Every ChatGPT query, every AI agent action, every generated video is based on inference. Training a model is a one-time ...

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 ...

This brute-force scaling approach is slowly fading and giving way to innovations in inference engines rooted in core computer systems design.

But the same qualities that make those graphics processor chips, or GPUs, so effective at creating powerful AI systems from scratch make them less efficient at putting AI products to work. That’s ...

The market for serving up predictions from generative artificial intelligence, what's known as inference, is big business, with OpenAI reportedly on course to collect $3.4 billion in revenue this year ...

AI inference demand is at an inflection point, positioning Advanced Micro Devices, Inc. for significant data center and AI revenue growth in coming years. AMD’s MI300-series GPUs, ecosystem advances, ...

Machine-learning inference started out as a data-center activity, but tremendous effort is being put into inference at the edge. At this point, the “edge” is not a well-defined concept, and future ...

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 ...