neural network

(redirected from neuromorphic chip)
Also found in: Dictionary, Encyclopedia.

neural network

A form of artificial intelligence that relies on a group of interconnected mathematical equations that accept input data and calculate an output. The more often the equations are used, the more reliable and valuable they become in drawing conclusions from data. Neural networks have been used in health care to interpret electrocardiograms and to make and suggest diagnoses.

neural network

a proposed system of interconnecting neurones to explain the higher brain functions such as memory perception and learning, where the pattern of resulting activity can be varied through the number and strength of connections between the constituent neurones.
References in periodicals archive ?
Artificial neural networks used in neuromorphic chips do not need to eat or sleep, but they generate heat and consume power at a large scale.
By contrast, neuromorphic chips process sensory data, such as images and sound, and respond to changes in data in ways not specifically programmed.
Neuromorphic chips attempt to model in silicon the massively parallel way the brain processes information as billions of neurons and trillions of synapses respond to sensory inputs such as visual and auditory stimuli.
Even if neuromorphic chips are nowhere near as capable as the brain, they should be much faster than current computers at processing sensory data and learning from it.
IBM makes neuromorphic chips by using collections of 6,000 transistors to emulate the electrical spiking behavior of a neuron and then wiring those silicon neurons together.
Whenever and however neuromorphic chips are finally used, it will most likely be in collaboration with von Neumann machines.
We've featured surprise modeling, a form of machine learning (2008); Siri (2009); deep learning (2013); neuromorphic chips (2014); conversational interfaces (2016); robots that teach each other (2016); self-driving trucks (2017); and reinforcement learning (2017).
Unlike traditional chips that process combinations of 0s and 1s as binary code, neuromorphic chips process spikes of electrical current that fire in complex combinations, similar to how neurons fire inside a brain.
But the speed and efficiency offered by neuromorphic chips won't stop there - reducing power draw by several orders of magnitude will allow such tasks to come out of the cloud entirely.
Neuroinformatics researchers from the University of Zurich and ETH Zurich together with colleagues from the EU and US demonstrate how complex cognitive abilities can be incorporated into electronic systems made with so-called neuromorphic chips: They show how to assemble and configure these electronic systems to function in a way similar to an actual brain.