On 8/15/06, Matt Mahoney <[EMAIL PROTECTED]> wrote:

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I realize it is tempting to use lossy text compression as a test for AI because that is what the human brain does when we read text and recall it in paraphrased fashion. We remember the ideas and discard details about the expression of those ideas. A lossy text compressor that did the same thing would certainly demonstrate AI. But there are two problems with using lossy compression as a test of AI: 1. The test is subjective. 2. Lossy compression does not imply AI. Lets assume we solve the subjectivity problem by having human judges evaluate whether the decompressed output is "close enough" to the input. We already do this with lossy image, audio and video compression (without much consensus). The second problem remains: ideal lossy compression does not imply passing the Turing test. For lossless compression, it can be proven that it does. Let p(s) be the (unknown) probability that s will be the prefix of a text dialog. Then a machine that can compute p(s) exactly is able to generate response A to question Q with the distribution p(QA)/p(Q) which is indistinguishable from human. The same model minimizes the compressed size, E[log 1/p(s)].

This proof is really not useful. The Turing test is subjective; all you are saying is that lossy compression is lossy, and lossless compression is not. A solution to the first problem would also solve the second problem. It is necessary to allow lossy compression in order for this compression test to be useful for AI, because lossless and uncomprehending compression is already bumping up against the theoretical limits for text compression. - Phil -------

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