Mugdha

Sep 10, 2022

What is Neuromorphic Computing?

Neuromorphic computing aims at modeling elements of a computer after the human brain and nervous system. It involves creating software and also hardware computing elements. Neuromorphic computing is often referred to as neuromorphic engineering. Neuromorphic engineers have knowledge of computer science, mathematics, physics, biology, and electronic engineering. This knowledge helps them create artificial neural systems inspired by the biological structure of networks in the human brain and nervous system. Neuromorphic computing has two primary goals:

To create devices that can make logical conclusions on inferences just the way a human brain can and also create devices that can learn, remember and retain information.

To gather new information in order to be able to prove a rational theory that illustrates how the human brain works.

Contrary to most supercomputers, our brains are compact and require much less space which is one of the factors that makes our brain an appealing model for computing.

The working of Neuromorphic Computing:

Firstly, Artificial Neural Networks, (ANN), consisting of millions of artificial neurons are placed. These artificial neurons are similar to the neurons in the human brain.

When layers of these artificial neurons pass signals to one another, a machine starts to act like the human brain. These electrical signals are responsible for converting input to output which helps start the working of neuromorphic computing devices or machines.

On the basis of Spiking Neural Networks, the electric spikes or signals functions are passed.

This thus formed spiking neural network architecture further gives a machine the ability to work similarly to the human brain and also to perform all functions that humans can on a daily basis including face recognition(sight), data interpretation, and similarly many other tasks.

These artificial neurons consume power only when the electric spikes are passed through them. Because of this, neuromorphic computing machines consume low power as compared to their traditional counterparts.

Neuromorphic computing devices have working like that of the human brain and are efficient and effective at performing tasks. Imitation of the neuro-biological networks present in the human brain helps achieve this. This has led to advancements in the developments of technology by bringing in the ability to work like the human brain in machines.

Traditional computers also require a lot of space for functioning, however, neuromorphic computing machines require much less space and come with an inbuilt ability to work faster and better.

Features:

Faster Response System.

Higher ability to adapt.

Less power consumption.

Mobile and handy.

Faster at learning.

Picture Courtesy: acm.org