"How Deep Learning Is Enabling Computer Vision Markets," a Presentation from Tractica

Copyright © 2016 Tractica 1

How Deep Learning Is Enabling

Computer Vision Markets Bruce Daley

May 2, 2016


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

published 1969

2001

Released April 3

1968

Calculus

solver

1961

Checkers

program 1962

Knowledge

based Chess

1967

Natural

Language

Algebra

Solver

1964

ATOMIC

CARS

ARTIFICIAL

INTELLIGENCE

VACATIONS ON

THE MOON


What We Got Instead

REALITY TV STAYCATIONS YUGO

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 Siri 2011


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


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?


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


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


Painting by the Numbers — Vary the Style

Content

Style

Content

Style


Painting by the Numbers — Vary the Content

Content Content

Style Style


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


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


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

Manually 0

20

40

60

80

100

120

140

2016 2017 2018 2019 2020 2021 2022

Predicted Growth in Amount of Data


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


Deep Learning Market Map

Universities

Big Tech

Semi-

conductor

Companies

Open

Source

University of Toronto

Stanford University

IDSIA Dalle Molle Institute NYU

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 KALDI CNTK


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 Monetize Use 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


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

($ M

illio

ns)

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


Digital Radiology Use Case


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


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

($ M

illio

ns)


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

($ M

illio

ns)

Companies to

Watch

Evidence-based

medicine could

lead to machine

prescriptions and

a new business

model, especially

in the developing

world

Key Takeaway


Agricultural Crop Health Analysis Use Case


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


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

($ M

illio

ns)


the Agriculture Industry by Region,


(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($ M

illio

ns)

Companies to

Watch

First world

agriculture has

some of the best

use cases of any

industry

Key Takeaway


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



Market Forecast: Healthcare


the Healthcare Industry by Region,


(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


Clothes Sizing and Fitting Use Case


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%


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

($ M

illio

ns)


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($ M

illio

ns

)

Companies to

Watch

Retail is likely to

be an industry

sector where

deep learning has

a profound

influence

Key Takeaway


Manufacturing Use Case — Quality Control Use Case


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


$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

($ M

illio

ns

)

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


• 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

Sa

les

Product Life Cycle

Fore

ca

sts

Summary


“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


TITLE

Subtitle Quarter

BRUCE DALEY

Principal Analyst

CLINT WHEELOCK

Managing Director

Deep Learning for Enterprise Applications Advert ising Technology, Financial Services, Media,

Manufacturing, Oil & Gas, Retail, and Other Enterprise

Markets for Deep Learning Software 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


Additional Reading

Where Data is Wealth Profiting from data storage in a digital society Published 4Q 2015

TITLE

Subtitle Quarter

BRUCE DALEY

Principal Analyst

CLINT WHEELOCK

Managing Director

Deep Learning for Enterprise Applications Advert ising Technology, Financial Services, Media,

Manufacturing, Oil & Gas, Retail, and Other Enterprise

Markets for Deep Learning Software 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


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