IBM research introduces SyNAPSE chip

IBM with the help of a Columbia, Cornell, University of Wisconsin (Madison) and University of California creates the first generation of neuromorphic chips (press release and video) which mimics the human brain’s computational architecture implemented via silicon.  The chip is a result of Project SyNAPSE (standing for Systems of Neuromorphic Adaptive Plastic Scalable Electronics)

Hardware emulating wetware

Apparently the chip supports two cores one with 65K “learning” synapses and the other with ~256K “programmable” synapses.  Not really sure from reading the press release but it seems each core contains 256 neuronal computational elements.

Wikimedia commons (481px-Chemical_synapse_schema_cropped)
Wikimedia commons (481px-Chemical_synapse_schema_cropped)

In contrast, the human brains contains between 100M and 500M synapses (wikipedia) and has ~85 billion neurons (wikipedia). Typical human neurons have 1000s of synapses.

IBM’s goal is to have a trillion neuron processing engine with 100 trillion synapses occupy a 2-liter volume (about the size of the brain) and consuming less than one kilowat of power (about 500X the brains power consumption).

I want one.

IBM is calling such a system built out of neuromorphic chips a cognitive computing system.

What do with the system

The IBM research team has demonstrated some typical AI applications such as simple navigation, machine vision, pattern recognition, associative memory and classification applications with the chip.

Given my history with von Neuman computing it’s kind of hard for me to envision how synapses represent “programming” in the brain.  Nonetheless, wikipedia defines a synapse as a connection between any two nuerons which can take two forms electrical or chemical. A chemical synapse (wikipedia), can have different levels of strength, plasticity, and receptivity.  Sounds like this might be where the programmability lies.

Just what the “learning” synapses do, how they relate to the programmatical synapses and how they do it is another question entirely.

Stay tuned, a new, non-von Neuman computing architecture was born today.  Two questions to ponder

  1. I wonder if they will still call it artificial intelligence?
  2. Are we any closer to the Singularity now?