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, ...

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

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 ...

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, ...

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 ...

Microsoft is also inviting developers and AI startups to explore model and workload optimisation with the new Maia 200 SDK.

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 ...

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, ...

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) ...