If you omit the training data points where the baseball hits the ground, what will a machine learning model predict?
You can train a classical ML model on the known orbits of the planets in the past, but it can presumably never predict orbits given unseen n-body gravity events like another dense mass moving through the solar system because of classical insufficiency to model quantum problems, for example.
Church-Turing-Deutsch doesn't say there could not exist a Classical / Quantum correspondence; but a classical model on a classical computer cannot be sufficient for quantum-hard problems. (e.g. Quantum Discord says that there are entanglement and non-entanglement nonlocal relations in the data.)
Regardless of whether they sufficiently generalize,
[LLMs, ML Models, and AutoMLs] don't yet Critically Think and it's dangerous to take action without critical thought.
You can train a classical ML model on the known orbits of the planets in the past, but it can presumably never predict orbits given unseen n-body gravity events like another dense mass moving through the solar system because of classical insufficiency to model quantum problems, for example.
Church-Turing-Deutsch doesn't say there could not exist a Classical / Quantum correspondence; but a classical model on a classical computer cannot be sufficient for quantum-hard problems. (e.g. Quantum Discord says that there are entanglement and non-entanglement nonlocal relations in the data.)
Regardless of whether they sufficiently generalize, [LLMs, ML Models, and AutoMLs] don't yet Critically Think and it's dangerous to take action without critical thought.
Critical Thinking; Logic, Rationality: https://en.wikipedia.org/wiki/Critical_thinking#Logic_and_ra...