AI/ML on edge
“AI/ML on edge” refers to the practice of deploying artificial intelligence (AI) and machine learning (ML) models directly on edge devicessuch as smartphones, IoT sensors, or embedded systemsrather than relying on centralized servers or cloud-based systems. This approach enables real-time data processing and decision-making by performing computations locally on the device. As a result, it can significantly reduce latency, enhance privacy, and decrease the need for constant network connectivity. By processing data on the edge, devices can operate more efficiently and autonomously, adapting quickly to changes in their environment without needing to communicate with a central server. This technology is crucial for applications requiring immediate responses or where data security and bandwidth constraints are concerns.
