For a long time, my AI strategy has been:
- First, figure out the AI’s knowledge structure – the way knowledge is stored inside its mind. You’d think this would be easy, but the problem of knowledge representation turns out to be nontrivial (much like the Pacific Ocean turns out to be non-dry).
- Once I know how to represent knowledge, I will begin work on knowledge acquisition, or learning.
To me, this order made sense. A mind must have a framework for storing information before you can help it learn new information.
Well, for the past week, I’ve tackled the problem from the opposite direction. I’ve pushed aside my 5,000+ lines of old code (for the moment) and started from scratch, building an algorithm that’s focused on learning.
The result is a little program (less than 200 lines long) that reads in a text file and searches for patterns…
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