@Bitking Yes, any relationship between information is useful, but wouldn’t seeing them at the same time (or close together) also preserve any relationship in your example?
My point was the only thing I see enforcing “semantic relationships in encoder output” giving was forcing processing to happen in different locations or to happen outside the system, assuming the system does what the brain does. Meaning if I removed that human generated relationship, a different computer element should see that same information and create a single “feature”, or set of related features, to be used by later elements. The system should extract the feature for me for later use in the same system.
“HTM doesn’t yet include a hierarchy which can form high levels of abstraction. So part of the job of an encoder is to do some of the work that lower hierarchical levels would do to capture abstract relationships (word SDRs are a good example)”
Perfect. Yes, I was about to return and ask if the newer idea of the brain using the same mechanism as location identification to organize the world (and it likely not existing in NuPic yet) was part of the problem. And yes, from the reading I’ve done it doesn’t appear the system has the ability to make layers yet.
Another reason I thought this might be required, was output. I don’t think I’ve seen a motor output mechanism or feature extractor (what I see our names for ideas as in the brain…finding the system’s highest processing element that signals something) or model creator (another way to picture decomposing a complex input into sub-ideas), so we’ll be the interpreter of any SDR output we need to understand beyond “yes/no” binary output. Sorry if I’m not using community accepted terms there, I’ll try to continue reading. And any logic we encode in that result output should help with finding relationships of our seemingly one possible layer. Or maybe I just haven’t gotten to where the output method is described?
It seems like offering flexible output to a system like this will introduce many interesting issues too.
Anyway, thanks all for the thoughts, and working through this with me. I am excited by a lot of what I’ve seen!