CPUs, GPUs, NPUs, and TPUs: A Deep Dive into AI Chips

Author(s): M

Originally published on Towards AI.

A deep dive into the hardware powering AI, from massive data centers to the phone in your pocket.

The rise of AI didn’t just require better software. It demanded entirely new hardware. Traditional computer chips, while versatile, simply can’t keep up with the billions of calculations modern AI requires. That’s where specialized accelerators come in.

This article extensively explores the four main types of chips that power AI: CPUs, GPUs, NPUs, and TPUs, detailing their distinct characteristics and roles in AI computation. It highlights how each type excels at various tasks, explains the required infrastructure for training and inference, and discusses the challenges associated with each chip. The article also addresses broader trends in AI hardware, including energy efficiency and the growing demand for specialized processors, while reflecting on the future landscape shaped by emerging technologies and market dynamics.

Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI