[bl]

I'd be very interested to know more details about the structure of the RAM units. (Neither the original article nor the IBM press release at http://www-03.ibm.com/press/us/en/pressrelease/35251.wss talk much about it. The videos on the SyNAPSE website are also pretty distilled.) A biological synapse does, in a sense, serve as one of thousands tiny memory units on a neuron. But they are more capable than a single bit. A packet of neurotransmitter released into the synaptic cleft does activate the synapse, but the synapse itself (technically, the post-synaptic group of neurotransmitter receptors) responds in a graded (i.e., a non-binary) manner, strongly dependent on a) its recent history of activation, b) other synaptic activations in the vicinity, and c) and the local biophysical environment. I think I'd want at least 8 bits for the signal amplitude plus a few more to store some associated state variables.

I'd guess that the IBM team would have to replicate a lot of that "hardware" to get the emergent behavior of a piece of cortex. I do know that computational neuroscientists have struggled for the last 15 years or so get reduced neuron models (i.e., point neurons with a small number of rudimentary synapses) to even crudely mimic full-featured neurons. It looks like this group recognizes this issue in that they are already starting with many hundreds of synapses.

Another thing to keep in mind is that a processor inspired by brain hardware will be most likely very efficient in the tasks a mammalian brain is good at (pattern recognition, pattern completion, pattern separation, etc.), but will concomitantly be worse at things that a standard serial instruction processor excels at. I'd bet that the IBM folks are looking to merge a cognitive processor and a classical processor into a single unit.

Also, I know very little about compilers, assembly language, and other close-to-the-metal issues, but it appears that this processor would be very different to program.

[ristretto]

The processor would be no different to program than what we know, they haven't invented a new computational paradigm, it's still turing machines.

Just to illustrate your point about the intricacies of simulating synapses realistically, and to show how far this is from actual biological systems, here is a model of a single NMDA receptor: [1], It requires 26 floating point numbers just for the state-change rates and 20 floating point state variables. And that's just to simulate a single receptor!

[1] http://senselab.med.yale.edu/ModelDb/showmodel.asp?model=502...