Analyst Day Presentation March 2018

This presentation contains forward-looking statements that are subject to many risks and uncertainties. All statements made during this presentation other than statements of historical facts are forward-looking statements, including, without limitation, statements regarding Ambarella’s strategy, future operations, financial position, financial targets, future revenues, projected costs, prospects, plans and objectives for future operations, future product introductions, the future rate of our revenue growth, the size of markets addressed by the company's solutions and the growth rate of those markets, our ability to address market and customer demands and to timely develop new or enhanced solutions to meet those demands, our ability to retain and expand our customer relationships.

In some cases, you can identify forward-looking statements by terms such as "may," "will," "should," "could," "would," "expects," "plans," "anticipates," "believes," "estimates," "projects," "predicts," "potential," or the negative of those terms, and similar expressions and comparable terminology intended to identify forward-looking statements. We have based these forward-looking statements largely on our estimates of our financial results and our current expectations and projections about future events and financial trends that we believe may affect our financial condition, results of operations, business strategy, short term and long-term business operations and objectives, and financial needs as of the date of this presentation. Although the forward-looking statements contained in this presentation are based upon information available at the time the statements are made and reflect management’s good faith beliefs, forward-looking statements inherently involve known and unknown risks, uncertainties and other factors that may cause actual results, performance or achievements to differ materially from anticipated future results. Important factors that could cause actual results to differ materially from expectations are disclosed in the Ambarella's annual reports on Form 10-K and quarterly reports and Form 10-Q filed with the Securities and Exchange Commission (the “SEC”), particularly in the sections titled “Risk Factors” and “Management’s Discussion and Analysis of Financial Condition and Results of Operations.” You should not place undue reliance on these forward- looking statements, which speak only as of the date hereof. We do not undertake to update or revise any forward-looking statements after they are made, whether as a result of new information, future events, or otherwise, except as required by applicable law. Moreover, we operate in a very competitive and rapidly changing environment. New risks emerge from time to time. It is not possible for management to predict all risks, nor can we assess the impact of all factors on our business or the extent to which any factor, or combination of factors, may cause actual results to differ materially from those contained in any forward-looking statements we may make. In light of these risks, uncertainties and assumptions, the forward-looking events and circumstances discussed in this presentation may not occur and actual results could differ materially and adversely from those anticipated or implied in the forward- looking statements.

Before you invest, you should read the annual and quarterly reports and other documents Ambarella has filed with the SEC for more complete information about the company and its ordinary shares. Additional information will also be set forth in Ambarella's future quarterly and annual reports and other filings made with the SEC from time to time. You may access these documents for free by visiting EDGAR on the SEC web site at www.sec.gov.

Fermi Wang, CEO Fermi Wang is a seasoned leader, a serial entrepreneur, and a video compression technology expert. He holds several digital video- related patents, including one of MPEGLA's core MPEG-2 and MPEG-4/AVC patents.

Prior to Ambarella, Wang was CEO and co-founder of Afara Websystems, which pioneered server throughput computing. Afara was acquired by Sun Microsystems in July 2002. Afara's multi-core, multi-thread CPU is the critical technology in Sun’s UltraSPARC roadmap. Before founding Afara, Wang served in senior engineering and business management roles at C-Cube Microsystems. Wang's team was responsible for developing the world’s first MPEG CODEC chip.

Les Kohn, CTO Les Kohn is well regarded in Silicon Valley as one of the leading chip architects in the industry. Prior to Ambarella, Kohn was CTO and co-founder at Afara. After Afara was acquired by Sun, Kohn became a fellow at Sun and continued to develop Afara’s throughput computing technology that would become the primary focus of Sun's UltraSPARC roadmap.

Kohn was also chief architect at C-Cube, where he led the development of three generations of digital video CODECs, including the first single-chip MPEG-2 and HD/multi-stream CODECs. Prior to C-Cube, Kohn was a distinguished engineer at Sun where he was the chief architect of UltraSPARC I and II, Sun's first 64-bit microprocessors. Before Sun, Kohn was chief architect of the Intel i860 and co-architected the National 32000 microprocessor family.

Dr. Alberto Broggi, GM, Ambarella, Italy Dr. Alberto Broggi is the founder of VisLab , General Manager of Ambarella Italy, and a professor of computer engineering at the University of Parma in Italy. Widely considered as a leading pioneer in the use of machine vision for automotive applications, Dr. Broggi has been actively engaged in autonomous driving research and development for over twenty-five years. He was most recently honored with the IEEE Medal for Environmental and Safety Technologies “for leadership in vehicular environmental perception, and for setting worldwide milestones in safe and reliable intelligent vehicles” on May 25, 2017.

