Edge Model
A type of AI model designed to process data directly on the device it was collected from, limiting the need for data transfer.
An Edge Model is specifically designed for edge computing, a practice that involves processing data directly at the 'edge' of the network where it is initially sourced, such as a smartphone or IoT device. Instead of sending volumes of data back to a centralized or cloud-based system for processing and analytics, an edge model takes care of it on the spot. The approach helps in reducing the latency of data processing, conserving network resources, and increasing privacy as the data does not need to leave the device.
The idea of edge computing and thus the application of edge model gained traction with the rise of IoT devices in the late 2000s and early 2010s. As more devices with processing power came online, the need for more efficient ways to handle the generated data became a concern. This led to the development and implementation of edge computing, and by extension, edge models.
The concept and practice of edge computing, and by association edge models, has been developed over time and draws on contributions from a wide variety of companies and individuals. Companies such as IBM, Cisco, and Akamai have made significant contributions to the field.