The problem is that we need to pair generative models with verification systems. We have the models, but no verification yet. Fortunately code and math are easier to verify. Some things require simulation. In other cases you can substitute an ensemble of solutions & picking the most frequent answer as consistency based verification. But for each domain we need to create verifiers and that will take some time.

The good thing is that we'll be able to generate training data with our models by filtering the junk with the verifiers. Then we can retrain the models. It's important because we are getting to the limit of available training data. We need to generate more data, but it's worthless unless we verify it. If we succeed we can train GPT-5. Human data will be just 1%, the race is on to generate the master dataset of the future. I read in a recent paper that such a method was used to improve text captions in the LAION dataset. https://laion.ai/blog/laion-5b/