I've noticed that whenever Jeff or another representative of Numenta gives a talk, they first revisit their definitions of terms used. Because a lot of these terms are "overloaded" by their context in everyday usage, it's probably important not to skip this step; especially because our goal brings with it conceptual hurdles as well as investigative.
I have a feeling this will become crucial when we start tackling "Attention" and awareness. Please forgive me if I'm stating the obvious? :-) David Sent from my iPhone > On Jul 11, 2014, at 7:12 AM, David Ray <[email protected]> wrote: > > Close. > > Using your "scale" analogy... > > Resolution = unit of measure of the most granular increment of change. (i.e > .01g) > > Capacity = count of distinct inputs possible at said resolution (i.e if scale > range is 0 to 10, then 1000) > > Accuracy = how "well" does the scale perform it's task of measuring weight > (i.e how often is it correct?) > > I don't know if resolution can be measured with the spacial pooler? > > David > > Sent from my iPhone > >> On Jul 11, 2014, at 6:48 AM, Rik <[email protected]> wrote: >> >>>> Sorry what value can be 1 billion? You keep bringing up that number. No >>>> spatial pooler of any sane dimensions has a capacity of 1 billion. Not for >>>> any reasonable definition of "capacity". >>> >>> In this case we are just trying to discriminate between a fixed set of >>> patterns. By "discriminate" we mean the SDR output should be unique with >>> respect to the other patterns by at least one winning column. Since there >>> are 1024 columns, of which 64 are on at a time, the total number of >>> patterns that can be discriminated is 1024 choose 64 > 10^102. In reality >>> it will be less than that, but if two inputs differ by more than a few >>> bits, we will have at least one column that is different. As such, there is >>> quite a bit of room here. >> The SP output can possibly produce 1 billion+ different patterns but that is >> what I would consider its "resolution", not its "capacity" or "accuracy" >> which is what we're after in this thread and what is the desirable property >> that one seeks to evaluate and optimize. A completely unlearned SP will also >> produce 1 billion+ different output patterns so that can't possibly be an >> interesting property. >> >> A real-world analogy: The local jeweler weighs precious metals with scales >> boasting a resolution of .01g but in the interest of getting a fair deal on >> my silver I'd rather know their accuracy. Scales with a resolution of .01g >> can still be off by 5g and usually will be so straight off the assembly line >> so they have to be calibrated, a primitive material world version of >> "learning". >> >> Or your digital SLR camera + computer monitor boast a 24bit color depth >> allowing for 4 million+ colors but that's saying nothing about how >> faithfully they reproduce the exact shade of red of a flower that you >> photographed and there's a calibration/"learning" process too that involves >> photographing known colors off a pantone sheet. >> >> A good definition of SP capacity or accuracy would IMHO involve a >> correlation between inputs and ouputs, along the lines of how well >> clusters in the input vector space correlate to clusters in the output >> vector space. Just thinking out loud here. >> >> -- Rik >> >> _______________________________________________ >> nupic mailing list >> [email protected] >> http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
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