The technology that enables machine learning on edge devices includes neural networks and specialized hardware like TPUs (Tensor Processing Units) and FPGAs (Field-Programmable Gate Arrays). These advancements allow data processing to occur on the device itself rather than relying on cloud-based systems, reducing latency and improving responsiveness. Edge machine learning enhances applications in various sectors, including autonomous vehicles and smart home devices.