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The Era of Artificial Intelligence
Lecture 2
Pietro Leo
IBM Italy Executive Architect and thought leader for Artificial Intelligence
Chief Scientist for IBM Italy Research & Business
IBM Academy of Technology Leadership
Member of ISO/SC42 Artificial Intelligence Standardization Committee
www.pieroleo.com

@pieroleo
How relevant is
Artificial
Intelligence for
the business
and research,
today?

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www.mckinsey.comVenture Scanner
mckinsey

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https://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/the-executives-ai-playbook?page=industries/

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Source: https://www.cognilytica.com/2019/01/16/cognilyticas-classification-of-the-ai-vendor-ecosystem-overview-
and-bottom-3-layers/ :: 4 layers, 40 categories, 100 sub categories. A sample of 3.000 AI companies.
700
1.500
3.000+
300
AIVendors

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7
How did China rapidly rise to be un AI superpower?

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8Source: https://www.nytimes.com/2018/11/25/business/china-artificial-intelligence-labeling.html
Workers at the
headquarters of Ruijin
Technology Company
in Jiaxian, in central
China’s Henan
Province. They
identify objects in
images to help
artificial intelligence
make sense of the
world.
CreditCreditYan Cong
for The New York
Times

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9
Hungry to Learn: There is a
constant growing interest
around Artificial
Intelligence
2013 – 138 students
2016 – 302 students
2017 – 700 students
2018 – 839 students
2019 – 984 students

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10
Source: https://www.timeshighereducation.com/data-bites/which-countries-and-universities-are-leading-ai-research
Volume of publications, China is leading
Source: Elsevier/Scopus
Country Publications
Field-weighted
citation impact
Switzerland 1,685 2.71
Singapore 2,432 2.24
Hong Kong 2,205 2.00
United States 25,471 1.79
Italy 6,221 1.74
Although, volume sometimes doesn’t
correspond to the quality
Which countries and universities are leading on AI
research?
Source: TimesHighereducation

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11
AI: Back to
the basic,
now!

@pieroleo
ALGORITHMS PROBLEMSDATACOMPUTING
High
Complexity
Low
Complexity
ANALOG
DIGITAL
HW Acceleration
QUANTUM
NUMBERS
INFORMATION
KNOWLEDGE
DATA WISDOM
2+2=4
DGITAL
TRANSFORMATON
CO-WORK WITH
MACHINES
PROCEDURAL
PROGRAM
SUPERVISED
UNSUPERVISED
REASONING
REINFORCED
Symbiotic
OPTIMIIZE AN
ENGENEERING
DECISION
ACTIVE PRODUCTS ANDSERVICES
NEW PROBLEMS
Stack of Dimensions of Digital Systems and their growing
complexity

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ALGORITHMS PROBLEMSDATACOMPUTING
High
Complexity
Low
Complexity
From a business perspective AI is THE ingredient that can push the
genetic evolution of IT from the status of a tool to a generalized
business problem solving environment
ANALOG
DIGITAL
ACCELERATED
NUMBERS
INFORMATION
KNOWLEDGE
2+2=4
DGITAL
TRANSFORMATON
CO-WORK WITH
MACHINES
PROGRAM
SUPERVISED
UNSUPERVISED
REASONING
REINFORCED
AI
REEF
QUANTUM
Symbiotic
OPTIMIIZE AN
ENGENEERING
DECISION
ACTIVE PRODUCTS ANDSERVICES
NEW PROBLEMS
SMART DATA

@pieroleo
ALGORITHMS PROBLEMSDATACOMPUTING
High
Complexity
Low
Complexity
We require systems that interact in behaviors and
processes
ANALOG
DIGITAL
ACCELERATED
NUMBERS
INFORMATION
KNOWLEDGE
2+2=4
DGITAL
TRANSFORMATON
CO-WORK WITH
MACHIN<ES
PROGRAM
SUPERVISED
UNSUPERVISED
REASONING
REINFORCEDQUANTUM
Symbiotic
OPTIMIIZE AN
ENGENEERING
DECISION
ACTIVE PRODUCTS ANDSERVICES
NEW PROBLEMS
SMART DATA
Dynamic or Active systems
Static or Passive systems
AI
REEF
(Take decisions in presence of uncertainly or lack of data)

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Hic sunt leones

@pieroleo
ALGORITHMS PROBLEMSDATACOMPUTING
High
Complexity
Low
Complexity
ANALOG
DIGITAL
ACCELERATED
QUANTUM
NUMBERS
INFORMATION
KNOWLEDGE
WISDOM
PROGRAM
SUPERVISE
AND TRAIN A
MACHINE
MACHINE LEARNS
WITHOUT A
TRAINING
2+2=4
ASK FOR A LOAN
DGITALTRANSFORMATON
CO-WORK WITH
MACHINES
TALK WITH A DIGITALHUMAN
AI
REEF
AI isn’t magic — it’s a lot of hard work!
Here there are lions

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Thanks!
Pietro Leo
IBM Italy Executive Architect and thought leader for Artificial Intelligence
Chief Scientist for IBM Italy Research & Business
IBM Academy of Technology Leadership
Member of ISO/SC42 Artificial Intelligence Standardization Committee
www.pieroleo.com