Deep Q-Network

... on the screen, so the raw data, the raw visual input, and no other information, no privileged information about, you know, access to the i- the insides of the program about, you know, where the ball is or the speed of it and so on, which obviously the program knows.

But we didn't give the, uh, the DQN system, as it was called, our Atari system, any of that information.

It just got the 20,000 pixels on the screen.

And 20,000 pixels, I mean, it seems, uh, uh, t- you know, sort of trivial now, but back in 2010, that was inc- enormous amount of input data.

And that AI research was mostly around reinforcement learning.

And that's kind of like the old school deep reinforcement learning where you have all of these agents, you know, DQN, PPO, AlphaZero, et cetera.

It's not the reinforcement learning with human feedback that you're seeing right now in LLMs.

So definitely something that was happening before.