When David Marr at MIT moved into computer vision, he generated a lot of excitement, but he hit up against the problem of knowledge representation; he had no good representations for knowledge in his vision systems.

Stanley Kubrick knew we had good graphics around MIT and came to my lab to find out how to do it. We had some really good stuff. I was very impressed with Kubrick; he knew all the graphics work I had ever heard of, and probably more.

The basic idea in case-based, or CBR, is that the program has stored problems and solutions. Then, when a new problem comes up, the program tries to find a similar problem in its database by finding analogous aspects between the problems.

Kubrick's vision seemed to be that humans are doomed, whereas Clarke's is that humans are moving on to a better stage of evolution.

We wanted to solve robot problems and needed some vision, action, reasoning, planning, and so forth. We even used some structural learning, such as was being explored by Patrick Winston.

I think Lenat is headed in the right direction, but someone needs to include a knowledge base about learning.