Chris Day, VP Marketing and Business Development Prior to joining Ambarella, Chris Day was President and CEO of Mobilygen, which was acquired by Maxim Integrated Products. Before Mobilygen, Day was general manager of media processing at NXP (formerly Philips Semiconductor), where he led TriMedia DSP efforts into video-over-IP, automotive, security, and display markets. Day has also held senior sales and marketing positions at C-Cube, AuraVision, Motorola, and Hitachi.

• 8:30 Introduction George

• 8:45 Strategic Overview: Computer Vision Fermi

• 9:15 Technical Review: Computer Vision & Les Automotive

• 10:00 EVA description Alberto

• 10:20 Car Demo start

• 10:30 Autonomous Development History Alberto

• 11:00 Market Overview Chris

• 11:20 Q & A Session

($MM) High-Growth, Profitable Company Diverse End Market Exposure

GoPro Revenue FY12-FY18 (excl. GoPro) CAGR: 21% Broadcast Other Non-GoPro Others Wear. Revenue $316 $310 VR Automotive $295 OEM Aftermarket $37 $96 $75 Sports (excl. $218 GoPro)

$158 $84 $295FY18 Sports $295MM $121 $53 $258 $235 (GoPro) $97 $28 $220 Prof $14 Security $135 $104 Drone $83 $93

Non- Cons. GAAP FY12 FY13 FY14 FY15 FY16 FY17 FY18 Security EBIT Margin 15% 21% 23% 31% 37% 35% 28%

Excl. GoPro, revenue grew 7% in FY17 and 10% in FY18

Note: Ambarella fiscal year ends January 31st. © 2018 Ambarella Inc. CONFIDENTIAL 6 History of Technological Innovations Within Video Computer Vision • >200M chips shipped CV1 • 2 – 3 chips taped out per year Sampling 1st Computer Vision SoC AmbaCastTM H2 Disrupted the broadcast video market – replaced 4KP60 solutions containing >20 DSPs + FPGAs and >40 HEVC DRAMs drawing >100W 10-bit Chip power consumption with…

1 Chip 1 DRAM 1W power & CV2 +50% A9 & CV22 better 1st 4K UHD, video quality(1) 10nm iOne DSC & IP CV SoC Smart Camera Camera SoC A6 SoC A1 1st 1080P60 st 1 full HD Infrastructure Broadcast SoC SoC Acquired VisLab

H1 A9AQ A8 1st Auto Camera 1st 4K UHD, 4KP60 chip with HEVC SoC with SVC Integrated A7L Infrastructure Founded SerDes A3 A5S 1st 32nm SoC 2004 1st 1080P60 1st 45nm Camera SoC Camcorder SoC Camera SoC (1) Compared to HD encoders before Ambarella. © 2018 Ambarella Inc. CONFIDENTIAL 7 Successfully Addressing Numerous Large Markets Automotive Security Cameras $4.1Bn By 2022 $1.1Bn By 2022

Virtual Reality Drones $100MM By 2022 $115MM by 2022

Sports Cameras Wearable Cameras $80MM By 2022 $60MM By 2022

Source: Internal estimates of addressable silicon market. © 2018 Ambarella Inc. CONFIDENTIAL 8 History of Using Technical Leadership to Ramp New Markets Quickly Initial Sales Selected Ramp ($MM) Customers Challenges Solved / Key Technologies

$18 ✓ Video is a special data type which requires an optimized $12 – chip solution – general purpose architecture does not work $2 ✓ Video Quality is the key to win and we’ve proven that we Broadcast are the best FY07 FY08 FY09

$34 ✓ Power consumption is critical for battery life and thermal design $19 ✓ Video quality and video stabilization are also significant $4 components of success Wearable ✓ CV is required for the next generation of products FY11 FY12 FY13 ✓ Power consumption is key for thermal design $46 ✓ Compression efficiency is key for video transmission and $16 storage $9 $5 ✓ Video quality in any light condition is critical Security FY11 FY12 FY13 FY14 ✓ CV is required for the next generation of products

$52 $38 ✓ Video Quality and Compression efficiency ✓ CV is the key for autonomous drones which will enable the $7 commercial drone market Drones FY15 FY16 FY16

