The Intersection Problem
This report describes research done at the Artificial Intelligence Laboratory of the Massachusetts Institute of Technology. Support for the laboratory's artificial intelligence research is provided in part by the Advanced Research Projects Agency of the Department of Defense under Office of Naval Research contract N00014-75-C-0643.
This paper is intended as a supplement to AI MEMO 331, "A System for Representing and Using Real-World Knowledge". It is an attempt to redefine and clarify what I now believe the central theme of the research to be. Briefly, I will present the following points: 1. The operation of set-intersection, performed upon large pre-existing sets, plays a pivotal role in the processes of intelligence. 2. Von Neumann machines intersect large sets very slowly. Attempts to avoid or speed up these intersections have obscured and distorted the other, non-intersection AI problems. 3. The parallel hardware system described in the earlier memo can be viewed as a conceptual tool for thinking about a world in which set-intersection of this sort is cheap. It thus divides many AI problems by factoring out all elements that arise solely due to set-intersection.