This is a really interesting point; it seems related to the idea that to be an expert in something, you need a vocabulary close to the domain in question.
I'm not so sure about this. I am pretty good at understanding visual reality, and I have some words to describe various objects, but my vocabulary is nowhere near as rich as my understanding is (of course, I'm only claiming to be an average member of a race of fantastically powerful interpreters of visual reality).
Let me give you an example. Say you had two pictures of faces of two different people, but the people look alike and the pictures were taken under similar conditions. Now a blind person, who happens to be a Matlab hacker, asks you to explain how you know the pictures are of different people, presumably by making reference to the pixel statistics of certain image regions (which the blind person can verify with Matlab). Is your face recognition vocabulary up to this challenge?
I think "vocabulary" in this sense refers to the vocabulary of the bits doing the actual processing. Humans don't have access to the "vocabulary" of their fusiform gyruses, only the result of its computations.
In the early 1980s Douglas Lenat wrote EURISKO, a program Eliezer called "[maybe] the most sophisticated self-improving AI ever built". The program reportedly had some high-profile successes in various domains, like becoming world champion at a certain wargame or designing good integrated circuits.
Despite requests Lenat never released the source code. You can download an introductory paper: "Why AM and EURISKO appear to work" [PDF]. Honestly, reading it leaves a programmer still mystified about the internal workings of the AI: for example, what does the main loop look like? Researchers supposedly answered such questions in a more detailed publication, "EURISKO: A program that learns new heuristics and domain concepts." Artificial Intelligence (21): pp. 61-98. I couldn't find that paper available for download anywhere, and being in Russia I found it quite tricky to get a paper version. Maybe you Americans will have better luck with your local library? And to the best of my knowledge no one ever succeeded in (or even seriously tried) confirming Lenat's EURISKO results.
Today in 2009 this state of affairs looks laughable. A 30-year-old pivotal breakthrough in a large and important field... that never even got reproduced. What if it was a gigantic case of Clever Hans? How do you know? You're supposed to be a scientist, little one.
So my proposal to the LessWrong community: let's reimplement EURISKO!
We have some competent programmers here, don't we? We have open source tools and languages that weren't around in 1980. We can build an open source implementation available for all to play. In my book this counts as solid progress in the AI field.
Hell, I'd do it on my own if I had the goddamn paper.
Update: RichardKennaway has put Lenat's detailed papers up online, see the comments.