Neural networks are powerful artificial intelligence models that laid the foundation for large language models like ChatGPT. Mimicking the human brain, neural networks consist of nodes, connections, and layers. While their learning capability is limitless, they are primarily used in machine learning for three key tasks: clustering, classification, and pattern recognition.

Deep learning is a subfield within machine learning, and neural networks form the backbone of deep learning. A neural network with more than three hidden layers is called a deep learning network. The key technical advantage of neural networks is that they can work more efficiently and longer than humans, making them ideal for tasks requiring continuous processing.

Artificial neural networks in artificial intelligence are gaining traction, finding applications in image recognition, chatbots, prediction algorithms, natural language processing, medical imaging, autonomous vehicles, route optimization, customer behavior prediction, risk identification, and more. There’s no overstating the impact of artificial neural networks in deep learning, leading the charge in driving innovative solutions across industries.