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Everything you need to know about neuromorphic computing

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In July, a bunch of synthetic intelligence researchers showcased a self-driving bicycle that might navigate round obstacles, comply with an individual, and reply to voice instructions. Whereas the self-driving bike itself was of little use, the AI expertise behind it was exceptional. Powering the bicycle was a neuromorphic chip, a particular form of AI pc.

Neuromorphic computing is just not new. Actually, it was first proposed within the 1980s. However latest developments within the synthetic intelligence business have renewed curiosity in neuromorphic computer systems.

The rising recognition of deep learning and neural networks has spurred a race to develop AI hardware specialised for neural community computations. Among the many handful of tendencies which have emerged prior to now few years is neuromorphic computing, which has proven promise due to its similarities to organic and synthetic neural networks.

Learn: [How machines see: everything you need to know about computer vision]


How deep neural networks work

On the coronary heart of latest advances in synthetic intelligence are artificial neural networks (ANN), AI software program that roughly follows the construction of the human mind. Neural networks are composed of synthetic neurons, tiny computation models that carry out easy mathematical capabilities.

Synthetic neurons aren’t of a lot use alone. However once you stack them up in layers, they’ll carry out exceptional duties, corresponding to detecting objects in pictures and reworking voice audio to textual content. Deep neural networks can comprise lots of of hundreds of thousands of neurons, unfold throughout dozens of layers.

artificial neuron structure