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1
FUTURE OF
ARTIFICIAL 
INTELLIGENCE
Andrew Trabulsi
June 2015
2
What are the major investment trends?
What’s the IP landscape look like?
What’s coming next?
3
Where’s the
money going?
4
Source: Capital IQ, Quid, iftf
Funding—where are we?
Private investment growing rapidly, M&A peaked in 2012
0
2,000
4,000
6,000
8,000
10,000
12,000
14,000
16,000
18,000
20,000
2010 2011 2012 2013 2014 2015*
Past five years of funding into artificial intelligence ($mn)
M&A
Private Investment
5
Source: Capital IQ, Quid, iftf
How’s the market shaping up?
Key investment areas since 2010
Cybersecurity!
Medical 10%
MapReduce 9%
NLP 9%
Ads 8%
ERP 8%
Robotics 7%
Shopping 7%
Computer Vision 6%
Market Composition
MapReduce!
Natural Language!
Processing!
Medical!
Cancer Diagnostics!
Recruiting!
Robotics!
Computer Vision!
Music!
Personal Assistant!
News Analysis!
Ads!
Shopping!
Financial services!
Enterprise Resource!
Planning!
6
Source: Capital IQ, Quid, iftf
Where’s it going?
Notable private investments and M&A deals since 2010
Quid, Inc.
ColdLight Solutions, LLC
Databricks, Inc.
Bright Media Corp.
Antuit Pte. Ltd.
Equivio, Ltd.
Sentient Technologies, LLC
Deep Mind Technologies, Ltd.
$49mn —
— $105mn
$54mn —
— $120mn
$59mn —
— $200mn
$104mn —
$400mn
Private M&A
7
But what are 
they doing with 
all this money?
8
Source: Thomson Reuters, Quid, iftf
Patent development is taking off
Over 7x growth in IP development from 2004 - 2013
0
50
100
150
200
250
300
350
400
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Previous ten years of patent filings
Machine Learning Patents
Source: Thomson Reuters, Quid, iftf
The IP ecosystem is diverse
Machine Learning patents across use cases
Text Classification!
Text Classification 11%
Customer Analytics 11%
Querying Methods 8%
Medical Diagnostics 7%
Data Mining 7%
Cybersecurity 6%
MRI Analysis 6%
Facial Recognition 4%
IP Deconstruction
Social Network !
Analysis!
Natural Language!
Processing!
Video Analysis!
Molecular Analysis! Querying Method!
Querying Method!
Personal Assistant!
Customer Analytics!
Cybersecurity!
Data Protection!
Semiconductors!
Data Mining!
Neural Network!
9
10
Source: Thomson Reuters, Quid, iftf
…But held by only a few players
Intellectual property not predominantly held by start-ups
Microsoft
IBM
Yahoo
Google
Nippon Telegraph & Telephone Corp
Hewlett-Packard
Behavioral Recognition Systems, Inc.
Qualcomm
Patents held %
140 9%
90 6%
59 4%
49 3%
34 2%
28 2%
24 1.5%
20 1%
11
What’s next?
12
Combinatorial Innovation
Won’t be just single technology or use case that changes game
13
Combinatorial Innovation
Won’t be just single technology or use case that changes game
14
Source: Thomson Reuters, Quid, iftf
Revisiting our patent analysis
Over 7x growth in IP development from 2004 - 2013
0
50
100
150
200
250
300
350
400
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Previous ten years of patent filings
Machine Learning Patents
15
Source: Thomson Reuters, Quid, iftf
It’s really a much bigger story…
IP development across use cases 2004 - 2013
0
100
200
300
400
500
600
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Previous ten years of patent filings
Automated Judgement Patents
Machine Learning Patents
16
Source: Thomson Reuters, Quid, iftf
Innovations build on top of each other
IP development across use cases 2004 - 2013
0
200
400
600
800
1000
1200
1400
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Previous ten years of patent filings
Computer Vision Patents
Automated Judgement Patents
Machine Learning Patents
17
Source: Thomson Reuters, Quid, iftf
To create a wide range of opportunities
IP development across use cases 2004 - 2013
0
200
400
600
800
1000
1200
1400
1600
1800
2000
2004 2005 2006 2007 2008 2009 2010 2011 2012 2013
Previous ten years of patent filings
Neural Network Patents
Computer Vision Patents
Automated Judgement Patents
Machine Learning Patents
18
Innovations overlap with one another. It won’t just be
advances in a single field that change the world or imp-
act our daily lives. It will be combinations of advances,
across fields, that do. Understanding this, helps put to-
day’s innovations into perspective for tomorrow.
