AI glossary · Machine learning
Deep learning
Deep learning is a type of machine learning that uses neural networks with many layers to learn complex patterns in text, images and sound.
In more detail
“Deep” refers to the many layers in the neural network. Early layers pick up simple features, like edges in a photo; later layers combine them into complex ones, like faces.
Deep learning needs large amounts of data and computing power, usually on GPUs. It is behind nearly every recent breakthrough in AI, including large language models, image generators and speech recognition.
Related terms
Neural networkA neural network is an AI model made of layers of connected units, loosely inspired by the brain, that learns by adjusting the strength of its connections.Machine learning (ML)Machine learning (ML) is a way of building AI where computers learn patterns from examples, instead of being given step-by-step rules.TransformerA transformer is the neural network design behind almost every modern language model. It reads a whole passage at once and works out how its words relate.Convolutional neural network (CNN)A convolutional neural network (CNN) is a type of neural network designed for images. It scans a picture in small patches to detect edges, shapes and objects.GPUA GPU (graphics processing unit) is a chip that runs many calculations at once. Built for graphics, GPUs are now the main hardware for training and running AI.
Browse related tools
AI tools listed on BroUseAI in these categories.
