Deep Learning
A subset of machine learning using neural networks with many layers to analyze complex patterns in data.
Definition
Deep learning uses artificial neural networks with multiple processing layers (hence "deep") to progressively extract higher-level features from raw input. These architectures can learn complex representations from unstructured data like images, audio, and text.
Deep learning powers many AI applications including image recognition, natural language processing, speech recognition, and autonomous systems. It requires substantial computational resources and training data but achieves superhuman performance on many tasks.
Why It Matters
Deep learning enables AI capabilities previously impossible, from accurate image classification to natural language understanding. These capabilities transform industries from healthcare diagnostics to autonomous vehicles.
For businesses, understanding deep learning helps evaluate AI vendor claims, identify application opportunities, and make informed technology investment decisions.
Examples in Practice
A healthcare company uses deep learning to analyze medical images, detecting potential cancers earlier than human radiologists with greater consistency.
Social media platforms employ deep learning for content moderation, automatically identifying policy violations across billions of daily posts.
A manufacturing company implements deep learning for quality control, identifying defects with 99% accuracy and reducing waste by 30%.