  Even at the height of Chomsky’s influence, it was clear that the strength of the Nativist position rested, to a great extent, on the weakness of the Empiricist alternative. The central argument from the Poverty of the Stimulus was that Empiricism had failed to make its case, and that the Nativist hypothesis was therefore more plausible. But it was implicit in this dialectic that if a more powerful Empiricist learning theory were developed, it could change the terms of the debate. Furthermore, Empiricists argued that there had to be a stronger general learning theory because learning theory as developed up until that time did not have the resources to account for much learning that was plainly based on experience (Harman 1967; Putnam 1967). Some would argue that these Empiricist hopes for a more powerful learning theory have been realized. Learning theory has advanced significantly, especially in the last decade, and Empiricism can now draw upon new resources; specifically, learning algorithms based on Bayes’ Theorem. The power of Bayesianism raises the possibility that the earlier Poverty of the Stimulus arguments underestimated what could be learned from experience by general learning mechanisms.