The speaker proposes reinforcing successful AI research behavior by turning the experiment into a reinforcement-learning environment based on production data and training on that environment.

“method actually works and in some cases you'll be like whoa it found this like kick-ass method it like totally de-risked it totally worked and then you can then reinforce that by just like uh i mean one thing you could do would be like take that behavior convert convert the like experiment you just ran into a production rl environment um sorry into an rl environment based on production data and then train on that or you could potentially just literally take the rollouts that found that and then um do like some sort of uh”

“off policy rl or”

“you could do some like on policy rl with”

“different data but like yeah”