Video Power Quality Consumption

Algorithm-First Approach Advantages

Acquired 2015

20+ Years of Compression Autonomous Efficiency Experience

CV Solutions Leverage Same Approach

Evolutionary:

• Natural progression from best-in-class video capture  understanding and contextualizing video in real-time • Ambarella has a long history of technical leadership in video processing, particularly at the edge • Ambarella and VisLab teams have been working on computer vision for edge devices across many large markets Revolutionary: • Ambarella’s CV1 is a completely new architecture, purpose-built for real-time analysis of video using deep learning techniques

• Provide complete hardware and software stack for autonomous systems • Ambarella’s computer vision roadmap opens the door to a multi-billion dollar Automotive opportunity in ADAS and Autonomous Driving solutions

Surround View Front Camera ADAS / Recorder

2025E

E-Mirror

Direct (1) (2) ~$2BN Silicon ~$8BN Opportunity

2017E

(3) ~$70BN (1) IDC + Gartner. (2) NVIDIA Presentation, September 2017. Systems + SW + Services (3) Intel / Mobileye Presentation. © 2018 Ambarella Inc. CONFIDENTIAL 12 Building on Existing Relationships Within Automotive

Approved Semiconductor Ambarella Ambarella Product Introductions and Supplier to Leading In Market Automotive Revenue Over Time OEMs and Tier 1s

($MM)

FY11 FY17 FY18 FY19E

Initial Rev. Surround Recorder Recorder E-Mirror View Recorder (Aftermarket) (OEM)

E-Mirror After- market

OEM

OEM Rev. Growth 135% 66% Surround View Opportunity to leverage existing automotive channel for CV solutions Note: Ambarella fiscal year ends January 31st. Projections based on preliminary management forecast. © 2018 Ambarella Inc. CONFIDENTIAL 13 Path to Autonomous Systems Ambarella In Market Sampling Taped-Out In-Design

A9AQ + A12A CV1 CV2 CV22 CV3 B6 and follow-ons

Recorder ADAS Autonomous Human and Autonomous Vision systems will co-exist E-Mirror

Surround View Computer Vision is the Key Enabler for Autonomy

Computer vision is the future and Ambarella has the best technology for computer vision at the edge

Dr. Alberto Broggi, GM , Ambarella, Italy Dr. Alberto Broggi is the founder of VisLab , General Manager of Ambarella Italy, and a professor of computer engineering at the University of Parma in Italy. Widely considered as a leading pioneer in the use of machine vision for automotive applications, Dr. Broggi has been actively engaged in autonomous driving research and development for over twenty-five years. He was most recently honored with the IEEE Medal for Environmental and Safety Technologies “for leadership in vehicular environmental perception, and for setting worldwide milestones in safe and reliable intelligent vehicles” on May 25, 2017.

Programmable Platform with Optimized Coprocessor Acceleration

Video Image Computer Compression Processing Vision

• 2x Compression • Best Low-Light, • Even Better Efficiency Efficiency HDR, Advantage Compared • >2x Power Efficiency Lens Dewarp, etc. to a General-Purpose Compared to App • Unified Viewing and Platform Processors Sensing

Porter 2009-now 4 fully autonomous electric vehicles VW Tiguan w/ 4K cameras

PROUD DEEVA CV integration 13km in 100% AV Parma, TerraMax 2004-2007 100% AV Fully autonomous + VIAC 15km cross- continent drive 100% AV following

DARPA Urban driving 100% AV, driverless

DARPA Grand 132 miles DEEVA 2014 Fully autonomous off-road 100% AV, With 13 stereo camera systems driverless 1993-1994 Fully manual Mille Miglia 2000+km Prometheus ADAS on Italian highways demo on closed track 94% autonomous steering

VisLab’s AV drove in

downtown Parma

2018

1994 2005 1993 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Stereo Camera Perception Monocular Camera Perception

Object Traffic Traffic Pedestrians Vehicles Motorcycles Classification Obstacle Detection Terrain Modeling Signs Lights

Curb and Barrier Visual Free Space Lane Marking Detection Odometry Detection Detection

Ultrasonic Multiple Cameras Depth Sensors LiDAR

Radar Sensor

Fusion Obstacle Fusion

Self Localization and Mapping

High-Level

Control Path Planning

Previous: DEEVA (18 PCs)

Now: EVA with CV1 Perception (replace 17 of 18 PCs)

