Page 46 - EE Times Europe Magazine | April2019

46 EE|Times EUROPE — Boards & Solutions Insert

SPECIAL REPORT: AI AT THE EDGE
Putting AI into the Edge Is a No-Brainer;

Here’s Why

By Duncan Stewart and Jeff Loucks

n 2020, Deloitte predicts that more than 750 million edge AI
chips — full chips or parts of chips that perform or accelerate
machine-learning tasks on-device, rather than in a remote data
Icenter — will be sold, representing US$2.6 billion in revenue.
Furthermore, the edge AI chip market will grow much more quickly
than the overall chip market. By 2024, we expect unit sales of edge
AI chips to exceed 1.5 billion, possibly by a great deal. That rep-
resents compound annual unit sales growth of at least 20%, more
than double the longer-term forecast of 9% CAGR for the overall
semiconductor industry.
These edge AI chips will likely find their way into an increasing Figure 2: The edge AI chip market (Image: Deloitte Insights)
number of consumer devices, such as high-end smartphones, tablets,
smart speakers, and wearables. They will also be used in multiple
enterprise markets: robots, cameras, sensors, and other devices for much less heat, making it possible to integrate them into handheld
the internet of things. devices as well as non-consumer devices such as robots. By enabling
The consumer market for edge AI chips is much larger than the these devices to perform processor-intensive AI computations locally,
enterprise market, but it is likely to grow more slowly, with a CAGR edge AI chips reduce or eliminate the need to send large amounts
of 18% expected between 2020 and 2024. The enterprise edge AI chip of data to a remote location, thereby delivering benefits in usability,
market is growing much faster, with a predicted CAGR of 50% over the speed, and data security and privacy.
same time frame. Keeping the processing on the device is better in terms of privacy
Nevertheless, this year, the consumer device market will likely rep- and security; personal information that never leaves a phone cannot be
resent more than 90% of the edge AI chip market, both in terms of the intercepted or misused. And when the edge AI chip is on the phone, it
numbers sold and their dollar value. The vast majority of these edge AI can do all these things even when not connected to a network.
chips will go into high-end smartphones, which account for more than Of course, not all AI computations have to take place locally. For
70% of all consumer edge AI chips currently in use. Indeed, not just in some applications — for instance, when there is simply too much data
2020 but for the next few years, AI chip growth will be driven principally for a device’s edge AI chip to handle — sending data to be processed
by smartphones. We believe that more than a third of the 1.56 billion- by a remote AI array may be adequate or even preferred. In fact, most
unit smartphone market this year may contain edge AI chips. of the time, AI will be done in a hybrid fashion: some portion on the
Because of the extremely processor-intensive requirements, AI com- device and some in the cloud. The preferred mix in any given situa-
putations have almost all been performed remotely in data centers, on tion will vary depending on exactly what kind of AI processing needs
enterprise core appliances, or on telecom edge processors — not locally to be done.
on devices. Edge AI chips are changing all that. They are physically
smaller, relatively inexpensive, use much less power, and generate THE ECONOMICS OF EDGE AI IN SMARTPHONES
Smartphones aren’t the only devices that use edge AI chips; other
device categories — tablets, wearables, smart speakers — contain them
as well. In the short term, these non-smartphone devices will likely
have much less of an impact on edge AI chip sales than smartphones,
either because the market is not growing (as for tablets) or because it
is too small to make a material difference (for instance, smart speakers
and wearables combined are expected to sell a mere 125 million units
in 2020). Many wearables and smart speakers depend on edge AI chips,
however, so penetration is already high.
Currently, only the most expensive smartphones — those in the top
third of the price distribution — are likely to use edge AI chips. But
putting an AI chip in a smartphone doesn’t have to be price-prohibitive
for the consumer.
It’s possible to arrive at a fairly sound estimate of a smartphone’s
edge AI chip content. To date, images of phone processors in Samsung,
Apple, and Huawei show the naked silicon die with all its features
visible, allowing identification of which portions of the chips are used
for which functions. A die shot of the chip for Samsung’s Exynos 9820
shows that about 5% of the total chip area is dedicated to AI processors.
Samsung’s cost for the entire SoC application processor is estimated
at US$70.50, which is the phone’s second-most expensive component
Figure 1: Locations in which intelligence can be embedded (after the display), representing about 17% of the device’s total bill of
(Image: Deloitte Insights) materials. Assuming that the AI portion costs the same as the rest of

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