What is deep learning?
Deep learning is a specialized branch of machine learning. It uses neural networks — structures loosely inspired by the brain — with many layers (the "deep" part) to learn from large datasets.
Each layer learns to recognize something slightly more abstract than the one before. In image recognition, early layers detect edges, later layers detect shapes, and final layers recognize faces or objects.
Why it matters
Most of the AI breakthroughs of the last decade — image generation, realistic voice synthesis, translation, and large language models — run on deep learning. It excels at messy, high-dimensional data like images, audio, and text where hand-written rules fail.
The trade-off
Deep learning models need substantial data and computing power to train, which is why specialized hardware like GPUs (and the NVIDIA H100 and DGX systems) became central to AI. They're also harder to interpret than simpler models, which is part of what makes explainable AI an active field.
Where you'll see it
Deep learning powers modern chatbots and large language models, image generators like Stable Diffusion and DALL·E, computer vision systems, speech-to-text, and recommendation engines. Whenever an AI product handles unstructured data well, deep learning is almost certainly underneath.