✨ Neuromorphic Computing ✨

✨ What is this❔

Neuromorphic computing draws inspiration from the intricate structure and functionality of the human brain. A neuromorphic computer/chip is a device that uses Spiking Neutron Network(SNN) to do computation. Spiking Neutron Networks are Artificial Neural Networks(ANN) that are build on mathematical descriptions of biological neurons.

✨ How does it work ❔

Traditional computer uses binary numbers , information is encoded into binary numbers using analog-to-digital converters . Neuromorphic computing works a little more flexibly. Nodes, or spiking neuron, process and hold data and communicate with each other like biological neurons, rather than using digital logic gates. This is different from traditional computing, which relies on transistors that can only be in two states : on or off.

✨ Advantages and Application ❔

🪶 Neuromorphic Computing is very energy efficient because they operate like the human brain .Human brain can perform a 100 trillion calculation per second using 12 watts of power(which is less than the power used by most modern light bulbs). As a result, it can lead to more energy- and compute-efficient AI systems.

🪶 Neuromorphic systems excel in tasks related to pattern recognition. They can identify complex patterns in data, making them valuable for applications like image and video recognition, surveillance, and medical imaging.

🪶 Neuromorphic architectures exhibit fault-tolerant behavior similar to the human brain. They can continue functioning even in the presence of hardware failures or noise.

🪶 Neuromorphic computing plays a crucial role in developing brain-machine interfaces. These interfaces allow direct communication between the brain and external devices, aiding in applications like prosthetics and assistive technologies.

✨ Challenges and Considerations❔

🪶 Neuromorphic systems, resembling human brains, raise ethical questions. Public anxiety about human-like robots may drive the need for restrictions and regulations. Clear legal frameworks are needed to prevent unauthorized use or misuse of this technology.

🪶 Due to the intricate structure of neuromorphic systems, implementing them can be challenging.

✨ Learn more from

GeeksforGeeks - Neuromorphic Computing

Spiking Neural Networks

YouTube Video