A long the coastline of Australia’s New South Wales (NSW) state hovers a fleet of drones, helping to keep the waters safe. Earlier this year, the drones helped lifeguards at the state’s Far North Coast rescue two teenagers who were struggling in heavy surf.
The drones are powered by artificial-intelligence (AI) and machine-vision algorithms that constantly analyze their video feeds and highlight items that need attention: say, sharks, or stray swimmers. This is the same kind of technology that enables Google Photos to sort pictures, a smart home camera to detect strangers, and a smart fridge to warn you when your perishables are close to their expiration dates.
But while those services and devices need a constant connection to the cloud for their AI functions, the NSW drones can perform their image-detection tasks with or without a solid internet connection, thanks to neural compute chips that let them perform deep-learning calculations locally.
These chips are part of a growing trend of edge-computing innovations that enable our software-powered devices to perform at least some critical functions without a constant link to the cloud. The rise of edge computing is helping us to solve problems new and old and pave the way for the next generation of smart devices.
A long the coastline of Australia’s New South Wales (NSW) state hovers a fleet of drones, helping to keep the waters safe. Earlier this year, the drones helped lifeguards at the state’s Far North Coast rescue two teenagers who were struggling in heavy surf.
The drones are powered by artificial-intelligence (AI) and machine-vision algorithms that constantly analyze their video feeds and highlight items that need attention: say, sharks, or stray swimmers. This is the same kind of technology that enables Google Photos to sort pictures, a smart home camera to detect strangers, and a smart fridge to warn you when your perishables are close to their expiration dates.
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