Wednesday, September 24, 2014

Asa H vs other deep learners

Other deep learners typically have a fixed number of layers, a fixed number of nodes, a fixed number of nodes per given layer, etc.  Geoffrey Hinton's ImageNet, for instance, had 7 layers, 650,000 nodes, total, and a fixed number of nodes in each given layer.  Asa H, on the other hand, adds layers and cases/concepts as it learns, and the number of cases per layer varies with time as Asa learns.

It is an advantage of Asa H over humans that it can add memory and processors as and when it needs them.

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