Microsoft Research shows offloading inference boosts physical AI robot performance and battery life

Microsoft Research found that running physical AI inference exclusively on onboard GPUs limits robot performance, battery life, and scalability; offloading inference to edge or cloud GPUs offers significant advantages across mobile manipulation workloads, improving task success rates, enabling larger AI models, and enhancing responsiveness in dynamic, real-world environments. This approach also substantially improves battery life by replacing power-hungry onboard compute with lightweight hardware and remote inference, and introduces Kubernetes-based tooling for orchestrating distributed inference across robots, edge infrastructure, and the cloud.