Deep learning: Deep learning is machine learning that uses neural networks with many layers, which lets a model learn complex patterns directly from raw data such as text, images, or audio. It is the technique behind today's language models and image generators.
Older machine learning needed a person to decide which features mattered. To detect fraud, someone had to say: look at transaction size, time of day, distance from home. Deep learning skips that step. Feed a many-layered neural network enough raw examples and it discovers the useful features on its own.
The 'deep' refers to the number of layers. Each layer transforms the data a little and hands it to the next, so early layers might pick up edges in an image while later layers recognize a face or a stop sign. The same idea applied to text is what lets a language model go from individual word pieces to the meaning of a paragraph.
Deep learning became practical around 2012, when graphics processors (GPUs) made training big networks affordable and the internet supplied enough data. The tradeoff is appetite: these models need enormous amounts of data and computing power, and their internal reasoning is hard to inspect, which is why explainability is an active concern.
Example at work
A hospital's radiology department pilots a deep learning tool that screens chest X-rays and flags likely abnormalities for a radiologist to review first. Nobody wrote rules about what pneumonia looks like. The model learned from a large set of labeled images, and the radiologist still makes every diagnosis.
Why it matters
When a vendor says their product uses AI, deep learning is usually what they mean. Knowing that these systems learn from raw examples, need lots of data, and cannot always explain themselves helps you judge which claims are credible and where you still need a human sign-off.
Related terms
- Machine learning (ML)Machine learning is the branch of AI in which software learns patterns from examples instead of following rules a programmer wrote by hand. Nearly every modern AI tool, including chat assistants, is built on it.
- Neural networkA neural network is a computing system made of layers of simple connected units that pass numbers to each other, with connection strengths (weights) adjusted during training until the network produces useful output. It is the building block of modern AI.
- GPU (graphics processing unit)A GPU is a processor built to perform enormous numbers of simple calculations in parallel. Originally for graphics, GPUs are now the main hardware used to train and run AI models, which is why they are central to AI cost, speed, and supply.
- Large language model (LLM)A large language model (LLM) is a neural network trained on enormous amounts of text to predict the next word, then tuned to follow instructions and hold a conversation. LLMs power ChatGPT, Claude, Gemini, and Microsoft Copilot.
- ExplainabilityExplainability is the degree to which you can understand why an AI system produced a particular output. It matters most when a decision affects a person and someone has to justify it.