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No. Compression == information, not intelligence. This is a common mistake that people make, and is a popular expression making the rounds right now, but it is
by tysam_and 3y ago
No. Compression == information, not intelligence. This is a common mistake that people make, and is a popular expression making the rounds right now, but it is incorrect.
Intelligence _may arise_ from information. Information _necessarily arises_ from compression.
It is very similar, to me, to the concept of humors (https://en.wikipedia.org/wiki/Humorism https://en.wikipedia.org/wiki/Humorism). Empirically, it was observed that these things had some correlation, and they occurred together, but they are not directly causative. Similarly with the theory of spontaneous generation (https://en.wikipedia.org/wiki/Spontaneous_generation https://en.wikipedia.org/wiki/Spontaneous_generation), which was another theory spawned (heh, as it were), from casual causal correlation (again, as it were).
This can be shown rather easily when you show that the time-dynamics of an exemplar system with high information diverge from the time dynamics of a system with high intelligence, i.e. there is a structural component to the information embedded in the system such that the temporal aspects of applied information are somehow necessary for intelligence.
I hope to release some work at least tangentially related to this within the next few years (though of course it is a bit more high-flying and depends on some other in-flight work). If we are to attempt to move towards AGI, I really think we need to stick with the mathematical basics. Neural networks, although they've been made out to be really complicated, are actually quite simple in terms of the concepts powering them, I believe. That's something I'm currently working on putting together and trying to distill to its essence. That will also be at least 1-2 years out, and likely before any temporally-related work, all going well. In my experience, this all is just a personal belief from a great deal of time and thought with the minutia of neural networks. That said, I could perhaps be biased with some notion of simplicity, since I've worked with them long enough for some concepts to feel comfortably second-nature.
- bbstats 3y agoOTOH true intelligence can still poorly compress things.
- tysam_and 3y agoAny ERM-based method will have this flaw (if it is a flaw -- I'd possibly consider it a tradeoff) -- it is the nature of compression itself. I would make the argument, I think, that I believe that this disrupts the 'information' layer of the hierarchy, not the 'intelligence', though that is just my personal 2 cents of course.
- derefr 3y agoI think what the GP meant is not that compressed data has intelligence, but rather that a compressor is necessarily "intelligent" in correlation to the degree that it compresses well on arbitrary novel datasets it wasn't tuned for. At least insofar as we define "intelligence" with measures like IQ, that relate to "number of examples of a pattern required to notice the pattern." To compress data, you have to derive some interesting insight about that data that allows the data to be projected into a lower-dimensional, lower-entropy embedding. (In pop-neurological terms, you have to "make a neuron" that represents a concept, so that you can re-phrase your dataset into a star-schema expressed in its connections to that concept.) The more different kinds of things a single compressor can do that for — without the compressor itself being made larger — the more "intelligent" the compressor is, no?
- tysam_and 3y agoYes, that is the point I'm addressing, I'm using Shannon's definition of information and making an argument about the _temporal_ aspects of it. If you're looking for a hint, it's in the Lyapunov exponents of the system, which do not come necessarily from compression alone, though compression I feel is a critical part of the process. Hence, the set vs superset argument.
- rurban 3y agoNo, compressability == complexity. Kolmogorov actually
- tysam_and 3y agoTo be a little blunt, this comment does not make that much sense. Kolmogorov complexity is based directly off of Shannon's information theory. It's the definition of the shortest possible length of a program that can output a particular string. It is an extension of information theory. If you just take either of the words 'Kolmogorov' or 'complexity' out of the phrase 'Kolmogorov complexity', it loses all meaning. We measure the programs for a given string against that string's Kolmogorov complexity by their entropy. Hence, why at the core, the very pith of the matter at hand is information, which is a measurable quantity. Additionally, K complexity is a lower bound, not a quantity. This is a similar kind of swap to saying "No, those baked goods are not food, because goods == items bought and sold for currency", if this recontextualizes it a bit.