Jim, If you look at how lossless compression works, e.g. lossless text compression, it is mostly based on predictive probability models ...
If you have an opaque predictive model of a body of text, e.g. a deep NN, then it's hard to manipulate the internals of the model ... OTOH if you have a predictive model that is explicitly represented as (say) a probabilistic logic program, then it's easier to manipulate the internals of the model... So I think actually "operating on compressed versions of data" is roughly equivalent to "producing highly accurate probabilistic models that have transparent internal semantics" Which is important for AGI for a lot of reasons -- Ben On Sat, Oct 6, 2018 at 5:05 AM Jim Bromer via AGI <[email protected]> wrote: > > A good goal for a next generation compression system is to allow > functional transformations to operate on some compressed data without > needing to decompress it first. (I forgot what this is called but > there is a Wikipedia entry on something s8milar in cryptography.) > This is how multiplication works by the way. > > If a 'dynamic compression' was preformed in stages using 'components' > which had certain abstract attributes that could be used in > computations that were done in multiple passes, then it might be > possible to postpone a complete analysis or computation until the data > was presented in a more abstract format (relative to the given > problem). The goal is to find a way to make each pass effective but > seriously less complicated. The idea is that the data 'components' > (the data produced by a previous pass) might have certain abstract > properties that were general, and subsequent passes might then operate > on narrower classes. (This is how many algorithms work now that I > think about it, but they are not described and defined using the > concept of compression abstractions as a fundamental principle.) > Jim Bromer -- Ben Goertzel, PhD http://goertzel.org "The dewdrop world / Is the dewdrop world / And yet, and yet …" -- Kobayashi Issa ------------------------------------------ Artificial General Intelligence List: AGI Permalink: https://agi.topicbox.com/groups/agi/T55454c75265cabe2-M41141e5fa13b30106edc749f Delivery options: https://agi.topicbox.com/groups/agi/subscription
