artificial intelligence

1. ARTIFICIAL
INTELLIGENCE
DEMYSTIFYING
ARTIFICIAL
INTELLIGENCE

2. 3 Goals of this presentation
#1 Introduce you to Artificial Intelligence
#2 Provide a high-level overview of today & tomorrow
#3 Help organisations get started with AI

3. Speaker on Bitcoin & Blockchain
Consultant at Duval Union Consulting
sam.wouters@duvalunion.com
Sam Wouters
@sdwouters
Made by
Speaker on Artificial Intelligence

4. ‣ We are a digital consulting company.
‣ Founded in 2009.
‣ We work for large clients across all
sectors.
‣ We have a strong vision on the impact
of digital and act accordingly.
‣ We are advisors, writers, coaches and
entrepreneurs.

5. ‣ Slide 8-22: A brief history of Artificial Intelligence
‣ Slide 23-36: Demystification
‣ Slide 37-44: AI is all around us
‣ Slide 45-63: Going from ANI to AGI
‣ Slide 64-75: Going from AGI to ASI
‣ Slide 76-98: How to use ANI
‣ Slide 99-110: How to start building
Table of contents

6. How to define AI
intelligence exhibited by machines

7. How to define AI
ARTIFICIAL
INTELLIGENCE
DEEP
LEARNING
MACHINE
LEARNING
A building
block of AI
A subset of
Machine Learning
Intelligence
by machines

8. ARTIFICIAL
INTELLIGENCE
ARTIFICIAL
INTELLIGENCE
A BRIEF HISTORY

9. First AI: The Staffelwalze
The first known calculator to perform all 4 operations:
addition, subtraction, multiplication and division.
1672

10. In the 1940s the Church–Turing thesis was created. It
suggested that digital computers can simulate any
process of formal reasoning and led researchers to
consider the possibility of building an electronic brain.
1940s

11. AI started getting developed by philosophers and
mathematicians in the 19th century. Alan Turing is
one of the best known founding fathers of modern AI.
1950s

12. INTERVIEWER
PERSON AI
The interviewer has a limited
amount of time to ask
questions to the other rooms.
An interviewer, a person and an
AI get put in 3 different rooms.
They communicate through text.
If the interviewer can’t figure out
who is human before time is up,
the AI passes the Turing Test.

13. AI research was founded at
Dartmouth College in 1956.
The founders and their students wrote
astonishing programs that were
winning at checkers, solving word
problems in algebra, proving logical
theorems and speaking English.
They expected to have pure AI within
twenty years, but underestimated the
difficulty and in 1974 all funding was
cut off from AI research.
1956-74 Founding of AI & practice

14. After a few more attempts at revival,
AI began to be used more in the 90s
in all kinds of areas. In 1997, IBM’s
Deep Blue beat Garry Kasparov, the
reigning world champion at chess.
1990s

15. In 2011 IBM’s Watson beat Ken Jennings and Brad Rutter in the
TV Quiz Jeopardy, the first sign of AI beating people at non-math.
1990s

16. In 2016, Google’s Deepmind beat
Lee Sedol 4-1 at Go, putting AI 10
years ahead of expectations.
2016

17. Today AI is booming

18. Across all sectors

19. AI Funding since 2012:
$14.9 BILLION
2250 DEALS

21. MORE DATA &
RESEARCH
Why now?
ERROR RATES
ARE FALLING
CHEAP NEURAL
NETWORKS
“2015 was a landmark year for AI, with software projects using AI at
Google increasing from ‘sporadic usage’ in 2012 to over 2700 projects.”
~Jack Clark, Strategy & Communications Director at OpenAI

22. Why does AI matter?
OUR LIVES
OUR BUSINESSES OUR SOCIETY
How will AI impact our purpose?
How will AI change our businesses? How will AI impact our workforce?

