Steepest descent neural networks

About Cognitive Neuromorphic Engineering
(c) steepest descent

The two weeks I spent in Capocaccia were worth the trip. The Cognitive Neuromorphic Engineering workshop, organized by the University of Zurich, is an interesting mix of engineering, science, math and biology.

I was there four years ago, when the main topic was the design of the Neuromorphic chips that are now available for experiments, together with sensors like the Silicon Retina developed by Toby (watch the video below). 

The focus today has shifted mainly to programming the chips, and it is not an easy task! The main difficulties lie in the different programming methodology one should adopt. These chips are clock-less chips implementing different flavors of spiking neuron models. Programming the chips requires a new paradigm which is not there, so PHDs spend most of their time implementing simple behaviors such as Winner Takes it All.

That's why other PHDs are creating some kind of primitives that could be used as building blocks when developing more complex programs using Neuromorphic Hardware.

Yet, other PHDs are also working on some kind of simulated development of the Human Neocortex. Development could be used to configure a Neuromorphic chip in the future; imagine having to configure a million or even a billion neurons and their synapses by hand or using a centralize algorithm: the problem is clearly a combinatorial explosion which can possibly be solved by a more localized and parallel approach, hence development.

Source: Ocrampal's blog

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Hi all,
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