Adults, given pictures of abstract, made-up objects, and given that some of them are called “tufas,” can pick out which other pictures are tufas and which aren’t. We can do this much faster than a typical Bayesian estimator can, with less training data. This is partly because we have background knowledge about the world and what sort of categories and structures it forms.
I would submit that the real reason for this is because the judge for whether the human subject has appropriately learned the classifier rule is also a human, and therefore shares the same inductive biases! If a non-human, near-blank-slate intelligence were the judge, it would rule that the human learned slower than a Bayesian estimator.
I would submit that the real reason for this is because the judge for whether the human subject has appropriately learned the classifier rule is also a human, and therefore shares the same inductive biases! If a non-human, near-blank-slate intelligence were the judge, it would rule that the human learned slower than a Bayesian estimator.
Right—shared prior for “what sorts of concepts go with words”, effectively. (bias or no)