What is a Neural Network in AI?

A Neural Network in AI is a computing system inspired by the biological neural networks that constitute animal brains. It is designed to simulate the behavior of biological systems composed of "neurons". A neural network consists of layers of interconnected nodes, or "neurons", which process information using dynamic state responses to external inputs.

How does a Neural Network work?

A Neural Network works by processing inputs through layers of artificial neurons. Each neuron takes a set of inputs, applies a weight to them, sums them up, and passes them through a non-linear activation function. The outputs of one layer of neurons become the inputs to the next layer. The weights are learned during training, where the network adjusts them to minimize the difference between its predictions and the actual values.

Neural networks can learn complex patterns and relationships from data, making them a powerful tool for tasks like image recognition, natural language processing, and more.

What are the applications of Neural Networks in AI?

Neural Networks are used in many areas of AI, including computer vision, natural language processing, speech recognition, and more. They are the basis for many state-of-the-art AI systems, such as deep learning models used for image recognition, speech-to-text conversion, and language translation.