How AI Thinks

Neural networks are the backbone of modern artificial intelligence. They are loosely modeled after the human brain, consisting of interconnected "neurons" that process information in layers.

Input and Hidden Layers

Data enters through the input layer and passes through various hidden layers where weights and biases are applied. This is where the "learning" happens. As the model is trained, it adjusts these weights to minimize errors.

By the time the data reaches the output layer, the network has made a prediction—whether that is identifying a cat in a photo or translating a sentence from English to French.