A.I Comes To Edge Computing
PC Magazine|April 2018
A.I Comes To Edge Computing

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.

Ben Dickson

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.

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.

UNBURDENING THE CLOUD

In the past two decades, the cloud has become the defacto way of hosting applications, with good reason.

“The thing that makes the cloud so attractive is that it tends to offload the cost of starting up any activity you want to perform,” says Rob High, CTO of IBM Watson. “The cloud... allows people to... solve real problems today without having to go through the cost of infrastructure creation.”

With ubiquitous internet connectivity and nearcountless cloud applications, services, and development platforms, the barriers to creating and deploying applications have lessened considerably. The vast resources of cloud providers such as IBM, Google, and Amazon have boosted the development not only of trivial business applications but also of complex software that require vast amounts of computation and storage—AI and machine learning algorithms as well as streaming and AR (augmented reality) applications.

But these advances have also created a challenge: Most of the applications we use can’t function unless they are connected to the cloud. This includes most of the applications that run on computers and phones as well as the software in fridges, thermostats, door locks, surveillance cameras, cars, drones, weather sensors, and so on.

With the advent of the Internet of Things (IoT), an increasing number of devices are running software and generating data, and most of them will require a link to the cloud to store and process that data. The amount of power and bandwidth required to send that data to the cloud is immense, and the space needed to store the data will challenge the resources of even the most powerful cloud behemoths.

“There’s a lot of data that we’re collecting in these systems, whether it’s at the edge, or it’s an IoT device, or any other place, that you could almost decide not to care about,” High says. But if every decision must take place in the cloud, all that data will have to be sent across the network to cloud servers to be scrubbed and filtered.

As an example, High names modern airplanes, which contain hundreds of sensors that monitor jet engines and collect hundreds of gigabytes of status and performance data during each flight. “How much of that data really matters if you want to analyze it over an aggregate? Probably only a fraction of it,” High says. “Why not just get rid of it at the source when it’s not necessary for anything else you’re doing?”

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April 2018