Andrej Karpathy

here's webpages that look like the stuff that you have, but you could just directly go to answer and then have supporting evidence.

And these models, basically, they've read all the texts and they've read all the webpages.

And so sometimes when you see yourself going over the search results and sort of getting a sense of the average answer to whatever you're interested in, that just directly comes out.

You don't have to do that work.

So they're kind of like... Yeah, I think they have a way of distilling all that knowledge into...

like some level of insight, basically.

Yeah, exactly.

I think the way we are programming these computers now, like GPTs, is converging to how you program humans.

I mean, how do I program humans via prompt?

I go to people and I prompt them to do things.

I prompt them from information.

And so natural language prompt is how we program humans, and we're starting to program computers directly in that interface.

It's pretty remarkable, honestly.

Yeah.

So I had a blog post on Software 2.0, I think several years ago now.

And the reason I wrote that post is because I kind of saw something remarkable happening in

software development and how a lot of code was being transitioned to be written not in sort of like C++ and so on, but it's written in the weights of a neural net.

Basically just saying that neural nets are taking over software, the realm of software, and taking more and more tasks.

And at the time, I think not many people understood this deeply enough, that this is a big deal, this is a big transition.

Neural networks were seen as one of multiple classification algorithms you might use for your dataset problem on Kaggle.