Deep learning is a subfield of machine learning and artificial intelligence that focuses on processing large amounts of data. It uses neural networks, which consist of many layers and can be trained using examples to recognize patterns and establish abstract relationships between the data. Deep networks can identify complex patterns in data, making it useful for tasks such as image and speech recognition, robotics, and autonomous driving.

Deep learning has made significant progress in recent years and is now being used in a wide range of applications, such as autonomous navigation of vehicles, automated language translation, and medical diagnosis.

There are various techniques used in deep learning, such as Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), which are specialized in different types of data.

However, deep learning often requires large amounts of training data and powerful computers to train and optimize complex models. In recent years, advancements in hardware development and the availability of data and tools have made deep learning more accessible for broader applications.