I'm interested in hardware implementation of ANNs (artificial neural networks). Are there any popular existing technology implementations in form of microchips which are purpose designed to run artificial neural networks? For example, a chip which is optimised for an application like image recognition or something similar?

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    $\begingroup$ Maybe you could research "SpiNNaker" and "TrueNorth". $\endgroup$ Commented Aug 3, 2016 at 16:33

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In May 2016 Google announced a custom ASIC which was is specifically built for machine learningwiki and tailored for TensorFlow. It is using tensor processing unit (TPU) which is a programmable microprocessor designed to accelerate artificial neural networks.

NeuroCores, 12x14 sq-mm chips which can be interconnected in a binary tree, see: Neurogrid, a supercomputer which can provide an option for brain simulations.

TrueNorth, a neuromorphic CMOS chip produced by IBM, which has 4096 cores in the current chip, each can simulate 256 programmable silicon "neurons", giving a total of over a million neurons.

Further readings: Neuromorphic engineering, Vision processing unit, AI accelerators

As a side note, you can always use an FPGA based piece of hardware which you can implement selected genetic algorithm (GA) directly in hardware. For example the CoDi model was implemented in the FPGA based CAM-Brain Machine (CBM)2001.


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