A Deep Dive in the Venture Landscape ofArtificial Intelligence and Machine Learning

September 2015

Ajit NazreRahul Garg

Artificial Intelligence Evolution

Artificial Intelligence is on its 3rd reincarnation since its first birth in 1950 and looks like it has longevity this time around

1950 -1970s – Start of AI as a concept but no real applications

1980 -2000 – AI/ML mainly used in Military & Academia

2005 onwards – Large tech companies such as IBM, Microsoft, Google, and Facebook have invested in AI/ML for commercial applications

1956

John McCarthy organized a

conference at Dartmouth &

named the field as Artificial Intelligence

1950

Alan Turing published a paper

about the possibility of machines with true intelligence

1995

US Department of Defense uses

predator UAV in Balkan War

1997

IBM’s Deep Blue wins chess against World Champion

Gary Kasparov

2011

Debut of Virtual personal assistants like Apple’s SIRI &

Microsoft’s Cortana

2011

IBM Watson computer defeats

Jeopardy game show champions

Jan 2014

DeepMind team uses deep learning

algorithms to create a program that wins

Atari games

Oct 2013

Vicarious breaks any ‘Captcha’ passing

the Turing test

Jun 2015

Facebook launches Moments that

detects faces and shares photos with

friends to whom they belong

May 2015

Google self driving cars complete 1M

miles autonomously

Jun 2015

DeepMind teaches program how to

read

Artificial Intelligence / Machine Learning Classification

Artificial Intelligence

Deduction, Reasoning,

Problem Solving

Knowledge Representation

Planning Perception: Computer Vision

Machine Learning

Robotics: Motion and

Manipulation

Natural Language Processing

Social Intelligence

Supervised Learning Unsupervised Learning

Reinforcement Learning

Decision Tree

Learning

Association Rule

Learning

Neural Networks

Inductive Logic

Programming

Support Vector

Machines

Bayesian Networks

Similarity and Metric

Learning

Clustering

Deep Learning

Manifold Learning

Sparse Dictionary Learning

Genetic Algorithms

Multiple Factors contributing to Dramatic Improvement in Prediction Accuracy

Increasing Prediction Accuracy of Algorithms

=Improved Decision

Making

Increase in affordable Compute

Power

Big Data

Faster networks

Cloud Infra-structure

Sensor Networks

Advances in Neuroscience

“Whenever we can replace human judgment by a formula, we should at least consider it.” -Daniel Kahneman (2002 Nobel Prize in Economics)

Applications of AI/ML in Daily Use Already

InfoSearch engines

Sentiment analysis (or opinion mining)

Information Retrieval

Spam filtering for email

Speech and handwriting recognition

Spoken language understanding

Stock analysis

Structural health monitoring

Syntactic pattern recognition

Topic spotting: categorize news articles

Weather prediction

ToolsFace Detection

Finance – Derivatives Trading

Game playing

Software Testing

Internet fraud detection

Machine translation

Medical diagnosis

Mood analysis

Brain machine interface in prosthetics

Optical character recognition

Recommendation systems

Robot locomotion

Services

Advertising - Targeting

Bioinformatics

Automatic word completion

Chemical Informatics

Classifying DNA Sequences

Computer Vision – Object Recognition

Customer Segmentation

Detecting Credit Card Fraud

R&D Activity in AI / ML as measured by Patents granted

Source: MarketRealist.com

IBM and Microsoft had more patents in AI / ML granted in 2014 than all others

M&A Activity in AI / ML is Heating up

GoogleDark Blue Labs, Vision Factory, Jetpac, Quest Visual, Titan Aerospace, Deepmind Technologies, Boston Dynamics, Bot & Dolly, Holomni, Redwood Robotics, Industrial perception, Schaft, Flutter, Wavii, Behavio, DNNresearch, Viewdle, Pittpatt, Saynow, Phonetic Arts, Metaweb

Google Facebook Yahoo Apple IBM0

5

10

15

20

25

21

10

6 64

FacebookPebbles, Surreal Vision, Ascenta, QuickFire, Wit.ai, Oculus VR, SportStream, Jibbigo, Face.com, RecRec

YahooTomfoolery, Cloud Party, Skyphrase, LookFlow, IQ Engines, Qwiki

AppleMetaio, Cue, Novauris Technologies, Polar Rose, Siri, FingerWorks

IBMAlchemyAPI, Silverpop Systems, Curam Software, Languagae Analysis Systems

No. of companies acquired in AI/ML

Source: Wikipedia

Google is most acquisitive (21 companies) in the space followed by Facebook (10 companies)

AI / ML Venture Funding Analysis: Methodology

• Created a database of over 2800 AI/ML companies from several sources including Angel list, Crunch base, Tracxn, Venture scanner, Portfolios of major VCs, News Reports & Secondary Research

• Weeded out public, acquired, closed down and non existent companies (with no website) arriving at a list of 1781 companies

• Filtered the list further to 312 companies based on funding > $100k

• In addition to the focus areas in AI / ML areas defined on slide 3, we have extended our analysis to areas like augmented reality, image / facial recognition, and drones that overlap multiple areas.

