this post was submitted on 28 Oct 2026
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There’s a difference between pre-training and reinforcement learning.
Pre-training is when the models are trained on scraped data. The models basically learn how to parrot the Internet. Usually they have a cutoff point to avoid training on slop.
Reinforcement learning is where most of the training is happening. They’re given tasks (for example, make a calculator app), and then judged by how well they complete the tasks. This is more resistant against model collapse because they’re not judged by how well they parrot slop.
As part of the reinforcement learning process they give the model access to tools like searching the internet so the newest programming language features can be accessed while the tasks are performed. This is where OpenAI is shifting to a cached version of the Internet the models can interact with instead.