23. ARTIFICIAL
INTELLIGENCE
ARTIFICIAL
INTELLIGENCE
DEMYSTIFICATION

24. Human
progress
Time
Where we
think we are

25. Human
progress
Time
Where we
really are

26. Human
progress
Time
Reason #1: Projection
“This is how things went in the past,
so that will probably continue but a bit faster”

27. Human
progress
Time
1. Experimentation
2. Exponential growth
3. Level off
Reason #2:
Innovation happens in phases
1 2
3 1
2
3
1995-2007
2008-2015

28. It’s not about robots
It’s about the brain

29. 3 Types of Artificial Intelligence
Artificial Narrow Intelligence
ANI

30. Specialised in ONE area
ANI Artificial Narrow Intelligence

31. 3 Types of Artificial Intelligence
Artificial Narrow Intelligence
ANI
AGI Artificial General Intelligence

32. AGI
Specialised in ALL areas
Artificial General Intelligence
Our best work
in progress

33. AGI
7 ABILITIES:
1. Reason
2. Plan
3. Solve problems
4. Think abstractly
5. Comprehend complex ideas
6. Learn quickly
7. Learn from experience
Artificial General Intelligence

34. 3 Types of Artificial Intelligence
Artificial Narrow Intelligence
ANI
AGI Artificial General Intelligence
ASI Artificial Super Intelligence

35. ASI
Smarter than humans in EVERY WAY
Artificial Super Intelligence

36. 3 Types of Artificial Intelligence
Artificial Narrow Intelligence
ANI
AGI Artificial General Intelligence
ASI Artificial Super Intelligence

37. ARTIFICIAL
INTELLIGENCE
ARTIFICIAL
INTELLIGENCE
IS ALL AROUND US

38. ANI is all around us

39. 5 business
applications

40. Google says its AI catches 99.9% of Gmail spam

41. Netflix uses AI to go from recommendations
based on what you’ve seen, to what you like

42. A 19-year-old made a
free chatbot lawyer
that has appealed
$3m in parking tickets

43. Identifying diseases by comparing huge amounts of data
Freenome, a startup focused on detecting
cancer through AI, set up by a 28-year
old, landed a $65 million investment by
Andreessen Horowitz & Google Ventures

44. Uber is using AI for Route optimization

45. ARTIFICIAL
INTELLIGENCE
ARTIFICIAL
INTELLIGENCE
FROM ANI TO AGI

46. We build computers to
process large amounts of data
= Hard to humans

47. Next step: things that are easy to humans
What is a cat?
What is a
human face?
Which of these is a tree?

48. A partially lit-up 3D rock to humans
Grey & black 2D shapes to a computer

49. Heavy investments to achieve AGI

50. “I truly believe the computing Singularity
is coming, that’s why I’m in a hurry –
to aggregate the cash, to invest.”
~Softbank CEO Masayoshi Son
on their $100B tech fund

52. How to achieve AGI
CHEAPER
COMPUTER
POWER
BECOMING
SMARTER

53. Goal: $1000 for human brainpower
CHEAPER
COMPUTER
POWER
1015
calcs/second
20 watts of power
0.00126M3

54. Our best computer: $390M Tianhe-2
CHEAPER
COMPUTER
POWER
1034
calcs/second
24 MW of power
2160M3

55. We should have enough cheap
computing power by 2025
CHEAPER
COMPUTER
POWER

56. How to achieve AGI
CHEAPER
COMPUTER
POWER
BECOMING
SMARTER

57. 3 Strategies
#1 Reverse Engineering
#2 Stimulating Evolution
#3 Autonomy
BECOMING
SMARTER

58. #1: Reverse-Engineering
BECOMING
SMARTER
Replicating human brains in a digital way

59. #2: Replicating Evolution
BECOMING
SMARTER
Networks of hardware & software
learning from each others mistakes

60. #3: Autonomy
Letting the computer write its own rules and learn from experience
BECOMING
SMARTER
Wolfpack game
Gathering game

