Now it is all clear! Thank you. One last question I have is about cells. Given an input each column is connected to 50% of the random input bit. That's very clear and works great for spacial pooler. When it comes down to temporal pooler, CLA deals with cells within the columns. Do I understand this correctly, that each cell has synapses with other cells in other columns (this would explain the learning). How many connections each cell has with other cells? Does each cell in each column connect to every other possible cell in other columns (fully connected network). Or is there a specific % of cells each cell has to be connected to? I'm assuming this should be limited, otherwise let's say there are 1024 columns with 16 cells in each (16384 cells in the whole network), this would yield in 268,435,456 synapses that you have to keep track of for temporal pooler..
On Nov 14, 2013, at 1:59 PM, Marek Otahal <[email protected]> wrote: > > > > On Thu, Nov 14, 2013 at 10:28 PM, Dennis Stark <[email protected]> wrote: > > > > > The result is that NuPIC has some visual capabilities, but they are very > > limited, in terms of what you're talking about, by the lack of hierarchy in > > NuPIC at present. > > You mean hierarchy in terms of creating several regions and connecting them > in a hierarchy? Isn't this one of the key points for HTM? > It is a key-point of a HTM. And nupic did experiments with it in past, as I > mentioned. But now Nupic is a CLA. HTM is a hierarchy of CLA. Still you can > do great for categorization and feature detection with a simple CLA's spatial > pooler. > > > -- > Marek Otahal :o) > _______________________________________________ > nupic mailing list > [email protected] > http://lists.numenta.org/mailman/listinfo/nupic_lists.numenta.org
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