Comment by tulio_ribeiro
3 days ago
Supervised learning and reinforcement learning are mathematically distinct. Supervised pre-training as you said maximizes the likelihood of a token sequence. RL optimizes a policy against an external reward signal or execution environment. For example, RL evaluates code against runtime execution/unit tests/proof checkers (e.g lean). Models learn new strategies and are able to produce novel code if trained in an RL environment.
I don‘t understand what you mean. Supervised learning is reinforcement learning, while not all reinforcement learning is supervised learning (e.g unsupervised learning is also reinforcement learning; i.e. reinforcement learning with unlabelled data).
Like you said, you can have reinforcement learning which doesn’t use training data. But that is not what my parent said. What they said is: since RL is used heavily in the training. And since reinforcement learning is a broad category which includes supervised learning, nothing in their logic disproves the strawman they created from an AI skeptic.
that's not how the terminology is typical used, even if it makes literal sense