Emerging Technologies

AI is coming to your phone

A Samsung Electronics' Galaxy S8 smartphone is seen on display at its booth in Pyeongchang, South Korea, February 2, 2018.  REUTERS/Kim Hong-Ji

Adding artificial intelligence processing unit to our smartphones could increase their computing power. Image: REUTERS/Kim Hong-Ji

Dom Galeon
Writer, Futurism
Share:
Our Impact
What's the World Economic Forum doing to accelerate action on Emerging Technologies?
The Big Picture
Explore and monitor how Digital Communications is affecting economies, industries and global issues
A hand holding a looking glass by a lake
Crowdsource Innovation
Get involved with our crowdsourced digital platform to deliver impact at scale
Stay up to date:

Digital Communications

Almost every major player in the smartphone industry now says that their devices use the power of artificial intelligence (AI), or more specifically, machine learning algorithms. Few devices, however, run their own AI software. That might soon change: thanks to a processor dedicated to machine learning for mobile phones and other smart-home devices, AI smartphones could one day be standard.

British chip design firm ARM, the company behind virtually every chip in today’s smartphones, now wants to put the power of AI into every mobile device. Currently, devices that run AI algorithms depend on servers in the cloud. It’s a rather limited set up, with online connectivity affecting how information is sent back and forth.

Project Trillium would make this process much more efficient. Their built-in AI chip would allow devices to continue running machine learning algorithms even when offline. This reduces data traffic and speeds up processing, while also saving power.

“We analyze compute workloads, work out which bits are taking the time and the power, and look to see if we can improve on our existing processors,” Jem Davies, ARM’s machine learning group head, told the MIT Technology Review. Running machine learning algorithms locally would also mean fewer chances of data slipping through.

A staple for mobile phones

With the advantages machine learning brings to mobile devices, it’s hard not to see this as the future of mobile computing. ARM, however, isn’t exactly the first in trying to make this happen. Apple has already designed and built a “neural engine” as part of the iPhone X’s main chipset, to handle the phone’s artificial neural networks for images and speech processing.

Google’s own chipset, for their Pixel 2 smartphone, does something similar. Huawei’s Mate 10 packs a neural processing unit developed by the Chinese smartphone maker. Amazon might follow soon with its own AI chips for Alexa.

Image: ARM

The MIT Tech Review notes, however, that ARM’s track record for energy-efficient mobile processors could translate to a more widespread adoption of their AI chip. ARM doesn’t actually make the chips they design, so the company has started sharing their plans for this AI chip to their hardware partners — like smartphone chipmaker Qualcomm. ARM expects to find their machine learning processor in devices by early 2019.

Have you read?
Don't miss any update on this topic

Create a free account and access your personalized content collection with our latest publications and analyses.

Sign up for free

License and Republishing

World Economic Forum articles may be republished in accordance with the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Public License, and in accordance with our Terms of Use.

The views expressed in this article are those of the author alone and not the World Economic Forum.

Share:
World Economic Forum logo
Global Agenda

The Agenda Weekly

A weekly update of the most important issues driving the global agenda

Subscribe today

You can unsubscribe at any time using the link in our emails. For more details, review our privacy policy.

Why the Global Digital Compact's focus on digital trust and security is key to the future of internet

Agustina Callegari and Daniel Dobrygowski

April 24, 2024

About Us

Events

Media

Partners & Members

  • Join Us

Language Editions

Privacy Policy & Terms of Service

© 2024 World Economic Forum