"AI Is Moving to the Edge—What’s the Impact on the Semiconductor Industry?," a Presentation from Yole Développement

© 2019 Yole Développement
AI Is Moving to the Edge –
What’s the Impact on the
Semiconductor Industry?
Yohann Tschudi
Yole Développement
May 2019

On the road to augmented intelligence
2
Introduction
Robot
2030
PC Mobile Smart
Imaging
3D graphics
cards
2006
DNN with
GPU
2000 2010
Siri
2014
Alexa
2017
First SoC
with NPU
1990 2020
Mobile
Surveillance
IP camera
Audio
Smart hearable
Smartwatch
integrating AI
HW for audio AI
Smartphone
Virtual personal
assistant
Smart
camera Next-gen
assistant
Smartphone
integrating AI
Smartwatch
Companion
robot
Olfactometry
Smell identification
Human
augmentation
>2040
Motion sensing
Holographic
interaction
Augmented
human
Robot
home
Personal
Computer

Edge computing for consumer applications
3
A 3D look at the market:
• Stand-alone chip vs. embedded
unit in system-on-chips
• Imaging and audio
• Systems: smartphones, drones,
robotic homes
Systems
Audio
Embedded unit in
system-on-chip
Stand-alone chip
Imaging
In imaging & audio there is clear a need for AI,
and the technology is ready (or about to be)
Other domains are not taken in account:
• Technology not ready (olfactometry, taste
recognition)
• AI unnecessary for achieving the desired
goal (motion sensing)
Introduction

Definition of the different trends
4
Introduction
All computing parts are distinct and
can even be mounted on a dedicated
board
• Graphic card for GPU
• Sound card for DSP
All computing parts are embedded
and interconnected in a single chip
• SoC, application processor
(SoC for smartphones)
Specialization
A dedicated hardware architecture is
needed to process/compute a specific
type of algorithm. This architecture
can be embedded in an SoC or
integrated as a stand-alone chip
• NPU in SoC
• Sound processor
ARCHITECTURE LOCATION
Cloud
Cloud computing - computation
is done on the server’s
computing hardware
Edge
Edge computing - computation is
done on the device’s computing
hardware

Imaging – Dedicated hardware for AI
5
Introduction
Vision processing unit (VPU)
Unit embedded within the system’s application processor (AP)
Vision processor (VP)
Specialized stand-alone chip
AP enables
integrating various
functions, including
imaging, into a single
chip
Imaging embedded in AP is
already in smartphone
applications
Main consumer
applications are
biometry, control
(drones), AR/VR, and
photography
New VP applications
are for smart homes
mostly (surveillance,
IoT?)
Understand the environment
around the device
This unit type was originally
created to compute computer
vision algorithms (Mobileye eyeQ)

Smartphone
6

AI-dedicated unit
• Processing AI applications with a dedicated unit is faster
and consumes less energy
• No dependence on internet connection: run applications
anywhere, anytime
• Improvement of privacy: not all data used for inferences
is sent to the cloud
• Possible to use personal data to improve applications
using AI algorithms
• Less latency for critical applications like authentication
7
Market trends – Smartphone
Smartphones hardware must manage:
AI’s huge requirements
• High computational need
• Real-time
• Always-on
• Huge neural network
Mobile environment constraints
• Thermal efficiency
• Low consumption for long battery life
• Memory limitations
And…

Apple Application Processor evolution
8
Annotated A4 die photo
(source: MuAnalysis) Annotated A6 die photo
(source: Chipworks) Annotated A12 die photo
(source: TechInsights)
Adding more and more elements inside the
same chip, and introducing specialized
computing units
2010
2012
2018

AI for smartphone – Supply chain
9

721
928 995 1075 1110 1140 1096 1086
1121
1146 1222
233
307
376
406
470 513 602 653 673 693
682
63
167
262
407
591
825
1115
0
200
400
600
800
1000
1200
1400
1600
1800
2000
2013-2023 AP volume shipments by manufacturer type
and AP with AI volume shipments
Fabless OEM AP with AI
OEMs or fabless?
10
• Because AI will be a
key technology, we
expect fabless to ship
less AP in the next
three years -
particularly Mediatek,
which seem to be a bit
behind in the AI race;
• Huawei is gaining
share and building its
own chip through
HiSilicon. This move
explains the slight tilt
in market share, from
fabless to OEMs.

2017 & 2018e market share, AI application processors, volume shipments
11
• Huawei smartphones equipped with a Kirin 970 or 980 (late-2018) are gaining market share
because the technology is equivalent to Apple’s, but much more accessible price-wise;
• More players are proposing an AI application processor solution in 2018, explaining the YoY of
165%.
Apple
59
94%
Huawei
3
5%
Qualcomm
1
1%
2017
Apple
115.3
69%
Huawei
25.0
15%
Samsung
7.6
5%
Qualcomm
12.2
7%
Mediatek
7.0
4%
2018e
167
Munits
63
Munits

2017 2018e 2019e 2020e 2021e 2022e 2023e
Volume 63 167 262 407 591 825 1115
NPU Penetration rate 4% 10% 15% 22% 30% 39% 50%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
0
200
400
600
800
1000
1200
Volume(Munits)
2017 - 2023 AI application processor - volume shipment (in
Munits) and penetration rate
AI application processors – 5y forecast
12
• Because AI will be a must-have
for multiple reasons (marketing,
authentication, privacy, etc.),
dedicated hardware is needed
• We expect a 46% CAGR for this
type of hardware over the five
next years
Clear risk for some competitors
to be kicked out of the AP market
by not integrating AI, following
Apple & Huawei
→ One way to catch-up is to
focus on audio AI, which is not
ready yet, and being the first to
provide it

