledge. I have something very hard and technical in mind. In my mind, education is the very difficult technical process of building ramps to knowledge. In my mind, nanochat is a ramp to knowledge because it’s very simple. It’s the super simplified full-stack thing. If you give this artifact to someone and they look through it, they’re learning a ton of stuff. It’s giving you a lot of what I call eurekas per second, which is understanding per second. That’s what I want, lots of eurekas per second. So to me, this is a technical problem of how do we build these ramps to knowledge. So I almost think of Eureka as maybe not that different from some of the frontier labs or some of the work that’s going on there. I want to figure out how to build these ramps very efficiently so that people are never stuck and everything is always not too hard or not too trivial, and you have just the right material to progress. You’re imagining in the short term that instead of a tutor being able to probe your understanding, if you have enough self-awareness to be able to probe yourself, you’re never going to be stuck. You can find the right answer between talking to the TA or talking to an LLM and looking at the reference implementation. It sounds like automation or AI is not a significant part. So far, the big alpha here is your ability to explain AI codified in the source material of the class. That’s fundamentally what the course is.…

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