The speaker says current reinforcement learning explores poorly, making a model very unlikely to receive a progress-enabling signal if it cannot find a useful result within 128 rollouts.

“yeah this just comes back to like the RL signal problem like RL is not very good at like exploring right now and so like if you if the model can't like get in like you know 128 rollout it's very unlikely to get signal to like progress and this is why like in RL we need like curricular whereas like in pre-training we don't because like it's that's not a problem for pre-training at all”