CPU, GPU, DSP brute-force performance with large number of cores

• Too expensive in die size and power for edge applications – Large internal communication overhead – Large external DRAM bandwidth

• Executes data flow 1st Layer graphs with Input ConVKernel optimized operators for superior efficiency Convolution 2nd Layer • Same programming model as deep Pooling ConVKernel learning

frameworks like Convolution Tensorflow and Caffe Pooling Input • Flexibility and high performance without many cores MatrixMultiply

Result

Customer Network from training framework

Tensorflow TOOL MAGIC

HW Network Fast, Optimized Efficient Coefficients CV SW ucode

High-Level Software A53

Video Image Vision RISC RISC Pipeline Pipeline Processing Processor Processor

Stereo + Feature Feature Matching Processor Processing

VMEM FEMEM MEM

DRAM Controller

DRAM

• 4K (8 Megapixel) Computer Vision Automotive Engine – Stereo: Generic Obstacle Detection up to and beyond 150m – Mono: CNN-based classification and tracking up to and beyond 180m – Alternatively 4x 2MP stereo pairs (8 cameras) for short range perception

• Optimized HW architecture – Best power/performance envelope – Allow most sophisticated algorithms to run on embedded platform

LiDAR Radar Stereo

Low Power − − ✓

Road Terrain Modeling − − ✓

Small Object Detection − − ✓

Short Range (Distance) − ✓ ✓

Long Range (Distance) ✓ ✓ ✓

Low Cost − ✓ ✓

Mono Redundancy − − ✓

SuperCam Long-Range Stereo SuperCam Short-Range Stereo • 2x 8MP sensors • 2x 2MP per module • 2x CV1 + H2 • B6 serializer • Data collection • Data collection • Ethernet output • 2x CV1 for 4 stereo pairs (8 cameras) • Evaluate long-range CNN and stereo • Evaluate short-range CNN and stereo

MotorVu ADAS Autonomous Superdrone • Front-facing, compact • 2x 2MP sensors + 6x 1MP sensors • Mono, 8MP or 2MP • 1x CV1 for 4 stereo pairs sensor • Full autonomous stack running on CV1 • Data collection • Data collection • Evaluate Ambarella CNN • Demoed at CES

✓ CV1 is a “unique combination of power and resolution” while “combining viewing and sensing applications”

✓ Architectural approach to CVflow processor has received very positive feedback

✓ Selected customers highly focused on LiDAR alternatives (e.g., Stereo)

✓ Potential customers evaluating performance via delivered CV1 development systems and SDK. Initial customer board designs under way

✓ 40+ Tier I and OEM customers experienced the CES 2018 demo and were highly impressed - virtually all requested SuperCam systems

7 nm 10 nm 14 nm CV3 CV2 CV1 • Scalable ADAS • Mono + Stereo CV Platform for L2 to CV Coprocessor • 20X CNN full stack • H.264/265 autonomous • IQ improvements • ASIL B (D) Support • System level ASIL

• Q218 Samples Performance 10 nm

CV22

• Mono CV • 4X CNN • H.264/265 • IQ improvements • System level ASIL • Q218 Samples

CY2017 CY2018 CY2019

Ambarella

CV1 CV2

Architecture Ambarella Optimized HW

Deep Learning 4K 15FPS 20x faster Performance

Stereo HW HW – 4K Stereo Pair @ 30fps

Power 3-4W 3-4W Typical Consumption Typical

Image Pipeline High-Quality Human and CV

Open: CV IP Customer IP and/or Amba IP

High- H.264/5 Codec No quality, Low-latency

Dr. Alberto Broggi, GM , Ambarella, Italy Dr. Alberto Broggi is the founder of VisLab , General Manager of Ambarella Italy, and a professor of computer engineering at the University of Parma in Italy. Widely considered as a leading pioneer in the use of machine vision for automotive applications, Dr. Broggi has been actively engaged in autonomous driving research and development for over twenty-five years. He was most recently honored with the IEEE Medal for Environmental and Safety Technologies “for leadership in vehicular environmental perception, and for setting worldwide milestones in safe and reliable intelligent vehicles” on May 25, 2017.

