In 2008, Robert Stadler had this really amazing series of posts explaining the hidden probability-theoretic structure of language and cognition. Essentially, explaining _natural language as an AI capability_. What your brain is doing when you [see a tiger and say, "Yikes! A tiger!"](https://www.lesswrong.com/posts/dMCFk2n2ur8n62hqB/feel-the-meaning) is governed the [simple math](https://www.lesswrong.com/posts/HnPEpu5eQWkbyAJCT/the-simple-math-of-everything) by which intelligent systems make observations, use those observations to assign category-membership, and use category-membership to make predictions about properties which have not yet been observed. _Words_, language, are an information-theoretically efficient _code_ for such systems to share cognitive content.
-And these posts hammered home the point over and over and over and _over_ again—culminating in [the 37-part grand moral](https://www.lesswrong.com/posts/FaJaCgqBKphrDzDSj/37-ways-that-words-can-be-wrong)—that word and category definitions are _not_ arbitrary, because there are optimality criteria that make some definitions _perform better_ than others as "cognitive technology"—
+And these posts hammered home the point over and over and over and _over_ again—culminating in [the 37-part grand moral](https://www.lesswrong.com/posts/FaJaCgqBKphrDzDSj/37-ways-that-words-can-be-wrong)—
+
+
-[...]
You see the problem. If "You can't define a word any way you want" is a good philosophy lesson, it should be a good philosophy lesson _independently_ of the particular word in question and _independently_ of the current year. If we've _learned something new_ about the philosophy of language in the last ten years, that's _really interesting_ and I want to know what it is!