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IBM Creates World's First Artificial Phase-Change Neurons (arstechnica.com)
An anonymous reader writes from a report via Ars Technica: IBM has created the world's first artificial nanoscale stochastic phase-change neurons and has already created and used a population of 500 of them to process a signal in a similar manner as the brain. Ars Technica reports: "Like a biological neuron, IBM's artificial neuron has inputs (dendrites), a neuronal membrane (lipid bilayer) around the spike generator (soma, nucleus), and an output (axon). There's also a back-propagation link from the spike generator back to the inputs, to reinforce the strength of some input spikes. The key difference is in the neuronal membrane. In IBM's neuron, the membrane is replaced with a small square of germanium-antimony-tellurium (GeSbTe or GST). GST, which happens to be the main active ingredient in rewritable optical discs, is a phase-change material. This means it can happily exist in two different phases (in this case crystalline and amorphous), and easily switch between the two, usually by applying heat (by way of laser or electricity). A phase-change material has very different physical properties depending on which phase it's in: in the case of GST, its amorphous phase is an electrical insulator, while the crystalline phase conducts. With the artificial neurons, the square of GST begins life in its amorphous phase. Then, as spikes arrive from the inputs, the GST slowly begins to crystallize. Eventually, the GST crystallizes enough that it becomes conductive -- and voila, electricity flows across the membrane and creates a spike. After an arbitrary refractory period (a resting period where something isn't responsive to stimuli), the GST is reset back to its amorphous phase and the process begins again." The research has been published via the journal Nature.
So, why can't we just query them for their contents?
(I'm an AI researcher by day.)
It's a very good idea, and something that many researchers have thought about. The problem is that it's very difficult to do, and so far no one's been able to figure out a good way to do it.
The cerebral cortex is composed of "columns", where each column is about the thickness of a human hair. If you could peel the cortex off and lay it flat, it would be about as thick as a business card. To all appearances, the cortex is composed of identical columns, with some slight variations for I/O columns and such.
Each column contains roughly 100 neurons in a handful of types. Any individual neuron makes between 2000 and 15000 connections with other neurons, and some neurons in a column make connections with neurons in other columns.
So you have 100 cells in a column the thickness of a human hair and length which is the thickness of a business card.
It's difficult to make a wire thin enough to contact one neuron, it's impossible to manoeuvre such a wire to get it in place to touch one neuron, it has to have insulation everywhere except the tip to avoid signals from other neurons, and the very faint signals have to be amplified close to the source to avoid noise.
It's just about impossible to map the connections between neurons because there are so many of them and the connections are much *much* smaller than the nerves themselves. Also, you have to do this without killing the nerve, and killing other nerves you have to go through to get the connections.
And this has to be done while the organism is living, and keeping it living while drilling into the head cavity is a trick in itself (and dealing with the resulting pain, blood loss, &c.). You can get some information from non-mammals (such as sea worms), but then none of those have a mammalian cortex to study.
Every once in awhile I read about new techniques using fiber optics and related technologies, but there's still the issue of routing the sensor (whatever it may be) to the neurons in a way that doesn't chop through other nerves.
One technology I read about has a pad with tiny needles laid down on the cortex. The needles can be made using chip fabrication technology, and you can have amplifiers on the chip at the base of the needles... but this still can only be applied to the *surface* of the cortex, and only connects to those nerves which are physically at the top of the column, and not the ones inside.
All in all, it's an extremely difficult problem that no one's figured out yet.
Firing rates:
* Human neuron: a couple hundred milliseconds
* Chip: A couple dozen nanoseconds. (note: not microseconds!)
Size:
* Human neuron: 4-100um on each axis
* Chip: Currently 100nm square on a thin wafer, with a 90nm process; scalable to 14nm process.
Now, let's not get ahead of ourselves: they are far from demonstrating the ability to emulate a human brain here. But if they do manage to implement a system that properly models human neural activity, the potential to vastly outperform the brain should be obvious. The number of neurons that make up the human brain could be packed into a single layer chip a third of a square centimeter (times some factor to account for the interconnects) operating at ten million times the speed. To say nothing of the ease of integrating it directly with storage, networking, and general purpose computing hardware.
And there is motive to advance this field, too. Neural nets are starting to have direct consumer applications (leaps and bounds improvements in image recognition, image enhancement, bandwidth reduction, etc). And we're talking about neural net chips that could readily be sized as a coprocessor in a phone. If there's a market, they'll make them. And advance them with time.
No, IBM is far from having a "brain on a chip". But it's very interesting research, to say the least.
Fox: "I think we should call it... your grave!" Cast: "Curse your sudden but inevitable betrayal!"
* Human neuron: an actual neuron
* Chip: nothing like a neuron. Doesn't even act like a neuron.
Just because someone calls something a "neuron" or "neural network" doesn't make it anything like a brain or even an approximation of how the brain works.