Using light to speed up computation

A group of researchers in Japan has developed a new type of processor known as PAXEL, a device that can potentially bypass Moore's Law and increase the speed and efficiency of computing. PAXEL, which stands for photonic accelerator, ...

Introducing quantum convolutional neural networks

Machine learning techniques have so far proved to be very promising for the analysis of data in several fields, with many potential applications. However, researchers have found that applying these methods to quantum physics ...

Learning transistor mimics the brain

A new transistor based on organic materials has been developed by scientists at Linköping University. It has the ability to learn, and is equipped with both short-term and long-term memory. The work is a major step on the ...

New technique reveals limb control in flies—and maybe robots

A new neural recording technique developed by EPFL bioengineers enables for the first time the comprehensive measurement of neural circuits that control limb movement. Tested on the fruit fly, results from the technique may ...

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Biological neural network

In neuroscience, a neural network describes a population of physically interconnected neurons or a group of disparate neurons whose inputs or signalling targets define a recognizable circuit. Communication between neurons often involves an electrochemical process. The interface through which they interact with surrounding neurons usually consists of several dendrites (input connections), which are connected via synapses to other neurons, and one axon (output connection). If the sum of the input signals surpasses a certain threshold, the neuron sends an action potential (AP) at the axon hillock and transmits this electrical signal along the axon.

In contrast, a neuronal circuit is a functional entity of interconnected neurons that influence each other (similar to a control loop in cybernetics).

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