What is Neural Network in AI ?


Artificial Intelligence A device takes in information, does some processing to complete the task successfully.

A system that perceives information from the environment understands and interprets the data to take required action is known as Artificial intelligence machines.

A system that maximizes its chance of success by properly analyzing data is the core of Artificial intelligence. To develop Artificial intelligence (AI) products hardcoded instructions or program is of no use as the data around us is huge.

So as to develop generic solution algorithms are designed in such a way that enables machines to learn the required pattern, gain intelligence over time to take make a good decision.

How do humans learn?

Acquiring new things and updating our skills, knowledge is the process of learning. God blessed humans and every creature on the planet with this skill. With experience, we learn and grow.

Due to continuous interaction with society and the environment consciously and unconsciously we all are learning.

Five traditionally recognized senses of humans are sight (eyes), smell (nose), touch (skin), hearing, taste (tongue). All the species in the world have a multitude of senses.

With these senses we continuously gather information, neurons carry information our brain interprets the signals, processes, integrates and coordinates to take decisions.

How AI mimics biological Neurons?

The brain’s basic working unit is neurons. The human brain is made up of 100 billion neurons. These neurons transmit information to and from the brain and to the various parts of the body.

Biological Neurons:

Deep Learning is a subset of Artificial Intelligence that consists of algorithms inspired by the function and structure of the brain.

Artificial neurons are inspired by biological neurons. The neurons are connected to each other to control body functions, emotions, and movements.

The key components of biological neurons are: Dendrites bring information to soma so dendrites accept stimuli from an external environment.

Soma is the spherical part of neurons, the incoming signals are summed up by the soma when sufficient input is received neurons fire up(i.e. when the threshold is exceeded) and the axon sends information to other neurons depending upon the strength of the signal. If the input is not sufficient no potential action is taken.

Artificial Neuron: