What is an AI accelerator?

At a glance

• Purpose-built chips that handle AI’s heavy math faster and cheaper than a normal CPU.
• Three types: GPUs (versatile, most common), TPUs (Google’s cloud chips), NPUs (small, power-saving chips in laptops and phones).
• Most businesses rent this hardware from cloud providers instead of buying it.

How it works

A normal CPU handles one task at a time. AI work, like recognizing images or writing text, means doing millions of similar calculations at once. Accelerators are designed for that bulk parallel math, so they finish AI tasks faster and use less power^[1]. For you, that means lower costs and quicker results.

The main types

GPUs (originally for video games) are the most common. TPUs are Google’s AI-only cloud chips. NPUs are energy-efficient chips now built into new laptops and phones to run AI on the device itself^[2][4]. Major makers: Nvidia, Google, Apple, Intel, AMD, Qualcomm.

When to use

You rarely buy these. Cloud AI services already include accelerator time in the price. For heavy workloads, rent GPU or TPU power by the hour. For private, on-device AI, choose newer computers advertising an NPU^[3].

Bottom line

An AI accelerator is the engine behind fast, affordable AI: rent cloud GPUs or TPUs for heavy work, and lean on the NPU in newer devices for private, on-device AI.