What do neural networks primarily do?

Neural networks primarily serve to teach computers to process data through layered architectures that simulate the way the human brain operates. This learning mechanism enables them to recognize patterns, classify information, and make predictions based on input data. The architecture of neural networks allows them to adjust their parameters automatically based on the data they process, which enhances their ability to handle diverse tasks such as image recognition, natural language processing, and anomaly detection.

While facilitating complex data processing is an aspect of what neural networks do, it is more accurate to say that their fundamental role is in teaching systems how to interpret and categorize data. Similarly, neural networks can mimic human decision-making by finding patterns and making predictions; however, their core function revolves around learning from data rather than simply replicating human behavior. Analyzing large datasets effectively is a result of their capabilities, but it does not encompass the primary purpose of neural networks, which is centered on the learning aspect.