Real-Time-Insights

Edge AI: Processing at the Edge for Real-Time Insights Edge AI brings smart computing directly to devices and gateways at the edge of the network. By running models on cameras, sensors, phones, and edge servers, organizations can gain real-time insights without sending every byte to the cloud. This approach reduces latency, saves bandwidth, and strengthens privacy because sensitive data can stay local. How it works: developers optimize models with pruning, quantization, and efficient architectures like small CNNs or compact transformers. Runtime engines on edge devices provide fast inference even with limited power. Some devices include AI accelerators, DSPs, or GPUs to speed up performance, while small devices may rely on optimized libraries such as TensorFlow Lite or ONNX Runtime. ...