Naah, even Apple II's 1Mhz processor could beat humans at "Pong" and read a written letter 7! This is just another scam on the taxpayer, and IBM should be ashamed! The so-called cognitive computer is nothing more than an underpowered curve-fitting device that gets stuck in local extrema, as IBM knows very well. A multi-core CPU with enough DRAM beats IBM's monstrosity in any task, any time.
Mr rbtbob-I am aware, and I tried to cover at least one application of a programmable resistance device, the PCM, in neural applications with the work I reported in:-
Here is my quote from PCM PR#4 that I think is applicable in light of the present stagnant state of commercial PCM product development
“If, going forward, the dreams of neural network emulation are to be fully realized, the challenges to PCM device designers in terms of precision, discrimination and scaling will exceed, by far, anything that has been accomplished to date.”
A quote that is also applicable to all programmable resistance devices, including, CBRAM and ReRAM. Also, with respect, I think you should also be reminded that for the synapse, timing between pre- and post-synaptic pulses as well as conduction change as a function of usage is important.
I can't help but find it a bit odd that IBM is still trying to duplicate probabilistic, over-complete, non-orthogonal, impulse integration systems using perfectly ordered and organized grids of binary devices. Might as well write the whole thing in software at that point. Biological neurons don't send signals in one or two defined routes, rather many directions randomized from neuron to neuron often including back to the neurons that originated the signal. It is interesting to note, though, that their learning algorithm does strengthen or "prune" pathways based on use.
Just to keep things straight, almost all neurons send OUT only one signal along one axon. The axon branches at the end and connects to the dendrites of many other neurons. Neurons may have thousands of dendrites receiving signals from other neurons (or receptors) Axons and synapses are like PCM, there is no possible way they could actually work :-)
PCM brings nothing to the so-called cognitive chip. Even if the cognitive chip made sense (which it does not), its value would be in the connectivity per sq inch (i.e., number of "synapses"), not the storage/counting media.
This is IBM's first generation device, intentionally created to transfer its supercomputer simulations to a hardware platform. As their simulations become more detailed, IBM will have to deal with all the mentioned issues going forward. (And yes, it is relatively easy to program a computer to play Pong or recognize a numeral, which is why these were good metrics for a very simple chip learning a task on its own.)
On reading your explanation of what Stanford had demonstrated, I was amazed that they could perform a resistance change using such a large number of pulses AND, if I understand your analysis, get the device to repeat the cycle enough to demonstrate a workable functionality.
Now the question is whether IBM is pursuing Stanford's scheme or some other? Also, could directional current pulses be used to enable both additive and subtractive resistance changes?
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.