Paper: http://arxiv.org/abs/1602.06987
Comments: Lossless compression of an image or audio file approximates its Kolmogorov complexity and reveals its "compressibility," or "interestingness." If it's not at all compressible it is too random to be aesthetic or enjoyable, whereas too much compressibility is associated with oversimplicity. Many classical works have been analyzed in this way and show to be in the middle. Schmidhuber mentions a theory of creativity, fun, motivation based on compression progress. Compression progress seems to be essential to theory of general AI- I refer to neuroevolution techniques, Cilibrasi and Vitanyi's paper Clustering by Compression for inference, as well as Wissner-Gross's simulations showing tool-usage behavior upon entropy maximization. Was a paper recently giving exact mapping between renomalization group and deep learning. Paper I link to above takes idea of data compression / Kolmogorov complexity even beyond a relationship to statistical mechanics or deep learning to explain the causal appearance of spacetime itself. I want to understand how Extreme Physical Information fits in to all of this.. it provides observer dependence and derivation of so many physical and nonphysical laws. It also encapsulates limits of knowledge using any particular channel of perception. -- You received this message because you are subscribed to the Google Groups "Everything List" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at https://groups.google.com/group/everything-list. For more options, visit https://groups.google.com/d/optout.
