distributed AI
-
Moving AI Workloads from Cloud to On-Premise: A Strategy for Reducing Power Consumption
Arm CEO Rene Haas advocates for distributing AI workloads from cloud-based infrastructure to local devices to reduce energy consumption and improve sustainability. He highlights a shift towards hybrid computing, with AI training in the cloud and inference occurring on devices like smartphones and AR glasses. Arm’s expanded partnership with Meta aims to optimize AI efficiency across the entire compute stack, exemplified by localized speech recognition in Meta’s Ray-Ban Wayfarer glasses. This localized processing enhances responsiveness and reduces reliance on cloud servers.