61. Experts expect we’ll achieve
AGI between 2030-2060
BECOMING
SMARTER

62. We could be missing 1 piece
BECOMING
SMARTER

63. Example: digital money
David Chaum - 1983 - Digital Cash Satoshi Nakamoto - 2008 - Bitcoin

64. ARTIFICIAL
INTELLIGENCE
ARTIFICIAL
INTELLIGENCE
AGI TO ASI

65. AGI doesn’t exist
Level
of AI
Time
Where are are
right now
Human
intelligence
AGI
ANI

66. An AGI has max skills in everything
0
25
50
75
100
Programming Pricing products Catching objects Fraud detection Identifying diseases
Human AI

67. And it can re-engineer its brain

68. AGI doesn’t exist
Level
of AI
Time
<1 day
Human
intelligence
AGI
ANI
ASI

69. What will an AI trillions of
times smarter than us do?

70. “AI is likely to be either the best or
worst thing ever to happen to
humanity.” ~Stephen Hawking
“If I had to guess at what our
biggest existential threat is, it's
probably AI.” ~Elon Musk
“When a few people control a
platform with extreme intelligence,
it creates dangers in terms of
power and control.” ~Bill Gates

71. But if we get it right…
Cure diseases? Solve energy problems?

72. Elon Musk launches Neuralink, a venture
to merge the human brain with AI

73. An Open Letter
Research priorities for robust and beneficial Artificial Intelligence
The potential benefits (of AI) are huge, since everything that
civilization has to offer is a product of human intelligence; we
cannot predict what we might achieve when this intelligence is
magnified by the tools AI may provide, but the eradication of
disease and poverty are not unfathomable.
Because of the great potential of AI, it is important to research
how to reap its benefits while avoiding potential pitfalls.
futureoflife.org/ai-open-letter/

75. Open AI’s “Universe”, a platform to train AI's
across games, websites and other apps

76. ARTIFICIAL
INTELLIGENCE
ARTIFICIAL
INTELLIGENCE
HOW TO USE ANI

77. How to use ANI
There are 10 building blocks in AI
COGNITION
SENSORY
PERCEPTION
MACHINE
LEARNING
DEEP
LEARNING
IMAGE
ANALYSIS
NATURAL
LANGUAGE
GENERATION
NATURAL
LANGUAGE
PROCESSING
SPEECH
RECOGNITION
ROBOTICS
KNOWLEDGE
ENGINEERING

78. 10 building blocks of AI
COGNITION
SENSORY
PERCEPTION
MACHINE
LEARNING
DEEP
LEARNING
IMAGE
ANALYSIS
NATURAL
LANGUAGE
GENERATION
NATURAL
LANGUAGE
PROCESSING
SPEECH
RECOGNITION
ROBOTICS
KNOWLEDGE
ENGINEERING

79. 10 building blocks of AI
A process to understand and represent human knowledge in data structures.
Knowledge Engineering can be used in applications to solve complex problems that
are generally associated with human expertise. IBM Watson Health uses engineered
knowledge in combination with over 290 medical journals, textbooks, and drug
databases to help oncologists choose the best treatment for their patients.
KNOWLEDGE
ENGINEERING

80. 10 building blocks of AI
A physical manifestation of an AI, allowing it to interact with the physical world.
Robots are mostly used to automate repetitive tasks in controlled manufacturing
environments across all industries. Applications are things such as transporting
goods, assembling products, quality checks, sorting objects,… Amazon employs
over 45.000 logistic robots in its warehouses and Tesla has a fully automated factory.
ROBOTICS

81. 10 building blocks of AI
A process to convert speech to text, to allow AI to listen to the physical world.
Speech recognition can be used to allow applications to take commands from
humans, to transcribe conversations or even participate in them.
Popular examples are Apple’s Siri, Google Now and Amazon’s Alexa.
SPEECH
RECOGNITION