2800

AI & ML companies from sources: Angel List, Crunch base, Tracxn, Venture scanner, VC websites, News

articles & secondary research

1781

Active companies after weeding out public, acquired, closed down, non

existent companies

312

Companies that have external

funding of >$100k

Active AI / ML Ventures by Country in 2015

More than half of the AI/ML companies are based in the US

USA UK India Canada Germany France Israel Russia China Nether-lands

Others0

100

200

300

400

500

600

700

800

900

1000929

127 10877 52 44 34 32 29 19

330

n= 1781

AI / ML Ventures based on Funding and Location

SF Bay Area has the highest density of funded startups followed by New York & London

Out of funded companies , nearly 40% are in the SF Bay Area & 70% in North America

Nearly 18% of companies are funded

Silicon Valley

San Francisco

NewYork London Seattle Berlin0

10

20

30

40

50

60

70

80

68

49

26

12 128

312

1469

Funded Com-paniesOthers

n=312

AI / ML Startups are still in their Infancy

62% of the startups still pre series A

Seed/Angel Series A Series B Series C Series D Series E Other0

50

100

150

200

250

193

72

26

10 5 1 5

n=312

Venture Funding and Most Active VCs in AI / ML

Khosla Ventures: Blue River, Scaled Inference, Atomwise, Lumiata, Kaggle, Idibon, Metamind, Pymetrics, Ayasdi, Catalia Health, Theatro, Thync

Google Ventures: Expect Labs, Wonder Workshop, Clarifai, Orbital Insights, Airware, Agent, AltspaceVR, Bento, Building Robotics, Framed, Skycatch

Intel Capital: API.ai, Cloudmade, Emotient, Expect Labs, Eyesmart, PrecisionHawk, Hooklogic, Prelert, Reflektion, Total Immersion, Fortscale,Whoknows, Incoming Media, Occipital

Two Sigma Ventures: Anki, 3D Robotics, Rethink Robotics, Jibo, Kasisto, Dextro, Socure, Floored, Canary, Zymergen, Indico Data,

RRE Ventures: DigitalGenius, Yhat, Clearpath Robotics, Jibo, Palantir, Giphy, Viglink, Airware

2010 2011 2012 2013 20140

50100150200250300350

Intel Capital Khosla Ventures

Two Sigma Ventures

Google Ventures

RRE Ventures

0

2

4

6

8

10

12

14

1614

12 12 12

8

Source: Company Websites

Source: CB Insights

No. of Investments in AI/ML companies

Venture Investments in $M in AI/ML companies

300% increase in venture funding from ‘13 to ‘14. Intel Capital, Google, Two sigma & Khosla ventures most active in investing in AI / ML

Funded Ventures in various fields of AI / ML

Machine learning, Robotics, AR and Image recognition are most actively funded areas

n=312

ML (exclud-ing Deep learning and pre-

dictive ana-lytics)

Robotics & Drones

AI (exclud-ing NLP,

ML, Robot -ics, Com-puter Vi-

sion)

Aug-mented Reality

Image & Face

Recog-nition

NLP Predictive Analytics

(clustering, SVM,

Bayesian networks)

Computer Vision

Deep Learning &

Neural Networks

Others0

10

20

30

40

50

60

70

80

90

10092

58

36 34 3326

11 10 84

Major Fields for AI / ML Venture Investment by Geography

North America is leading the way but Europe has significant presence in AI & AR areas

n=312

0

10

20

30

40

50

60

70

80

68

44

22 20 20 19

116 6

2

1710 9

14

613

0 2 2 27 4 2 2 2 0 2 0

North America

Europe

Asia/Other

Areas of Application of Venture funded companies in AI/ML

72% of the funded startups targeting enterprise applications

n=312

(consumer apps, consumer electronics, educational applications for consumers

& toys)

