Jerry Tworek, OpenAI VP of Research, discusses how reinforcement learning changes the baseline operation of modern AI models beyond simple next-token prediction.
Opinion
Tworek: GPT-5 can effectively be considered an iteration like 'o3.1'
“Like GPT-Five in some way I can be considered as like, oh, 3.1. It's a little bit of like, you know, iteration of like the same thing and the same concept”
Disclosure
Tworek: OpenAI team was initially underwhelmed by pre-trained GPT-4
“When we trained GPT-IV, we were pretty underwhelmed internally, and then there was a lot of moments, oh, we trained this small, we spent a lot of money on it, and it's kind of like, you know, pretty dumb, at least, like, you know, we have GPT-IV, GPT-III alrea…”
Prediction Not checkable as stated
Tworek: Traditional human data labeling is becoming obsolete as models advance
“I think, like, in a way, I think it's getting more and more to be a thing of the past as the models are getting smarter and smarter. This is becoming less of a thing, but I think a few years back, and especially in GPT-IV days, this was the thing.”
Opinion
Tworek: OpenAI's o1 was mostly a tech demo for solving puzzles
“O-one like, to be perfectly honest, it was really mostly good at solving puzzles and like maybe a few kind of thinking problems here and there, but it wasn't like, it wasn't a very useful model. It was almost more like a technology demonstration.”
Assertion Not checkable as stated
Tworek: Coding agents are the first successful agentic AI products
“Like, coding agents are at the moment the first, like, pretty successful agentic products built on top of AI.”
Opinion
Tworek: The landmark 2012 ImageNet AI results were not that significant
“From my perspective, and again, this is just how my brain works, that the 20 12 ImageNet results, like, weren't that significant.”