Artificial synapse and autonomous learning

Scientists have created an artificial synapse that can learn autonomously. Every single human beings has a brain consisting of neurons and synapses shaped uniquely to each person.

Advanced artificial intelligence and developments have been formed to copy how the brain functions. Such Artificial Intelligence systems are known as neural networks. Researchers have studied how artificial neural works contain algorithms in order to say it is capable of learning autonomously. The network also consumes a lot of time and energy. They have even created a sample device, which will be the next step forward to manufacture complex circuits.

CNRS research centre in Thales, Bordeaux University in Paris have manufactures a mersister on a chip which is also known as an artificial synapse. It is a good example for intelligent systems that needs less time and energy consumption for the process of learning and thus can learn autonomously.

Synapses work as a connective between neurons in the human brain which are reinforced and learning is enhanced the more the synapse is stimulated. The memristor also works similarly. It is created using a then ferroelectric layer between two electrodes using voltage pulses. The resistance can be adjusted like the natural neurons. When the resistance is low the synaptic connection will be strong. Thus the memristors learning capacity is based on this resistance.

The Memristor helps the learning process improve rapidly. Work continues in many explorable ways to maximize the functioning of it. The Scientists have built a physical model to help beginners understand how to predict its functions. So in future, the generations to come may look forward to use such a system to improve the functioning of the brain in order to do better. The work of the researchers and scientist are published in the Nature communications Journal if any further clarifications are needed.



Rajat Chakraborty Written by: