AI Infrastructure
The compute, chips, data centers, and energy behind AI, and the constraints that shape what gets built.
52 stories · page 3 of 3
How Faster Image Delivery Is Becoming a Revenue Tool
Imgix, which processes 8 billion images daily for brands like Spotify and Porsche, has cut its image processing time in half by moving to Google Cloud's newest GPU-powered servers, a shift that reveals a broader pattern: the infrastructure behind visual media is quietly becoming one of the most direct levers businesses have over their online revenue.
June 2, 2026 · 2 min read
Nvidia's Bet on Micro Data Centers Near Power Substations
Nvidia and partners are building small data centers plugged directly into spare grid capacity at electrical substations across the U.S., a move that signals where AI infrastructure is heading next and has real consequences for businesses that rely on AI services, energy costs, and local grid stability.
June 2, 2026 · 3 min read
The Real AI Cost Problem Is Storage, Not Chips
Google has launched a high-speed cloud storage product aimed at AI workloads, and while it sounds technical, it points to a much bigger issue that every business running or evaluating AI needs to understand: the expensive computing hardware powering AI sits idle far more than anyone admits, and storage is usually the reason.
June 2, 2026 · 2 min read
The Hidden Cost of Running Your Own AI Engine
Superhuman's decision to hand off its AI serving infrastructure to Databricks after years of building it in-house reveals a pattern that every organisation deploying AI at scale will eventually face: the real cost of running your own AI is not hardware, it is the engineering time consumed just keeping the lights on.
June 2, 2026 · 2 min read