reinforcement learning

“The scaling in post-chaining itself is not hitting the wall, and that's because Basically, we went from, like, raw data sets from pre-trained models to infinite amount of tasks that you can teach the model in the post-training world via reinforcement learning.…”

“Software is deterministic. When you write code and you hit run, either runs or it doesn't. And that is why that's the key insight Anthropic really had. They just went deep. And this is what they're doing. It's just reinforcement learning. I'm basically permuta…”

“Code has this whole automated feedback loop, right, where you can run the code, and that is the kind of automated feedback that really feeds into the RL, which makes these models so great at coding.”

“Reinforcement learning was really working and was going to be the next big paradigm shift in capabilities.”

“If you look at the scaling laws, they're continuing to hold true. We did kind of need this transition from like normal pre-training to reinforcement learning, scaling up to continue the scaling laws.”

“With the advent of agents and products that think and can act and reason, there's going to be this kind of new wave around RL, and I have a deep belief that that, that will become one of the most important product techniques, kind of the next season, or at lea…”

“It speaks to conversations I've had with a lot of researchers and executives at top labs, which is that it's highly likely that the entire economy will become an RL environment machine.”

“I think what we're going to see is a split between job functions that demand kind of mid IQ intelligence, and those will often be open weight, sort of biased with reinforcement learning, you know, things that make the models even cheaper, more performant for a…”