Enterprise Consumer0

50

100

150

200

250

224

88

AI / ML Ventures with Applications across Industries

Impact across a wide range of industries

Consumer Apps

Industrial Automation

AI/ML as a Service

Healthcare

Media

Marketing

Advertising

Security

Financial Services

Ecomm

erce

HR Agriculture

Education

Enterprise productivity

IT Services

Customer Service

Others

0

10

20

30

40

50

60

50

38

30

23 23 23

16 14 149 8 7 6 6 5 5

35

n=312

Aerospace

Cumbersome & manual process of maintenance and repair using

field manuals that have to be frequently updated

Field service agents can call or chat with support from his/her augmented reality view

Today Future

Companies making it happen: Atheer Labs, Augmate, Infinity AR, Total Immersion, Vuzix

Pic Courtesy: Atheer Labs

Agriculture

Farming decisions based on tradition and intuition

Machine learning algorithms using sensor data and aerial imaging help farmers make

intelligent data based decisions increasing yield

Today Future

Companies making it happen: Blue River, Farmlogs, Greensight, Mavrx, Pulsepod, Terravion

Pic Courtesy: Farmlogs

Automotive

Cars driven by humans, prone to errors (nearly 1.3M people die in road accidents

every year)

Driverless cars – leading to comfortable experience & less human fatalities

Today Future

Companies making it happen: BMW, Daimler Benz, Google

Pic Courtesy: Google

Background Checks

Checking of background information, documents and identity manually taking 1-2

weeks

Automated background checking process through APIs, real time ID authentication using

image recognition. Nearly 60% reduction in costs

Today Future

Companies making it happen: Onfido

Pic Courtesy: Onfido

Communications

People can talk to one another only in a common language that they speak

People will be able to talk to one another without knowing the other person’s language

– Nothing lost in translation

Today Future

Companies making it happen: Lexifone

Pic Courtesy: Clker.com

Hi, How are you

I’m fine thank you

Hi, How are you

मैं ठीक हूं धन्यवाद

Customer Care

Time consuming process of Authentication

Biometric Voice recognition based instant authentication

Today Future

Companies making it happen: Agnitio, Nuance, Verbio, Voicebase, Voiceitt, VoiceVault

Sir, Please help me with the authentication & tell me your DOB, Address,

Mobile No.My Password is XXXXX

Customer Care

Cumbersome & time wasting Voice Menu

Virtual assistant that can converse like humans & assist without Menus

Today Future

Companies making it happen: DigitalGenius, Expect Labs, Nuance

Press 1 for Credit Cards, Press 2 for

Debit Cards, Press 3 for Loans, Press 4 for

Netbanking……

Healthcare

Doctor reads static patient charts before or after visiting a patient

Doctor can read all relevant reports dynamically using gestures during her patient

visit

Today Future

Companies making it happen: Atheer Labs, Augmedix, Infinity AR

Media

Watching ads on TV is avoided as they are not actionable and mostly irrelevant

Automatic content recognition will allow advertisers/ programmers to inject

interactivity & context relevant content

Today Future

Companies making it happen: Cognitive Networks, Datascription, Dextro, Enswers, Magic Pony Technology, Persado, Videntifier Technologies

Wonder if that Jersey came in my

size

Just ordered the Jersey

directly

Pic Courtesy: Forbes

Navigation

Driver needs to divert his gaze or has to give rigid voice instructions

On windshield navigation with heads up display that recognizes the surrounding and

gives instructions

Today Future

Companies making it happen: Nuviz, Wayray

Pic Courtesy: Wayray

Office Productivity

Mundane tasks in office leading to decreased productivity

Automatic meeting schedulers, note takers, speech to text transcription & virtual personal

assistants will improve productivity

Today Future

Companies making it happen: Assistant.to, Gridspace, Idibon, Robin Labs, Thoughtly, X.ai, Zahdoo

Pic Courtesy: Typepad & Coolcontourproducts.com

Oil and Gas

Crack Detection: It takes human 5 hours per inspection with 92%

accuracy (Avg cost ~ $7.5)

20 seconds with 94% accuracy through image recognition (Average Cost ~ $2)

Today Future

Companies making it happen: Tractable

Pic Courtesy: Wikipedia

Recruiting

Impossible to manage candidates with required behavioral skills

Neuroscience based games will match candidates with required skills

Today Future

Companies making it happen: Connectifier, Pymetrics, Talentoday

Pic Courtesy: Pymetrics

Wealth Management

Stock trading & investing happens mainly on personal skills and divine luck

Sentiment analysis, crowd sourced research & algorithms will make investing more

transparent and better informed

Today Future

Companies making it happen: Betterment, Estimize, Narrative Science, Personal Capital, Sigfig, Wealthfront