6 stories tagged Edge Computing
Researchers have developed a runtime-aware framework that predicts how long large language models (LLMs) will take to respond on heterogeneous edge devices like smartphones and IoT gadgets, achieving 95% accuracy by accounting for hardware, runtime backend, thermal variation, and prompt behavior.
Nvidia has released Cosmos 3 Edge, an open-source AI model designed to run on everyday devices like smartphones and smart home gadgets, enabling real-time, offline AI capabilities.
Researchers proposed a modular design for AI agents that could run on small, low-power devices like sensors or wearables. This could enable smart assistants and automation in places where bulky computers aren't practical.
NVIDIA showcases Gemma 4's Variable-Length Attention (VLA) running on the Jetson Orin Nano Super. This highlights the model's efficiency and flexibility in edge computing applications.
Researchers propose a new method for resource-aware knowledge distillation in multi-agent reinforcement learning (MARL). The approach addresses the challenges of deploying expert policies on edge devices by focusing on coordination structure and heterogeneous agent capabilities.
Researchers introduce AgentGate, a new routing engine designed to solve dispatch inefficiencies in the emerging Internet of Agents. By replacing unrestricted text generation with structured candidate-aware routing, it optimizes latency, privacy, and cost.