Scientists make a 'true' neural network using brain-like chips

Memristors behave like synapses, so they're a perfect fit.

Many people have built brain-like neural networks that can learn on their own, but they're typically using plain old silicon to do it. Wouldn't it be better if the chips themselves were brain-like? A mix of Italian and Russian researchers might help. They've created a neural network based on plastic memristors, or resistors that remember their previous electrical resistance. Since they effectively work like brain synapses, they're ideal for creating "true" neural networks where signal transfers create long-lasting effects. And importantly, the choices of technology and materials allows them to be very small (as tiny as 10 nanometers, in theory) without resorting to exotic substances -- you could design a neural network as compact as a regular chip without reinventing the wheel.

The technology is still a long way off. A prototype is relatively massive at 1mm wide, and it has only learned the most basic of tasks. However, the potential is huge. Besides creating neural networks that behave more organically, it'd enable machine learning systems and robots that need only a relatively tiny chip to do their digital thinking. If this technology pans out, it could form the basis of intelligent computers for years to come.

[Image credit: Moscow Institute of Physics and Technology]