19
Thank you!

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Future of AI Funding and Innovation Trends

  • 2. 2 What are the major investment trends? What’s the IP landscape look like? What’s coming next?
  • 4. 4 Source: Capital IQ, Quid, iftf Funding—where are we? Private investment growing rapidly, M&A peaked in 2012 0 2,000 4,000 6,000 8,000 10,000 12,000 14,000 16,000 18,000 20,000 2010 2011 2012 2013 2014 2015* Past five years of funding into artificial intelligence ($mn) M&A Private Investment
  • 5. 5 Source: Capital IQ, Quid, iftf How’s the market shaping up? Key investment areas since 2010 Cybersecurity! Medical 10% MapReduce 9% NLP 9% Ads 8% ERP 8% Robotics 7% Shopping 7% Computer Vision 6% Market Composition MapReduce! Natural Language! Processing! Medical! Cancer Diagnostics! Recruiting! Robotics! Computer Vision! Music! Personal Assistant! News Analysis! Ads! Shopping! Financial services! Enterprise Resource! Planning!
  • 6. 6 Source: Capital IQ, Quid, iftf Where’s it going? Notable private investments and M&A deals since 2010 Quid, Inc. ColdLight Solutions, LLC Databricks, Inc. Bright Media Corp. Antuit Pte. Ltd. Equivio, Ltd. Sentient Technologies, LLC Deep Mind Technologies, Ltd. $49mn — — $105mn $54mn — — $120mn $59mn — — $200mn $104mn — $400mn Private M&A
  • 7. 7 But what are they doing with all this money?
  • 8. 8 Source: Thomson Reuters, Quid, iftf Patent development is taking off Over 7x growth in IP development from 2004 - 2013 0 50 100 150 200 250 300 350 400 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Previous ten years of patent filings Machine Learning Patents
  • 9. Source: Thomson Reuters, Quid, iftf The IP ecosystem is diverse Machine Learning patents across use cases Text Classification! Text Classification 11% Customer Analytics 11% Querying Methods 8% Medical Diagnostics 7% Data Mining 7% Cybersecurity 6% MRI Analysis 6% Facial Recognition 4% IP Deconstruction Social Network ! Analysis! Natural Language! Processing! Video Analysis! Molecular Analysis! Querying Method! Querying Method! Personal Assistant! Customer Analytics! Cybersecurity! Data Protection! Semiconductors! Data Mining! Neural Network! 9
  • 10. 10 Source: Thomson Reuters, Quid, iftf …But held by only a few players Intellectual property not predominantly held by start-ups Microsoft IBM Yahoo Google Nippon Telegraph & Telephone Corp Hewlett-Packard Behavioral Recognition Systems, Inc. Qualcomm Patents held % 140 9% 90 6% 59 4% 49 3% 34 2% 28 2% 24 1.5% 20 1%
  • 12. 12 Combinatorial Innovation Won’t be just single technology or use case that changes game
  • 13. 13 Combinatorial Innovation Won’t be just single technology or use case that changes game
  • 14. 14 Source: Thomson Reuters, Quid, iftf Revisiting our patent analysis Over 7x growth in IP development from 2004 - 2013 0 50 100 150 200 250 300 350 400 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Previous ten years of patent filings Machine Learning Patents
  • 15. 15 Source: Thomson Reuters, Quid, iftf It’s really a much bigger story… IP development across use cases 2004 - 2013 0 100 200 300 400 500 600 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Previous ten years of patent filings Automated Judgement Patents Machine Learning Patents
  • 16. 16 Source: Thomson Reuters, Quid, iftf Innovations build on top of each other IP development across use cases 2004 - 2013 0 200 400 600 800 1000 1200 1400 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Previous ten years of patent filings Computer Vision Patents Automated Judgement Patents Machine Learning Patents
  • 17. 17 Source: Thomson Reuters, Quid, iftf To create a wide range of opportunities IP development across use cases 2004 - 2013 0 200 400 600 800 1000 1200 1400 1600 1800 2000 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Previous ten years of patent filings Neural Network Patents Computer Vision Patents Automated Judgement Patents Machine Learning Patents
  • 18. 18 Innovations overlap with one another. It won’t just be advances in a single field that change the world or imp- act our daily lives. It will be combinations of advances, across fields, that do. Understanding this, helps put to- day’s innovations into perspective for tomorrow.