The focus of artificial-intelligence spending has gone from training models to using them. Here’s how to understand the difference—and the implications.

Edge AI is the physical nexus with the real world. It runs in real time, often on tight power and size budgets. Connectivity becomes increasingly important as we start to see more autonomous systems ...

These tech stocks look particularly well positioned to benefit from this opportunity.

Nvidia just paid $20 billion for Groq's inference technology in what is the semiconductor giant's largest deal ever. The question is: Why would the company that already dominates AI training pay this ...

To understand what's really happening, we need to look at the full system, specifically total cost of ownership of an AI ...

A food fight erupted at the AI HW Summit earlier this year, where three companies all claimed to offer the fastest AI processing. All were faster than GPUs. Now Cerebras has claimed insanely fast AI ...

Startups as well as traditional rivals are pitching more inference-friendly chips as Nvidia focuses on meeting the huge demand from bigger tech companies for its higher-end hardware. But the same ...

Red Hat is pushing Kubernetes inference into the mainstream by contributing llm-d to the CNCF, as enterprises race to run AI ...

Despite ongoing speculation around an investment bubble that may be set to burst, artificial intelligence (AI) technology is here to stay. And while an over-inflated market may exist at the level of ...