Demystifying 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

20. 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

21. 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?

22. ARTIFICIAL INTELLIGENCE ARTIFICIAL INTELLIGENCE DEMYSTIFICATION

23. Human progress Time Where we think we are

24. Human progress Time Where we really are

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

26. 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

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

28. 3 Types of Artiﬁcial Intelligence Artiﬁcial Narrow IntelligenceANI

29. Specialised in ONE area ANI Artiﬁcial Narrow Intelligence

30. 3 Types of Artificial Intelligence Artificial Narrow IntelligenceANI AGI Artificial General Intelligence

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

32. 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

33. 3 Types of Artificial Intelligence Artificial Narrow IntelligenceANI AGI Artificial General Intelligence ASI Artificial Super Intelligence

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

35. 3 Types of Artificial Intelligence Artificial Narrow IntelligenceANI AGI Artificial General Intelligence ASI Artificial Super Intelligence

36. ARTIFICIAL INTELLIGENCE ARTIFICIAL INTELLIGENCE IS ALL AROUND US

37. ANI is all around us

38. 5 business   applications

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

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

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

42. 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

43. Uber is using AI for Route optimization

44. ARTIFICIAL INTELLIGENCE ARTIFICIAL   INTELLIGENCE FROM ANI TO AGI

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

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

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

48. Heavy investments to achieve AGI

49. “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

50. How to achieve AGI CHEAPER COMPUTER POWER BECOMING SMARTER

51. Goal: $1000 for human brainpowerCHEAPER COMPUTER POWER 1015 calcs/second 20 watts of power 0.00126M3

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

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

54. How to achieve AGI CHEAPER COMPUTER POWER BECOMING SMARTER

55. 3 Strategies #1 Reverse Engineering #2 Stimulating Evolution #3 Autonomy BECOMING SMARTER

56. #1: Reverse-EngineeringBECOMING SMARTER Replicating human brains in a digital way

57. #2: Replicating EvolutionBECOMING SMARTER Networks of hardware & software learning from each others mistakes

58. #3: Autonomy Letting the computer write its own rules and learn from experience BECOMING SMARTER Wolfpack gameGathering game

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

60. We could be missing 1 pieceBECOMING SMARTER

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

62. ARTIFICIAL INTELLIGENCE ARTIFICIAL   INTELLIGENCE AGI TO ASI

63. AGI doesn’t existLevel   of AI Time Where are are right now Human intelligence AGI ANI

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

65. And it can re-engineer its brain

66. AGI doesn’t existLevel   of AI Time <1 day Human intelligence AGI ANI ASI

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

68. “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

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

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

71. 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/

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

73. ARTIFICIAL INTELLIGENCE ARTIFICIAL   INTELLIGENCE HOW TO USE ANI

74. 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

75. 10 building blocks of AI COGNITIONSENSORY PERCEPTION MACHINE LEARNING DEEP LEARNING IMAGE ANALYSIS NATURAL LANGUAGE GENERATION NATURAL LANGUAGE PROCESSING SPEECH RECOGNITIONROBOTICSKNOWLEDGE ENGINEERING

76. 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

77. 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

78. 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

79. 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

80. 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

81. 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

82. 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

83. 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

84. 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

85. 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

86. 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

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

88. 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

89. 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

90. Dealing with phase 3: AI+Humans

91. Dealing with phase 3: AI+Humans

92. 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

93. 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

94. 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…

95. 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

96. ARTIFICIAL INTELLIGENCE ARTIFICIAL   INTELLIGENCE HOW TO START BUILDING

97. How to start building DEVELOPERS PLATFORMSCOMPUTING POWERDATA

98. Everyone needs AI talent, build a team!

99. How to start building DEVELOPERS PLATFORMSCOMPUTING POWERDATA

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

101. How to start building PLATFORMSCOMPUTING POWERDEVELOPERS DATA

102. You can start smaller than this :-)

103. How to start building PLATFORMSCOMPUTING POWERDEVELOPERS DATA

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

105. Facebook Messenger has 34.000 chatbots

106. Or leverage the crowd through Kaggle

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

108. Get started on the next level of business!

109. ARTIFICIAL INTELLIGENCE ARTIFICIAL   INTELLIGENCE WANT TO LEARN MORE? consulting@duvalunion.com

110. ARTIFICIAL INTELLIGENCE CHECK OUR BOOK ON   DIGITAL TRANSFORMATION digitaltransformationbook.com Sold in 50 countries

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