Drone
13

Segmentation of the market
Market trends – Drone

Consumer drones landscape
15

SoC hardware for drones players integrating AI
16

Supply chain
17
AI hardware
AI software
OEM
Image sensor
Possibility to add personalized
software something on top

Why use AI in drone applications ?
18
• AI is key to improving autonomous capabilities and human
comprehension
• Three core AI-based technologies can be used to improve
drone capabilities:
• With object detection and obstacle recognition, the drone
identifies obstacles, avoids them, and anticipates user
movements
• With gesture recognition, the drone can understand the user
without needing a smartphone interface
• With user authentication and tracking (face authentication),
the drone identifies its user, films him, and follows him
• The global trend is to reduce the smartphone’s role as the
interface between user and drone
Follow user
Obstacle avoidance
Palm control

2018e 2019e 2020e 2021e 2022e 2023e
Total high end drones with AI
hardware
0.9 1.3 1.9 2.7 3.3 3.8
Total high end drones 1.4 1.8 2.4 3.1 3.6 3.9
Total penetration rate 65.2% 70.6% 77.2% 87.1% 92.2% 97.7%
0.0%
20.0%
40.0%
60.0%
80.0%
100.0%
0
1
1
2
2
3
3
4
4
5
VolumeShipment(Munits)
High-end drones market forecast and AI penetration rate
19
This forecast include $500
ASP & $1200 ASP drones.
• Gesture recognition
and understanding
the environment
(object recognition)
are key applications
that will explain the
appearance of AI
hardware;
• DJI is a driver in the
drone market and
owns 70%. Other
players must follow
innovations like
3DR, or die;

Robot home
20

The robot home
• Home automation, or ”domotics”, is the discipline of building automation for a home: called a ”smart
home” or ”smart house”
• However, the term “smart home” is misused: it is more about a connected home than a smart home
• Connected to the internet, devices are part of the Internet of Things
• We define “robot home” as a smart home where devices are driven by AI technologies
• These technologies include deep learning for recognition and natural language processing
• For the robot home, latency and mobility are less important. However, privacy is key - and because of the
continuous presence of intelligent systems in our home, a transition from cloud to edge computing, system by
system, will happen.
Market trends – Robot home
Imaging Audio

2016 2017 2018e 2019e 2020e 2021e 2022e 2023e CAGR
Home IoT devices - - 0.3 2.1 7.4 19.3 32.5 60.2 189%
Personal Robotics - - - - 1.3 2.9 6.2 11.9 110%
Total Vision Processor - - 0.3 2.1 8.7 22.2 38.7 72.1
-
10
20
30
40
50
60
70
80
Volume(Munit)
2017-2023 Smart home systems - Vision Processor volume shipment
(in Munits)
Imaging AI hardware – 5y forecasts
22
• We imagine that half of IoT devices for smart home that have a camera, computing will be
based on a vision processor and the other half based on an embedded VPU in a SoC;
• For personal robotics though, because it needs a powerful computing hardware similar to
drones, we expect that only a vision processor will be viable for the next 5 years.

On the road to robot home
23
Security
Companion
robots
Connectivity
Home help
Home comfort
Robot
home

Conclusion
24

• We expect two different behaviors for imaging and audio: while audio AI will probably run on a specialized stand-
alone chip, imaging AI will be embedded
• All approaches will have a place in many applications. Embedded and stand-alone specialized chips will have almost
equivalent revenue by 2023.
Imaging and audio AI computing hardware
25
Conclusion
Sound
Processor
41%
Embedded Sound
Processing Unit
6%
Vision
Processor
15%
Embedded
Vision
Processing Unit
38%
2023e
Sound
Processor
46%
Embedded Sound
Processing Unit
4%
Vision
Processor
7%
Embedded Vision
Processing Unit
43%
2020e
Vision
Processor
4%
Embedded Vision
Processing Unit
96%
2017
CAGR17-20
96%
CAGR17-20
501%
CAGR20-23 31%
CAGR20-23 36%
$635 $9,722
CAGR17-20
148%
$23,305
CAGR20-23
34%
$611
$24
$4,581
$5,141
$10,243
$13,062
Total embedded in AP
IP revenues/Added-value of
the unit
Total specialized
chip
2019 - 2020
Audio AI in
smartphone

AP designers and
manufacturers
Without edge computing HW design
With edge computing HW design
Close to sensor
IP companies
Value chain
26
Conclusion
• Today, most of the value coming
from data is captured by GAFAM
& BATX;
• They are even designing their
own hardware to get deeper into
the value chain;
• There is tough competition on
the edge, between computing
close to sensor and centralized
in AP.

Resources
27
Market reports
From image processing to deep learning
2019
https://www.generic.org
Hardware & software for AI – Consumer
focus
https://www.i-
micronews.com/produit/hardware-and-
software-for-ai-2018-consumer-focus/
From image processing to deep learning,
introduction to hardware & software
https://www.i-micronews.com/produit/from-
image-processing-to-deep-learning-
introduction-to-hardware-and-software/
Blogs & websites
http://image-sensors-world.blogspot.com/
https://www.i-micronews.com/
https://www.embedded-vision.com/
https://www.visiononline.org/
https://www.mac4ever.com/
https://www.lembarque.com/

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"AI Is Moving to the Edge—What’s the Impact on the Semiconductor Industry?," a Presentation from Yole Développement