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 ...

Instead, a poor comprehender may be reading the text superficially and find no gaps requiring connections to missing information or may be trying to make connections, but the connections are to ...

Everyone is not just talking about AI inference processing; they are doing it. Analyst firm Gartner released a new report this week forecasting that global generative AI spending will hit $644 billion ...

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 ...

Kubernetes has become the leading platform for deploying cloud-native applications and microservices, backed by an extensive community and comprehensive feature set for managing distributed systems.

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 ...

Nvidia is aiming to dramatically accelerate and optimize the deployment of generative AI large language models (LLMs) with a new approach to delivering models for rapid inference. At Nvidia GTC today, ...

Nvidia Corp. is reportedly working on a dedicated inference processor that will be used by OpenAI Group PBC and other artificial intelligence companies to develop faster and more efficient models, ...

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 ...

Microsoft has announced the launch of its latest chip, the Maia 200, which the company describes as a silicon workhorse designed for scaling AI inference. The 200, which follows the company’s Maia 100 ...

Interactive LLMs (chat, copilots, agents) with strict latency targets Long‑context reasoning (codebases, research, video) with massive KV (key value) cache footprints Ranking and recommendation models ...

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, ...