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 ...

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, ...

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.

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 ...

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, ...

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 ...

Google expects an explosion in demand for AI inference computing capacity. The company's new Ironwood TPUs are designed to be fast and efficient for AI inference workloads. With a decade of AI chip ...

The major cloud builders and their hyperscaler brethren – in many cases, one company acts like both a cloud and a hyperscaler – have made their technology choices when it comes to deploying AI ...

Inference is rapidly emerging as the next major frontier in artificial intelligence (AI). Historically, the AI development and deployment focus has been overwhelmingly on training with approximately ...

Qualcomm’s answer to Nvidia’s dominance in the artificial acceleration market is a pair of new chips for server racks, the A1200 and A1250, based on its existing neural processing unit (NPU) ...