Neural Networks & Artificial Intelligence

Neural networks & artificial intelligence

Neural network example

In recent years, we noticed the ability of computers to understand and analyze the world around them, e.g.: the camera recognizes the faces of characters automatically, some types of cars avoid accidents and also have the ability to drive without a driver, these applications are mainly related to Neural Networks.

First, the term “Logistic Regression” should be explained. It is an appropriate regression analysis for a specific procedure when the variable is dichotomous.

Accordingly, we can say that logistic regression is a predictive analysis, which is used to describe and explain the relationship between a binary variable and one or more of the nominal or ordinal independent variables on the relative level.

Another term is “Multiplayer Perceptron”, it is considered a class of ANN neural networks.

This term is used explicitly to refer to networks composed of MLP.

Sometimes MLP is colloquially referred to as “Vanilla-Neural Networks”, especially if it has a single hidden layer.

MLP consists of at least three layers of nodes; The first layer is the input layer, the second is the hidden layer, and the third is the output layer.

Each node is a neuron that uses a nonlinear activation function except for the input.

MLP is based on the method of “Supervised Learning” (backpropagation), many layers and nonlinear activation distinguish MLP from linear cognition and enables it to distinguish data that is not linearly separable.

So, what is the difference between artificial intelligence and the human brain?

Neural networks were originally designed to simulate the function of the human brain, but they differ structurally from real human brains in ten aspects: form and function, size, connectivity, power consumption, architecture, activation potential, speed, learning technique, structure, and accuracy.

Another point, there are two forms of consciousness, natural and artificial. “Artificial consciousness tries to simulate natural consciousness.”

Natural intelligence and natural consciousness are linked to the biological substrate “Brain”.

Scientists agree that a natural being without a brain does not possess intelligence or consciousness.

However, it is possible for a natural entity— if it possesses a brain — only intelligence or consciousness only, or both.

The pillar of the human brain is certainly important because; Many examples represent physical differences, illnesses, and traumatic injuries with measurable effects on intelligence or consciousness.

Intelligence is clearly proportional to a specific place on the “color gradient” and this gradient is measured by IQ thus, we can classify normal intelligence along this gradient.

On the other hand, it is possible that the natural awareness of all intents is either something conscious or it is something acquired.

In the end, I tried as much as possible to clarify the relationship between neural networks and their attempt to simulate the human brain, but there is an important question, is it possible for artificial intelligence to outperform human intelligence? Knowing that currently, robots are still limited in their ability to sense their environment, excluding pre-defined environments, such as the chessboard, for example.

Some of the used sources:

· What is Artificial General Intelligence?

· Intelligence and Consciousness: What’s the Difference?

· HOW DO NEURAL NETWORK SYSTEMS WORK?

· Will robots take over the world?

· 10 differences between artificial intelligence and human intelligence