High-level description and objects

pixels

30 cm

75 deg

Monitor

Vision: Long-Range Modules PC Vision: Short-Range Modules Other sensors: Radar, GPS, Vehicle System,…

Currently, sensor fusion and planning run on the PC

4 Short Range stereo cameras 6 Long Range stereo cameras

» Urban Environment in Regular Traffic Worn-out lane markings and narrow lanes

Series of 90-deg curves Traffic light with turn on red

Junction with limited visibility Expressway Merging with fast traffic Series of traffic lights

– Perception running on Ambarella chips only (CV1) • Vision is the main sensor • Stereo 3D perception beyond 150m • Mono perception beyond 180m – 3D visualization, Sensor Fusion, and Path Planning running on PC

Dr. Alberto Broggi, GM , Ambarella, Italy Dr. Alberto Broggi is the founder of VisLab , General Manager of Ambarella Italy, and a professor of computer engineering at the University of Parma in Italy. Widely considered as a leading pioneer in the use of machine vision for automotive applications, Dr. Broggi has been actively engaged in autonomous driving research and development for over twenty-five years. He was most recently honored with the IEEE Medal for Environmental and Safety Technologies “for leadership in vehicular environmental perception, and for setting worldwide milestones in safe and reliable intelligent vehicles” on May 25, 2017.

» In June 2015, Ambarella acquired VisLab – Spinoff of Parma University, Italy – Active for 20+ys in Autonomous Driving (AD) – VisLab set worldwide milestones in AD with unique challenges

» ARGO, first long test

» ARGO, First Stereo Version

» DARPA Challenges

» DARPA Challenges, trinocular system

» VIAC, VisLab Intercontinental Autonomous Challenge

» VIAC, VisLab Intercontinental Autonomous Challenge – Stereo Terrain Modeling and Obstacle Detection

Urban Traffic Off Road

Downtown Parma, Italy – July 12, 2013

13x Stereo Systems 4x 2D Lasers

Dr. Alberto Broggi, GM , Ambarella, Italy Dr. Alberto Broggi is the founder of VisLab , General Manager of Ambarella Italy, and a professor of computer engineering at the University of Parma in Italy. Widely considered as a leading pioneer in the use of machine vision for automotive applications, Dr. Broggi has been actively engaged in autonomous driving research and development for over twenty-five years. He was most recently honored with the IEEE Medal for Environmental and Safety Technologies “for leadership in vehicular environmental perception, and for setting worldwide milestones in safe and reliable intelligent vehicles” on May 25, 2017.

1800

1600

VR 1400 Flying Cam Wearable Car-DV 1200 Sports IP-cam Cons 1000 IP-cam Pro

800

600 Security

400

200

0 FY2017 FY2018 FY2019 FY2020 FY2021 FY2022 FY2023

$K 6000

Automotive 5000

Surround View Autonomous 4000 Car Record eMirror ADAS 3000 VR Flying Cam Wearable Car-DV 2000 Sports IP-cam Cons IP-cam Pro

1000 Security

0 FY2017 FY2018 FY2019 FY2020 FY2021 FY2022 FY2023

• Dash Cameras (retail after market) – estimate 20M unit SAM • OEM Car Recorders – estimate 6-7M unit SAM, growing rapidly, high AMBA market share, multiple China and Japan OEMs

• AVM/Surround view – 5-7M unit SAM, growing market • Electronic Mirrors (new market) – rearview and rearview + side cameras • ADAS Forward Cameras • Semi-Autonomous • Autonomous

Aftermarket OEM and Dealer Video Recorders Fit Recorders

Ambarella powers ‘dash cameras’ Ambarella powers many OEM and that record millions of hours of dealer-fit drive recorders, combining video every day, worldwide. best video quality with automotive reliability.

• Ambarella-based car recorder, integrated with in-car infotainment system

• Electronic mirrors provide a clear unencumbered view and visibility in low light • Gentex Corp partnership announced

• Ambarella advantages: low light imaging, HDR, low latency, LFM, integrated recording capability • AVM provides 360-degree parking assist, security • Ambarella SoC solution provides four HD channels, advanced stitching and recording • CV required for next generation i.e. blind spot monitoring for three- channel electronic mirrors (potential to replace Radar)

Gentex three-channel electronic mirror based on Ambarella SoC

2017 Nissan Note – built-in Rear-View Electronic Mirror (competing solution)

Ambarella-based Rear-View Electronic Mirror

Ambarella-based Side-View Electronic Mirror

Ambarella has complete solution including SoC and SERDES

• ADAS – Forward-Facing Cameras • 2018: 25M* units, growing rapidly • Future - Euro NCAP requirements, example - emergency braking (standard by 2022 in US) • AMBA targeting with CV22 (mono) AMBA “MotorVu ADAS”

