How Do Neural Networks Work in AI Systems?

Neural networks in AI systems work by mimicking the human brain's structure to recognize patterns and make decisions. They consist of interconnected layers of nodes (neurons), where each node processes input data and passes the result to the next layer. The network learns by adjusting the weights of connections based on the error in output using techniques like backpropagation. Over time, it improves accuracy in tasks like image recognition, language translation, or data prediction. Neural networks are the backbone of many advanced systems today, including natural language models and computer vision. For deeper knowledge, explore a Generative AI course.