Post by Ben Seipel, University of Wisconsin-River Falls/California State University, Chico; with Gina Biancarosa, University of Oregon; Sarah E. Carlson, Georgia State University; and Mark L. Davison, ...

Jim Fan is one of Nvidia’s senior AI researchers. The shift could be about many orders of magnitude more compute and energy needed for inference that can handle the improved reasoning in the OpenAI ...

Historically, we have used the Turing test as the measurement to determine if a system has reached artificial general intelligence. Created by Alan Turing in 1950 and originally called the “Imitation ...

AMD is strategically positioned to dominate the rapidly growing AI inference market, which could be 10x larger than training by 2030. The MI300X's memory advantage and ROCm's ecosystem progress make ...

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 ...

The vast proliferation and adoption of AI over the past decade has started to drive a shift in AI compute demand from training to inference. There is an increased push to put to use the large number ...

Expertise from Forbes Councils members, operated under license. Opinions expressed are those of the author. We are still only at the beginning of this AI rollout, where the training of models is still ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Rearranging the computations and hardware used to serve large language ...

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 ...

Post by Ben Seipel, University of Wisconsin-River Falls/California State University, Chico; with Gina Biancarosa, University of Oregon; Sarah E. Carlson, Georgia State University; and Mark L. Davison, ...