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ARTIFICIAL
INTELLIGENCE
DEMYSTIFYING
ARTIFICIAL
INTELLIGENCE
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
Speaker on Bitcoin & Blockchain
Consultant at Duval Union Consulting
sam.wouters@duvalunion.com
Sam Wouters
@sdwouters
Made by
Speaker on Artificial Intelligence
‣ 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.
‣ 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
How to define AI
intelligence exhibited by machines
How to define AI
ARTIFICIAL
INTELLIGENCE
DEEP

LEARNING
MACHINE

LEARNING
A building
block of AI
A subset of
Machine Learning
Intelligence
by machines
ARTIFICIAL
INTELLIGENCE
ARTIFICIAL
INTELLIGENCE
A BRIEF HISTORY
First AI: The Staffelwalze
The first known calculator to perform all 4 operations: 

addition, subtraction, multiplication and division.
1672
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
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
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.
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
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
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
In 2016, Google’s Deepmind beat
Lee Sedol 4-1 at Go, putting AI 10
years ahead of expectations.
2016
Today AI is booming
Across all sectors
AI Funding since 2012:
$14.9 BILLION
2250 DEALS
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
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?
ARTIFICIAL
INTELLIGENCE
ARTIFICIAL
INTELLIGENCE
DEMYSTIFICATION
Human
progress
Time
Where we
think we are
Human
progress
Time
Where we
really are
Human
progress
Time
Reason #1: Projection
“This is how things went in the past, 

so that will probably continue but a bit faster”
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
It’s not about robots
It’s about the brain
3 Types of Artificial Intelligence
Artificial Narrow IntelligenceANI
Specialised in ONE area
ANI Artificial Narrow Intelligence
3 Types of Artificial Intelligence
Artificial Narrow IntelligenceANI
AGI Artificial General Intelligence
AGI
Specialised in ALL areas
Artificial General Intelligence
Our best work
in progress
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
3 Types of Artificial Intelligence
Artificial Narrow IntelligenceANI
AGI Artificial General Intelligence
ASI Artificial Super Intelligence
ASI
Smarter than humans in EVERY WAY
Artificial Super Intelligence
3 Types of Artificial Intelligence
Artificial Narrow IntelligenceANI
AGI Artificial General Intelligence
ASI Artificial Super Intelligence
ARTIFICIAL
INTELLIGENCE
ARTIFICIAL
INTELLIGENCE
IS ALL AROUND US
ANI is all around us
5 business 

applications
Google says its AI catches 99.9% of Gmail spam
Netflix uses AI to go from recommendations
based on what you’ve seen, to what you like
A 19-year-old made a
free chatbot lawyer
that has appealed 

$3m in parking tickets
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
Uber is using AI for Route optimization
ARTIFICIAL
INTELLIGENCE
ARTIFICIAL 

INTELLIGENCE
FROM ANI TO AGI
We build computers to 

process large amounts of data
= Hard to humans
Next step: things that are easy to humans
What is a cat?
What is a
human face?
Which of these is a tree?
A partially lit-up 3D rock to humans
Grey & black 2D shapes to a computer
Heavy investments to achieve AGI
“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
How to achieve AGI
CHEAPER
COMPUTER
POWER
BECOMING
SMARTER
Goal: $1000 for human brainpowerCHEAPER
COMPUTER
POWER
1015
calcs/second
20 watts of power
0.00126M3
Our best computer: $390M Tianhe-2CHEAPER
COMPUTER
POWER
1034
calcs/second
24 MW of power
2160M3
We should have enough cheap
computing power by 2025
CHEAPER
COMPUTER
POWER
How to achieve AGI
CHEAPER
COMPUTER
POWER
BECOMING
SMARTER
3 Strategies
#1 Reverse Engineering
#2 Stimulating Evolution
#3 Autonomy
BECOMING
SMARTER
#1: Reverse-EngineeringBECOMING
SMARTER
Replicating human brains in a digital way
#2: Replicating EvolutionBECOMING
SMARTER
Networks of hardware & software
learning from each others mistakes
#3: Autonomy
Letting the computer write its own rules and learn from experience
BECOMING
SMARTER
Wolfpack gameGathering game
Experts expect we’ll achieve 

AGI between 2030-2060
BECOMING
SMARTER
We could be missing 1 pieceBECOMING
SMARTER
Example: digital money
David Chaum - 1983 - Digital Cash Satoshi Nakamoto - 2008 - Bitcoin
ARTIFICIAL
INTELLIGENCE
ARTIFICIAL 

