Sponsored Content

Edge computing could be the hottest tech of 2019. But, what is it? And, why do we need it?

The growth of technologies such as the internet of things (IoT), artificial intelligence (AI) and the increasing use of devices and online activities has driven an immense growth in data generation, consumption and internet traffic.

By 2025 the number of installed IoT devices will be over 75.4 billion, and the world’s data is expected to hit 163 Zettabytes (one trillion gigabytes).

What’s more, the amount of the data that’s subject to analysis will grow by a factor of 50, and more than a quarter of all data created will be real-time.

Most of this data flows to and from the cloud. Whether it is the public cloud or an enterprise’s private cloud storage, this flow of data requires bandwidth and security protocols to ensure the data is safe.

The challenge of latency also slows down the speed at which we can access data in the cloud. For example, cloud storage is not quite literally in the cloud – it is housed in large data centres that are often in remote parts of the world as they require huge amounts of space.

One of the world’s largest data centres is 7.2 million square feet and is in the Nevada desert.

Edge computing enables the processing of data locally at the edge of the network or on the device, meaning the data does not need to be sent back to a central hub to be processed.

This could see internet of things devices placed in remote areas with the ability to operate on a private network.

This technology can also revolutionise technologies such as driverless cars, where the sensors could process the data at the sensor location as opposed to sending it back to the central hub for processing. This will increase reaction speeds as well as freeing up space at the central hub for other activities.

ASX-listed artificial intelligence company, BrainChip (ASX:BRN) is one company developing the processing power that will drive utilisation of edge technologies.

Its Akida Neuromorphic System-on-Chip (NSOC) technology utilises BrainChip’s unique artificial intelligence that is based on emulating a biological neural network. In other words, it is modelled to closely mimic the human brain.

These types of networks are called neuromorphic computing or spiking neural networks (SNNs). The Akida NSoC accelerates these spiking neural networks (SNNs) but in very low power, making it suitable for use in edge computing.

By deploying this technology onto a single chip, it is small, low cost and low power, making it ideal for applications such as driver assistance systems (ADAS), autonomous vehicles, drones, surveillance and machine vision systems.

Louis Dinardo, CEO of BrainChip said: “The burden of transferring large amounts of data to data centres or clouds creates delays and puts a huge burden on our infrastructure.

“By placing the computing power or storage as close to the device as possible, we can significantly increase speeds and reduce the burden of transporting the data to a central hub or data centre.”

This could be particularly relevant in Australia, which still relies heavily on cloud centres on the other side of the world, and where distances are massive.

While other companies are researching SNN technology, such as IBM and Intel, no company is solely focused on deploying and accelerating these SNNs at the edge like BrainChip.

BrainChip’s technology is currently being trialled with a number of ADAS and autonomous vehicle companies.

The amount of data being generated and processed globally will only continue to increase, and the infrastructure supporting it will be strained.

Touted as the solution to reducing the burden on infrastructure while increasing processing speeds and power, it is no surprise that edge computing is tipped to be the next technology trend on every tech investor’s mind.


This content is produced by Star Investing in commercial partnership with BrainChip. This article does not constitute financial product advice. You should consider obtaining independent advice before making any financial decisions.