The Engine of AI: What is a GPU?

Modern AI is built on mountains of data and complex algorithms. But none of it would be possible without a specific piece of hardware, originally designed for something else entirely: video games.

The Traditional Engine: The CPU

A CPU (Central Processing Unit) is the "brain" of a standard computer. It's a brilliant specialist, designed to handle complex, sequential tasks one after another very quickly. Think of it as a winding country road—perfect for one car making complex turns.

The AI Engine: The GPU

A GPU (Graphics Processing Unit) is different. It's a brute-force army of thousands of smaller, simpler cores working in parallel. It can't handle one complex task as well as a CPU, but it can handle thousands of simple tasks all at once. Think of it as a massive, multi-lane superhighway.

Why AI Needs the Superhighway

Training an AI neural network involves millions of simple, repetitive calculations (mostly matrix multiplication). For a CPU, this is like a massive traffic jam on a single-lane road. For a GPU, it's what the superhighway was built for. It can process all the calculations in parallel, turning months of training time into days or even hours.

An Accidental Revolution

The rise of deep learning was made possible by this happy accident—that the hardware designed to render pixels in video games was perfectly suited for the parallel workloads of neural networks. The GPU is the unsung hero, the powerful engine driving the entire AI revolution.