Many questions arise around this topic: What is Artificial Intelligence and what isn't? What is possible today? How can my organisation use AI? Will this replace my job? What can we expect in the future?
We will answer these and more in our presentation. We help you understand the impact of digital on your business and give you concrete steps to start taking action.
2. 3 Goals of this presentation
#1 Introduce you to Artiļ¬cial 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 Artiļ¬cial Intelligence
4. ā£ We are a digital consulting company.
ā£ Founded in 2009.
ā£ We work for large clients across all
sectors.
ā£ We have a strong vision on the impact
of digital and act accordingly.
ā£ We are advisors, writers, coaches and
entrepreneurs.
5. ā£ Slide 8-22: A brief history of Artiļ¬cial Intelligence
ā£ Slide 23-36: Demystiļ¬cation
ā£ Slide 37-44: AI is all around us
ā£ Slide 45-63: Going from ANI to AGI
ā£ Slide 64-75: Going from AGI to ASI
ā£ Slide 76-98: How to use ANI
ā£ Slide 99-110: How to start building
Table of contents
7. How to deļ¬ne AI
ARTIFICIAL
INTELLIGENCE
DEEPāØ
LEARNING
MACHINEāØ
LEARNING
A building
block of AI
A subset of
Machine Learning
Intelligence
by machines
9. First AI: The Staļ¬elwalze
The ļ¬rst known calculator to perform all 4 operations: āØ
addition, subtraction, multiplication and division.
1672
10. In the 1940s the ChurchāTuring 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 canāt ļ¬gure 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
difļ¬culty 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, IBMās
Deep Blue beat Garry Kasparov, the
reigning world champion at chess.
1990s
15. In 2011 IBMās Watson beat Ken Jennings and Brad Rutter in the
TV Quiz Jeopardy, the ļ¬rst sign of AI beating people at non-math.
1990s
16. In 2016, Googleās Deepmind beat
Lee Sedol 4-1 at Go, putting AI 10
years ahead of expectations.
2016
21. MORE DATA &
RESEARCH
Why now?
ERROR RATES
ARE FALLING
CHEAP NEURAL
NETWORKS
ā2015 was a landmark year for AI, with software projects using AI at
Google increasing from āsporadic usageā in 2012 to over 2700 projects.ā
āØ
~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?
41. Netļ¬ix uses AI to go from recommendations
based on what youāve seen, to what you like
42. A 19-year-old made a
free chatbot lawyer
that has appealed āØ
$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
50. āI truly believe the computing Singularity
is coming, thatās why Iām in a hurry ā āØ
to aggregate the cash, to invest.ā
~Softbank CEO Masayoshi Son āØ
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
69. What will an AI trillions of āØ
times smarter than us do?
70. āAI is likely to be either the best or
worst thing ever to happen to
humanity.ā ~Stephen Hawking
āIf I had to guess at what our
biggest existential threat is, it's
probably AI.ā ~Elon Musk
āWhen a few people control a
platform with extreme intelligence,
it creates dangers in terms of
power and control.ā ~Bill Gates
71. But if we get it rightā¦
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 beneļ¬cial Artiļ¬cial Intelligence
The potential beneļ¬ts (of AI) are huge, since everything that
civilization has to oļ¬er is a product of human intelligence; we
cannot predict what we might achieve when this intelligence is
magniļ¬ed 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 beneļ¬ts while avoiding potential pitfalls.
futureoļ¬ife.org/ai-open-letter/
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,ā¦ 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. āØ
Popular examples are Appleās Siri, Google Now and Amazonās 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 ļ¬nancial markets, to analyse product reviews, monitor social media,ā¦
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 AIās 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 identiļ¬es 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,ā¦ 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 artiļ¬cial brain to handle large amounts of data.
Deep learning is a branch of machine learning that focuses on algorithms to create
artiļ¬cial neural networks. These networks are more efļ¬cient 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 canāt tell AI apart from other humans.
Cognitive applications have a mind of their own and are able to perceive, āØ
interact, learn, act and evolve by themselves. Cognition is a missing piece that, āØ
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 āØ
Learning
ImageāØ
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 āØ
Learning
ImageāØ
Analysis
Natural Language
Generation
Speech
Recognition
Natural Language
Processing
Machine
Learning
Adds some value for
your business today
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 āØ
Learning
ImageāØ
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 āØ
Learning
ImageāØ
Analysis
Natural Language
Generation
Natural Language
Processing
Machine
Learning
Doesnāt 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 applicationsā¦