This document provides an overview of deep learning and computer vision markets from 2016. It discusses how increases in data, improvements in hardware like GPUs, and advances in algorithms have enabled deep learning applications. The document outlines several potential use cases for deep learning in computer vision, including image tagging, medical diagnostics from scans, agricultural analysis, and retail. It also provides forecasts for the growth of deep learning software markets in various industries from 2015 to 2024.

1. Copyright © 2016 Tractica 1
How Deep Learning Is Enabling
Computer Vision Markets
Bruce Daley
May 2, 2016

2. Copyright © 2016 Tractica 2
What the Future Promised
1956 1958 1960 1962 1964 1966 1968 1970
First AI
Winter
1970
Term
“Artificial
Intelligence”
Coined at
Dartmouth
Conferences
Summer
1956 Mark 1
Perceptron
Artificial
Neural Net
1958
Perceptrons
published1969
2001
ReleasedApril 3
1968
Calculus
solver1961
Checkers
program1962
Knowledge
based Chess1967
Natural
Language
Algebra
Solver
1964
ATOMIC
CARS
ARTIFICIAL
INTELLIGENCE
VACATIONS ON
THE MOON

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What We Got Instead
REALITY TVSTAYCATIONSYUGO
Google
Unsupervised
Deep
Learning Test
June
2012
2008 2009 2010 2011 2012 2013 2014 2015
Checkers
solved by
researchers at
University of
Alberta
2007
Google
builds self
driving car
2010
Artificial
Intelligence
for Enterprise
Applications
published
Apr
2015
Her
Released
Dec
18
2013
Narrative
Science
creates Quill to
write news
stories
2010
IBM
Watson
wins
Jeopardy!
2011
Apple
launches Siri2011

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Why We Became Interested
$-
$10,000
$20,000
$30,000
$40,000
$50,000
$60,000
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
Expected Growth in Deep Learning
Hardware Services Software
WHAT IS
DIFFERENT NOW?
$10.4 billion
for software
alone in
2024
Hardware
and services
revenue will
be many
times
software
sales
• Increases in data
• Improvements in
hardware
• Advancements in
algorithms

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Introductions
BRUCE DALEY
Principal Analyst
Artificial Intelligence
Conclusion
Deep Learning Market Use Cases and Forecasts
Market Drivers and Market Barriers
About Tractica
What is Different About Deep Learning?

6. Copyright © 2016 Tractica 6
About Tractica
Tractica is a market intelligence firm that focuses
on human interaction with technology
The firm’s market research and consulting services
provide industry participants and stakeholders with
in-depth analysis of emerging technology trends,
business issues, market drivers, and end-user demand
dynamics across multiple application domains
Sector Focus
• User Interface Technologies
• Biometrics
• Digital Health
• Wearable Devices
• Automation & Robotics
Research Services
• Research Reports
• Research Subscriptions
• Analyst Inquiry Sessions
• Consulting Projects
• Go-to-Market Services
• End-User Surveys

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Using Deep Learning to Paint by the Numbers
The Numbers
19 layer neural net
~524,288 nodes
500 – 1,000 iterations to generate
Represent
Generate
Content
Style

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Painting by the Numbers — Vary the Style
Content
Style
Content
Style

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Painting by the Numbers — Vary the Content
Content Content
StyleStyle

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Painting by the Numbers — Conclusion
Usually Low Ascetic Value Occasionally Very High Aesthetic Value — Fine Art
COULD HAVE
BEEN DONE
USING:
• Photoshop
• C++
• Paint Brush

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What’s New About Deep Learning?
Mimic the
Brain
Philosopher's
Stone
01110111
01101000
01100101
01110010
01100101
00100000
Enabling
Technology
• Deep learning is limited
• Deep learning is real
• Deep learning is different

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More Data Than Ever Before
Growth of
Value of
Data
Growth Maturity Decline
Product
Life Cycle
Introduc-
tion
The data from millions of security video cameras vastly outnumbers the time humans
can spend monitoring them in real-time – much less analyze them after the fact
Data Grows Throughout
Product Life Cycle
Amount
of Data
Impossible to
Analyze
Manually0
20
40
60
80
100
120
140
2016 2017 2018 2019 2020 2021 2022
Predicted Growth in
Amount of Data