82. 10 building blocks of AI
A process to understand the meaning of words in text.
Natural Language Processing can be used to analyse any text to extract topics,
sentiment, meaning and ultimately to gain knowledge. It is used to read the
sentiment in financial markets, to analyse product reviews, monitor social media,…
NATURAL
LANGUAGE
PROCESSING

83. 10 building blocks of AI
A process to express stored information in an understandable way for humans.
Natural Language Generation is the opposite of NL Processing. It allows AI’s to
communicate back to humans about the information they processed. It is mostly
used in virtual personal assistants such as Siri, Google Now and Alexa, but also in
customer service chatbots.
NATURAL
LANGUAGE
GENERATION

84. 10 building blocks of AI
Converts objects to text, to allow AI to see the physical world.
A technology that identifies and understands what can be seen in images and video.
It assigns labels to objects and situations. Best known applications of Image Analysis
are facial recognition, quality controls and self-driving technology.
IMAGE
ANALYSIS

85. 10 building blocks of AI
Machine Learning consists of tools and algorithms to analyze data.
Machine learning can be used in a large variety of ways, such as predictions,
identifying patterns, recommendations,… Today it is used to better detect diseases,
recommend content, improve products and services and many other applications.
MACHINE
LEARNING

86. 10 building blocks of AI
The creation of an artificial brain to handle large amounts of data.
Deep learning is a branch of machine learning that focuses on algorithms to create
artificial neural networks. These networks are more efficient at handling data at large
scale and are used by large Internet companies to organise information, analyse and
predict behaviour, improve search and products & services and more.
DEEP
LEARNING

87. 10 building blocks of AI
A process to convert physical characteristics to text to provide context.
Sensors measure and collect information about people, places and all kinds of
objects to provide context. Examples of this are location, weather, sound, presence,
volume and pressure. Sensory perception is used to predict equipment or material
failures before they happen, so maintenance can be adjusted to it.
SENSORY
PERCEPTION

88. 10 building blocks of AI
Turing-complete applications, where we can’t tell AI apart from other humans.
Cognitive applications have a mind of their own and are able to perceive,
interact, learn, act and evolve by themselves. Cognition is a missing piece that,
in combination with the other building blocks, will create pure AI.
COGNITION

89. How to use ANI
There are 10 building blocks in AI
COGNITION
SENSORY
PERCEPTION
MACHINE
LEARNING
DEEP
LEARNING
IMAGE
ANALYSIS
NATURAL
LANGUAGE
GENERATION
NATURAL
LANGUAGE
PROCESSING
SPEECH
RECOGNITION
ROBOTICS
KNOWLEDGE
ENGINEERING
5 maturity phases
Phase 1: In research phase but not in practical use yet
Phase 2: Used in commercial applications but not accurate and consistent enough
Phase 3: Accurate enough for applications, but still has technical challenges to overcome
Phase 4: Has overcome the challenges in phase 3 but requires perfection
Phase 5: Pure AI, indistinguishable from human intelligence

90. The maturity of AI in 5 phases
Cognition
Phase 1: In research phase but not in
practical use yet
Watch for promising
future opportunities

91. The maturity of AI in 5 phases
Cognition
Phase 1: In research phase but not in
practical use yet
Phase 2: Used in commercial applications
but not accurate and consistent enough
Knowledge
Engineering
Deep
Learning
Image
Analysis
Natural Language
Generation
Pioneering a market
before the value is created

92. The maturity of AI in 5 phases
Cognition
Phase 1: In research phase but not in
practical use yet
Phase 2: Used in commercial applications
but not accurate and consistent enough
Phase 3: Accurate enough for
applications, but still has technical
challenges to overcome
Knowledge
Engineering
Deep
Learning
Image
Analysis
Natural Language
Generation
Speech
Recognition
Natural Language
Processing
Machine
Learning
Adds some value for
your business today

