Modern air defense confrontations demand rapid, precise task assignments in environments where threats evolve within seconds.

T-Mobile, Nokia, and Nvidia agree on where AI and wireless are converging, but not on the compute architecture to get there The “AI RAN” label has become a bit of a catch-all — AI for RAN, AI on RAN, ...

Abstract: Datacentres provide the foundations for cloud computing, but require large amounts of electricity for their operation. Approaches that promise to reduce power use by minimizing execution ...

RLightning is a reinforcement learning framework designed for embodied intelligence — from humanoid locomotion to robotic manipulation. Its core principle is "prototype locally, scale seamlessly": ...

Given that extreme weather disturbances frequently threaten the safe and stable operation of new power systems, the uncertainty of source–load forecasting has become a particular bottleneck affecting ...

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In this article, we advocate environmental equity as a priority for the management of future globally deployed AI systems. Concretely, we explore the potential of harnessing AI workloads’ scheduling ...

NanoFlow is a throughput-oriented high-performance serving framework for LLMs. NanoFlow consistently delivers superior throughput compared to vLLM, Deepspeed-FastGen, and TensorRT-LLM. NanoFlow ...