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Market Drivers and Barriers
MARKET DRIVERS
MARKET BARRIERS
• Technology limitations
• Gap between expectations
and reality
• Social concerns
• Political and regulatory factors
• Shortage of talent
• Immaturity of the market
• Increase in data
• Hardware performance
improvement
• GPU
• FPGA
• ASSP
• Software algorithm
advancement
• Macro markets
• Economic trends

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Deep Learning Market Map
Universities
Big Tech
Semi-
conductor
Companies
Open
Source
University of Toronto
Stanford University
IDSIA Dalle Molle InstituteNYU
Intel
NVIDIA
Qualcomm
Microsoft
Caffe
Theano
TensorFlow
H20.AI
Baidu
Apple
Torch
IBM
Google
Facebook
Amazon
Uber
University of Montreal
Xilinx
Tsinghua University
Berkeley
Carnegie Mellon
Oxford
MIT
University of Hong Kong
Purdue
KALDICNTK

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Image Tagging and Owner Identification Use Case
Although
not strictly
computer
vision, an
important
use case to
understand
#cat
10110
01001
10010
#1
#cat owner
10110
01001
10010
#2
Extract Group Identify Classify MonetizeUse Case
Use Case 2.1 from Deep Learning Use Cases for Computer Vision
The need — every day, Facebook users upload 350 million new photos, and
Google is estimated to have indexed over 1 trillion images. It is not humanly
possible to tag all these pictures. Yet they have significant value

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Market Forecast: Ad Services Industry
$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
$3,500
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
North America
Western Europe
Eastern Europe
Asia Pacific
Latin America
Middle East
Africa
($Millions)
Deep Learning Software Revenue in
the Ad Service Industry by Region,
World Markets: 2015-2024
(Source: Tractica)
Companies to
Watch
Most data and
best business
model makes
this sector the
one to follow
Key Takeaway
“Deep Learning can be applied to almost every Google product.”
—Pete Warden
Staff Research Engineer, Google

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Digital Radiology Use Case
Use Case 2.2 from Deep Learning Use Cases for Computer Vision
The need — reading X-Rays and other electronic images is expensive and often
not very influential on a patient’s health. Many stakeholders in the system would
like to eliminate waste, reduce the number of mistakes, and reduce compensation
for analyzing these images

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Market Forecast: Medical Diagnostics Industry
$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
$3,500
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
North America
Western Europe
Eastern Europe
Asia Pacific
Latin America
Middle East
Africa
($Millions)
Deep Learning Software Revenue in
the Medical Diagnostics Industry by
Region, World Markets: 2015-2024
(Source: Tractica)
$0
$50
$100
$150
$200
$250
$300
$350
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
North America
Western Europe
Eastern Europe
Asia Pacific
Latin America
Middle East
Africa
($Millions)
Companies to
Watch
Evidence-based
medicine could
lead to machine
prescriptions and
a new business
model, especially
in the developing
world
Key Takeaway

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Agricultural Crop Health Analysis Use Case
Use Case 2.3 from Deep Learning Use Cases for Computer Vision
The need — more food for a hungry world. Satellites can conduct remote
agricultural inventories of crops; identify soil health, wet spots in fields, or
irrigation and waste runoff; and monitor crop canopies

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Market Forecast: Agriculture Industry
$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
$3,500
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
North America
Western Europe
Eastern Europe
Asia Pacific
Latin America
Middle East
Africa
($Millions)
Deep Learning Software Revenue in
the Agriculture Industry by Region,
World Markets: 2015-2024
(Source: Tractica)
$0
$50
$100
$150
$200
$250
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
North America
Western Europe
Eastern Europe
Asia Pacific
Latin America
Middle East
Africa
($Millions)
Companies to
Watch
First world
agriculture has
some of the best
use cases of any
industry
Key Takeaway

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Clinical Trial Medication Compliance Use Case
The need — patients not taking the right medications, at the right time,
and in the right doses is a major problem in medicine. The problem is
particularly acute in clinical trials
Use Case 2.4 from Deep Learning Use Cases for Computer Vision

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Market Forecast: Healthcare
Deep Learning Software Revenue in
the Healthcare Industry by Region,
World Markets: 2015-2024
(Source: Tractica)
$0
$10
$20
$30
$40
$50
$60
$70
$80
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
North America
Western Europe
Eastern Europe
Asia Pacific
Latin America
Middle East
Africa
Companies to
Watch
The more
administrative
aspects of
healthcare will
benefit from deep
learning long
before patients
will see any
meaningful
benefit
Key Takeaway