• Level 2-3 – Partial Autonomy • Current examples: GM SuperCruise, Audi, Tesla • AMBA targeting with CV2 (stereo)

• Level 4-5 Autonomous • AMBA targeting with CV3 (stereo) AMBA “SuperCam”

Market Trends SAM Over Time

+15% CAGR • Market continuing to grow rapidly as (MM Units) 91 cameras transition from Analog and HDcctv to full IP-Cameras +13% CAGR • China dominating 2MP category worldwide 55 • Market moving to higher resolutions 39 • EU/US focusing on higher MP, fisheye, multi-imager, etc. 27 +27% CAGR • HEVC starting to take off in EU/US, 15 following China 3

• CV is key to all new design decisions FY17 FY23E

Mainstream High End >$599 ASP Low End <$120 ASP $120-$599 ASP

Specialized Spec driven Low cost commodity • High Mega-pixel, AFZoom, • New features • Competing with HDcctv multi-sensor, advanced • 3M, 5M, 4K, HEVC, HDR, low- • SoC: $2.50-$3.50 analytics, extreme light environment • CV/analytics features • Advanced CV features • SoC: $3.50 - $15 • SoC: $10 - $50

Market Trends SAM Over Time (1)

(MM Units) Battery-powered Cameras strong growth +19% CAGR 66 • Ease of installation • Multiple cameras per household Door bell and “spotlight” cameras

Smart Cameras demand computer vision at the edge • Person detection, face detection, package detection 24 +14% CAGR New AI cameras emerging 17 • ”Alexa”, “Assistant” inspiring new use-cases 8

Cloud storage costs driving HEVC adoption FY17 FY23E

Retail Service Providers AI Cameras Sensing Cameras

• Smart cameras • Home security • Alexa/Assistant • Intelligent sensing • Doorbell cameras channels integration cameras replacing • Battery-powered • Mix of low-cost • Face recognition PIR sensors in cameras and high-end homes and offices • Smart baby monitors • Where innovation happens

New Form Factors: Battery-powered, Doorbell, Floodlight

• Computer vision at the edge – enables faster response, lower cloud costs, reduced network bandwidth, higher accuracy • Professional IP cameras examples: • Smart motion detection • Person detection, recognition, tracking • Trip wire • License plate recognition • Retail analytics cameras examples: • People counting, hot spots • Consumer cameras examples: • Person, pet, car detection and recognition • Package drop and removal detection

Total Units (MM)(1) SAM ($MM)(1)

Consumer Professional Consumer Professional

244 $1,119

161 $734

100 $490

69 $351 83 385 31 139

FY17 FY23 FY17 FY23

• Total camera market est. 10M units • 4K becoming baseline for even low-cost models • Ambarella combines dual 4K processing, low power, high-quality photography, and complete camera SDKs • Action cameras transitioning to 360-degree, 4K video • VR cameras creating immersive content for next- generation headsets • Computer vision will enable smart editing features

• Police Cameras – Ambarella powers the majority of the world’s police cameras – China dominates the volume – Low power, electronic image stabilization, and efficient HEVC are key differentiators – Computer Vision required for next generation of designs (i.e. face recognition) • Professional & Consumer Cameras/Glasses – Wearable camera market remains nascent – Snap Spectacles first high-volume glasses to ship

• Continuing treadmill of high resolution, high frame rates, high-quality photography and advanced stabilization requirements • DJI dominant player with approx. 80% market share – DJI introducing own silicon solutions • New entrants Skydio, Vantage/Snap using Ambarella for cameras • New opportunities in both consumer and commercial drones based on computer vision SoCs – Ambarella “Superdrone” demoed at CES 2018 • New opportunities in robotics driven by CV, example robotic vacuum cleaners

© 2018 Ambarella Inc. CONFIDENTIAL 86 Why Ambarella Continues to Win • Ambarella has been competing versus larger competitors with significantly more resources (e.g., Qualcomm, HiSilicon) for many years and has continued to succeed based on: – Superior Encoding Efficiency HD

– Superior Imaging Video Image Quality Processing – Multiple Stream Processing

– Lower-Power Performance Video Power Compression Consumption – Lower Total BOM Cost – Complete Software SDKs Total Computer – Complete Reference Designs Cost Vision – CVflow Architecture – Best CV Power/Performance