Hardware

System performance, efficient infrastructure scaling and continuous software optimization are key levers that determine AI inference economics. Higher system performance means more tokens generated, resulting in higher revenue. Efficient scaling...

The next wave of AI is placing new demands on infrastructure.  As AI agents and trillion-parameter workloads become mainstream, the performance of AI infrastructure depends not only on compute, but...

To generate intelligence at scale, AI factories run continuously, and their economics are defined by delivered output: tokens per second, tokens per watt, cost per token, utilization and uptime.  That...

According to OpenRouter data, agentic AI workloads consume 15x more tokens than a simple chat request. Why? ...

Every new generation of accelerated computing demands more from the infrastructure underneath it — more compute performance, higher rack density and more efficient, scalable power distribution. The bottleneck isn’t just...

Erin Davis calls it the “SuperDuperPOD.” That’s two things in one name: pharmaceutical giant Bristol Myers Squibb (BMS) already runs one of the largest AI clusters in life sciences, with...

Power is AI infrastructure’s inescapable constraint. How many tokens an AI factory can generate within a fixed power budget determines its revenue and profitability. Because of this, performance per watt...

As organizations move from AI pilots to production AI factories, infrastructure decisions have shifted from peak chip specifications to cost per token: how many useful tokens they can deliver per...

NVIDIA technologies power more than 400 of the world’s 500 fastest supercomputers — 81% of the TOP500 — according to the latest rankings released this week at the ISC High...

Enterprises are moving agentic AI from proof of concept to production — and the next generation of AI factories are built for the era of agents. At HPE Discover Las...