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A learning system that is as fast as a static one

August 16, 2015 - Tagged as: en, supercompilation, multi-stage programming.

I was reading the 1986 paper The Concept of a Supercompiler one more time, and I found this amazing part that I either missed or didn’t find interesting when I read it for the first time:

(emphasis mine)

Supercompilation can also be performed throughout all levels of the system. Fix k = K and supercompile E(K, q) with a variable q. You have an expert system that cannot learn, but answers questions very quickly. You can restore the ability of the system to learn by endowing it with two memories: short-term and long-term. To answer a question, both memories must be scanned. The long-term memory has those procedures that are obtained by using a supercompiler with the knowledge present at the moment of the last supercompilation session. The short-term memory includes universal interpretive procedures operating on the incremental knowledge received after the last supercompilation session. Such a system can be both fast and able to learn. When it has no questions to answer(the periods of “sleep”), it will execute supercompilation procedures, converting its short-range memory into the long-range one. This would be a step towards a computer individual.

This is interesting for two reasons. First, we discussed similar ideas with my advisor couple of weeks ago, but in a different context. I’m hoping to write more about this in future posts. Second, I think the idea is easily implementable with a multi-stage language. I think this is one of the ideas that are very good yet even after years still waiting to be implemented and explored further.