INTELLIGENCE
AGI TO ASI
AGI doesn’t existLevel 

of AI
Time
Where are are
right now
Human
intelligence
AGI
ANI
An AGI has max skills in everything
0
25
50
75
100
Programming Pricing products Catching objects Fraud detection Identifying diseases
Human AI
And it can re-engineer its brain
AGI doesn’t existLevel 

of AI
Time
<1 day
Human
intelligence
AGI
ANI
ASI
What will an AI trillions of 

times smarter than us do?
“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
But if we get it right…
Cure diseases? Solve energy problems?
Elon Musk launches Neuralink, a venture
to merge the human brain with AI
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/
Open AI’s “Universe”, a platform to train AI's 

across games, websites and other apps
ARTIFICIAL
INTELLIGENCE
ARTIFICIAL 

INTELLIGENCE
HOW TO USE ANI
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
10 building blocks of AI
COGNITIONSENSORY
PERCEPTION
MACHINE
LEARNING
DEEP
LEARNING
IMAGE
ANALYSIS
NATURAL
LANGUAGE
GENERATION
NATURAL
LANGUAGE
PROCESSING
SPEECH
RECOGNITIONROBOTICSKNOWLEDGE
ENGINEERING
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
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
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
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
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
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
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
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
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
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
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
The maturity of AI in 5 phases
Cognition
Phase 1: In research phase but not in
practical use yet
Watch for promising
future opportunities
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
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
Dealing with phase 3:
AI+Humans
Dealing with phase 3:
AI+Humans
The maturity of AI in 5 phases
Cognition
Knowledge
Engineering
Speech
Recognition
Sensory PerceptionRobotics
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
The maturity of AI in 5 phases
Cognition
Knowledge
Engineering
Speech
Recognition
Sensory PerceptionRobotics
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
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…
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
ARTIFICIAL
INTELLIGENCE
ARTIFICIAL 

INTELLIGENCE
HOW TO START BUILDING
How to start building
DEVELOPERS PLATFORMSCOMPUTING
POWERDATA
Everyone needs AI talent, build a team!
How to start building
DEVELOPERS PLATFORMSCOMPUTING
POWERDATA
You need vast amounts of training
data to perfect your algorithms
How to start building
PLATFORMSCOMPUTING
POWERDEVELOPERS DATA
You can start smaller than this :-)
How to start building
PLATFORMSCOMPUTING
POWERDEVELOPERS DATA
Platforms to get started
tensorflow.org
ibm.com/watson
deepmind.com
deeplearning.net/software/theano/
Facebook Messenger has 34.000 chatbots
Or leverage the crowd through Kaggle
Like other technology, AI is an 

open-source focused community
Get started
on the next level of business!
ARTIFICIAL
INTELLIGENCE
ARTIFICIAL 

INTELLIGENCE
WANT TO LEARN MORE?
consulting@duvalunion.com
ARTIFICIAL
INTELLIGENCE
CHECK OUR BOOK ON 

DIGITAL TRANSFORMATION
digitaltransformationbook.com
Sold in 50 countries

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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
  • 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
  • 19. AI Funding since 2012: $14.9 BILLION 2250 DEALS
  • 20.
  • 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?
  • 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 IntelligenceANI
  • 30. Specialised in ONE area ANI Artificial Narrow Intelligence
  • 31. 3 Types of Artificial Intelligence Artificial Narrow IntelligenceANI 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 IntelligenceANI 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 IntelligenceANI AGI Artificial General Intelligence ASI Artificial Super Intelligence
  • 38. ANI is all around us
  • 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
  • 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
  • 51.
  • 52. How to achieve AGI CHEAPER COMPUTER POWER BECOMING SMARTER
  • 53. Goal: $1000 for human brainpowerCHEAPER COMPUTER POWER 1015 calcs/second 20 watts of power 0.00126M3
  • 54. Our best computer: $390M Tianhe-2CHEAPER 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
  • 59. #2: Replicating EvolutionBECOMING 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 gameGathering game
  • 61. Experts expect we’ll achieve 
 AGI between 2030-2060 BECOMING SMARTER
  • 62. We could be missing 1 pieceBECOMING SMARTER
  • 63. Example: digital money David Chaum - 1983 - Digital Cash Satoshi Nakamoto - 2008 - Bitcoin
  • 65. AGI doesn’t existLevel 
 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 existLevel 
 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/
  • 74.
  • 75. Open AI’s “Universe”, a platform to train AI's 
 across games, websites and other apps
  • 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 COGNITIONSENSORY PERCEPTION MACHINE LEARNING DEEP LEARNING IMAGE ANALYSIS NATURAL LANGUAGE GENERATION NATURAL LANGUAGE PROCESSING SPEECH RECOGNITIONROBOTICSKNOWLEDGE 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 PerceptionRobotics 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 PerceptionRobotics 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
  • 100. How to start building DEVELOPERS PLATFORMSCOMPUTING POWERDATA
  • 101. Everyone needs AI talent, build a team!
  • 102. How to start building DEVELOPERS PLATFORMSCOMPUTING POWERDATA
  • 103. You need vast amounts of training data to perfect your algorithms
  • 104. How to start building PLATFORMSCOMPUTING POWERDEVELOPERS DATA
  • 105. You can start smaller than this :-)
  • 106. How to start building PLATFORMSCOMPUTING POWERDEVELOPERS 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 WANT TO LEARN MORE? consulting@duvalunion.com
  • 113. ARTIFICIAL INTELLIGENCE CHECK OUR BOOK ON 
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