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Clothes Sizing and Fitting Use Case
Use Case 2.5 from Deep Learning Use Cases for Computer Vision
The need — during the dot-com boom, online clothing sales were
predicted to grow to 50% of total sales. Other kinds of merchandise have
reached that mark but online clothing sales hovers around 20%

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Market Forecast: Retail Industry
$0
$500
$1,000
$1,500
$2,000
$2,500
$3,000
$3,500
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
North America
Western Europe
Eastern Europe
Asia Pacific
Latin America
Middle East
Africa
($Millions)
Deep Learning Software Revenue in
the Retail Industry by Region, World
Markets: 2015-2024
(Source: Tractica)
$0
$100
$200
$300
$400
$500
$600
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
North America
Western Europe
Eastern Europe
Asia Pacific
Latin America
Middle East
Africa
($Millions)
Companies to
Watch
Retail is likely to
be an industry
sector where
deep learning has
a profound
influence
Key Takeaway

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Manufacturing Use Case — Quality Control Use Case
Use Case 2.6 from Deep Learning Use Cases for Computer Vision
The need — in 2012, the number of automobile recalls almost equaled
the number of sales, and a high volume of warranty payments impacted
automakers’ profits

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$0
$200
$400
$600
$800
$1,000
$1,200
2015 2016 2017 2018 2019 2020 2021 2022 2023 2024
North America
Western Europe
Eastern Europe
Asia Pacific
Latin America
Middle East
Africa
($Millions)
Market Forecast: Manufacturing
Deep Learning Software Revenue
in the Manufacturing Industry by
Region, World Markets: 2015-2024
(Source: Tractica)
Companies to
Watch
Surprisingly, this
sector lags
behind others in
research and
adoption. The
U.S. and China
lead, but a strong
Japanese
resurgence
should not be
ruled out
Key Takeaway

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• Deep learning is limited
• Enabling technology
• Mimics the brain but not exactly
• Dependent on good data
• Deep learning is real
• More data
• Faster hardware
• Better software
• Deep learning is different
• Data agnostic
• New programming methodologies
• Companies with the best business models will win
Its the business
models, not the
technology, that will
prove most disruptive
Growth in Value
of Data
Introduction Growth Maturity Decline
Sales
Product Life Cycle
Forecasts
Summary

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“In all industries, especially the
technology industry, people
overestimate what you can do in one
year, and they underestimate what
you can do in ten.”
Deep Learning Will Enable New Business Models,
Disrupt Old Ones, and Create New Sources of Wealth
Largest taxi
Company
(Source: Tom Goodwin)
Most valuable
retailer
Largest hotel
company
Most popular
media company
Marc Benioff
Chairman and CEO

29. Copyright © 2016 Tractica 29
TITLE
Subtitle
Quarter
BRUCEDALEY
Principal Analyst
CLINT WHEELOCK
Managing Director
DeepLearningfor Enterprise Applications
Advertising Technology,Financial Services,Media,
Manufacturing,Oil & Gas,Retail,and Other Enterprise
Marketsfor Deep LearningSoftware and Systems
Published 4Q 2015
RESEARCH REPORT
• Industries
• Ad Service Technology
• Agriculture
• Automotive
• Consumer Finance
• Data Storage and Networking
• Education
• Healthcare
• Investment
• Legal
• Manufacturing
• Media
• Medical Diagnostics
• Oil and Gas
• Philanthropies
• Retail
Additional Reading
• Hardware Product Categories
• Cloud Services
• Compute Products
• GPU Chips
• Network Products
• Storage Devices

30. Copyright © 2016 Tractica 30
Additional Reading
Where Data is Wealth
Profiting from data storage in a digital society
Published 4Q 2015
TITLE
Subtitle
Quarter
BRUCEDALEY
Principal Analyst
CLINT WHEELOCK
Managing Director
DeepLearningfor Enterprise Applications
Advertising Technology,Financial Services,Media,
Manufacturing,Oil & Gas,Retail,and Other Enterprise
Marketsfor Deep LearningSoftware and Systems
Published 4Q 2015
RESEARCH REPORT
Deep Learning Use Cases for Computer Vision
Six Deep Learning-Enabled Vision Applications in Digital Media,
Healthcare, Agriculture, Retail, Manufacturing, and Other Industries
Published 2Q 2016

31. Copyright © 2016 Tractica 31
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