93. Dealing with phase 3:
AI+Humans

94. Dealing with phase 3:
AI+Humans

95. The maturity of AI in 5 phases
Cognition
Knowledge
Engineering
Speech
Recognition
Sensory Perception
Robotics
Phase 1: In research phase but not in
practical use yet
Phase 2: Used in commercial applications
but not accurate and consistent enough
Phase 3: Accurate enough for
applications, but still has technical
challenges to overcome
Phase 4: Has overcome the challenges in
phase 3 but requires perfection
Deep
Learning
Image
Analysis
Natural Language
Generation
Natural Language
Processing
Machine
Learning
Adds serious value for
your business today

96. The maturity of AI in 5 phases
Cognition
Knowledge
Engineering
Speech
Recognition
Sensory Perception
Robotics
Phase 1: In research phase but not in
practical use yet
Phase 2: Used in commercial applications
but not accurate and consistent enough
Phase 3: Accurate enough for
applications, but still has technical
challenges to overcome
Phase 4: Has overcome the challenges in
phase 3 but requires perfection
Phase 5: Pure AI, indistinguishable from
human intelligence
Deep
Learning
Image
Analysis
Natural Language
Generation
Natural Language
Processing
Machine
Learning
Doesn’t exist yet

97. How to use ANI
There are 10 building blocks in AI
COGNITION
SENSORY
PERCEPTION
MACHINE
LEARNING
DEEP
LEARNING
IMAGE
ANALYSIS
NATURAL
LANGUAGE
GENERATION
NATURAL
LANGUAGE
PROCESSING
SPEECH
RECOGNITION
ROBOTICS
KNOWLEDGE
ENGINEERING
5 maturity phases
Phase 1: In research phase but not in practical use yet
Phase 2: Used in commercial applications but not accurate and consistent enough
Phase 3: Accurate enough for applications, but still has technical challenges to overcome
Phase 4: Has overcome the challenges in phase 3 but requires perfection
Phase 5: Pure AI, indistinguishable from human intelligence
And countless applications…

98. SENSORY
PERCEPTION
ROBOTICS
SPEECH
RECOGNITION
SENSORY
PERCEPTION
NATURAL
LANGUAGE
PROCESSING
NATURAL
LANGUAGE
GENERATION
KNOWLEDGE
ENGINEERING
NATURAL
LANGUAGE
PROCESSING
IMAGE
ANALYSIS
MACHINE
LEARNING
IMAGE
ANALYSIS
DEEP
LEARNING
A few ANI applications
Do you repetitively deal with physical objects?
e.g. moving objects, translating physical to digital, maintenance
Are there interfaces you can improve?
e.g. chatbots, voice commands, face detection
Do you need data to be analysed?
e.g. categorisation, predictions, recommendations

99. ARTIFICIAL
INTELLIGENCE
ARTIFICIAL
INTELLIGENCE
HOW TO START BUILDING

100. How to start building
DEVELOPERS PLATFORMS
COMPUTING
POWER
DATA

101. Everyone needs AI talent, build a team!

102. How to start building
DEVELOPERS PLATFORMS
COMPUTING
POWER
DATA

103. You need vast amounts of training
data to perfect your algorithms

104. How to start building
PLATFORMS
COMPUTING
POWER
DEVELOPERS DATA

105. You can start smaller than this :-)

106. How to start building
PLATFORMS
COMPUTING
POWER
DEVELOPERS DATA

107. Platforms to get started
tensorflow.org
ibm.com/watson
deepmind.com
deeplearning.net/software/theano/

108. Facebook Messenger has 34.000 chatbots

109. Or leverage the crowd through Kaggle

110. Like other technology, AI is an
open-source focused community

111. Get started
on the next level of business!

112. ARTIFICIAL
INTELLIGENCE
ARTIFICIAL
INTELLIGENCE
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113. ARTIFICIAL
INTELLIGENCE
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