Edge Artificial Intelligence

Edge artificial intelligence (AI) focuses on deploying AI capabilities directly on resource-constrained devices at the network's edge, minimizing latency and bandwidth requirements for real-time applications. Current research emphasizes energy-efficient hardware designs, such as photonic processors, and optimized model architectures like convolutional neural networks (CNNs), often employing techniques like model compression and early exit prediction to reduce computational demands. This approach is crucial for enabling AI in diverse applications, from the Internet of Energy to implantable brain-machine interfaces, by addressing the limitations of cloud-based AI in terms of power consumption, latency, and data privacy.