Computer Vision

A field of AI that trains computers to interpret and understand the visual world.

How it works

Computer vision systems process images as grids of pixel values. Convolutional Neural Networks (CNNs) pass learnable filters over these grids to detect edges, textures, and increasingly abstract features through many layers. Modern vision systems often use Transformer architectures (Vision Transformers) that split images into patches and apply attention across them. Tasks range from image classification and object detection to semantic segmentation and depth estimation.

Why it matters

Computer vision gives machines the ability to perceive and interpret the physical world, enabling autonomous vehicles, medical imaging diagnostics, manufacturing quality control, and facial recognition. The ability to process visual information at machine speed and scale — watching every frame of every security camera, or screening every medical scan — creates capabilities fundamentally inaccessible to human teams and is driving billions of dollars in investment.