Author(s): Mauro Di Pietro

Originally published on Towards AI.

What’s inside a data center, the infrastructure behind AI

A data center is a physical facility (room or building) packed with computers used for the storage and processing of digital information. Data centers are the backbone of the internet, required to run websites, cloud applications, and AI. But recently, there has been a growing demand to transform the traditional data center model and accommodate the massive power consumption of new AI products.

After introducing what data centers are, the article explains how modern data centers evolved from early room-sized computers to server-based facilities enabled by cloud computing. It then breaks down traditional data centers by size (micro, onsite enterprise, colocation, and hyperscale) and shows what all of them consist of: servers (rack, blade, tower), networking (switches/KVM, routers, firewalls), data storage (DAS, NAS, SAN), power (generators plus PDU and UPS, along with cooling needs like CRAC units), and the room/layout areas where equipment is distributed. The article’s core comparison follows: as AI workloads rose—especially with deep learning and later Transformers—organizations shifted from CPU-oriented “warehouses” to GPU/TPU-heavy “AI factories,” requiring much more electricity, more heat, different cooling (e.g., liquid-to-chip or immersion), and dramatically higher capital expenditure (e.g., far greater cost per MW). It concludes by framing this transition as a move from the cloud era to the AI era, where purpose-built infrastructure is optimized to produce intelligence at scale.

Read the full blog for free on Medium.

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Published via Towards AI