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1. BIYour C ompany N ame

2. Agenda
2
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Agenda
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Agenda

3. Artificial
Intelligence
outline
01 Artificial Intelligence Introduction
02 Artificial Intelligence Objectives
03 Artificial Intelligence Components
04
Artificial Intelligence Key Statistics
05 Reasons For Using Artificial Intelligence
06 Survey on Adoption of Emerging Technologies
07 Artificial Intelligence & Investment by Sector
08 Artificial Intelligence In Various Sectors
09
Driving Force Behind Artificial Intelligence Maturity
10
Core Areas of Artificial Intelligence
11 Artificial Intelligence Value Chain Elements
12 Artificial Intelligence Development Phases
14
Artificial Intelligence Approaches
• Logic & Rules-based Approach
• Machine Learning (Pattern Based)
15 Machine Learning Description
16 Machine Learning Process
13 Artificial Intelligence Themes
17 Machine Learning Use Cases
18
Artificial Narrow Intelligence Vs Artificial
General Intelligence
19 Potential Use Cases of AI In Healthcare
20 Challenges In Adoption of Artificial
Intelligence
3

4. Artificial Intelligence Introduction 4
AI Technologies
Computer Vision
Audio Processing
Sense
Natural Language Processing
Knowledge Representation
Comprehend
Machine Learning
Expert Systems
Act
Illustrative Solutions
Data Visualization
Recommendation Systems
Speech Analytics
Cognitive Robotics
Identity Analytics
Virtual Agents

5. Artificial
Intelligence
Objectives
Achieve the
objectives of
company XX by 2020
Make company XX the
first in the field of AI
investments in
various sectors
Boost organizational
Performance at all levels
Text here
Use an integrated smart
digital system that can
overcome challenges and
provide quick efficient
solutions
Text here
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5

6. Artificiel Intelligence Components Template 1 6
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Strategy
• Aligning with strategic
goals
• Text Here
Development
• Iterative development
• Managing data
dependency
Design
• Software design is
transparent & auditable
• Text here
Operating Model
• Data as your key intellectual
property
• Text here

7. Data
• Pay per Click
• Search console data
• Customer service Transcripts
• Social feedback
Technology
• AI Analytical Engine
• Interface for data upload
Strategy
• Select optimal AI Engine
• Instruct AI Engine
• Create a training strategy
Artificiel Intelligence Components Template 2 7

8. Artificial Intelligence Key Statistics 8
65%
Two- third of senior
decision- makers agree
that AI is fundamental to
the success of their
organization’s strategy
45%
By 2022, those currently
or planning to use AI
technology anticipate a 39%
boost to their organization’s
revenue, on average
69%
7 in 10 organizations that
have replaced, or plan to
replace, roles with technology
will retain or redeploy those
who are displaced
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9. Reasons for Using Artificial Intelligence 9
Automated data- driven reporting
All of the above Automated
data-driven reporting
Automation that eliminates manual
and repetitive tasks
Other
Automated Communications that
give consumers data they can use to
effective decisions
Monitoring and alerts about the
health of the business
Automated communications that give firms data
they can use to make effective business decisions
9%
16%
15%
25%
8% 10%
17%
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10. Survey on Adoption of Emerging Technologies 10
65%
57%
45%
40%
38%
35%
32%
28%
23%
0%
20%
40%
60%
80%
IoT/ Smart Sensors Artificial Intelligence Blockchain AR/VR Robotics/Autonomous
Robots
3D Printing Autonomous Vehicles Wearables Text Here
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11. Artificial Intelligence & Investment by sector 11
Travel & Tourism
Construction
Education
Automotive & Assembly
Transportation & Logistics
Financial Services
Media & Entertainment
Energy & Resources
Professional Services
Healthcare
Retail
Consumer packed Goods
High tech & Telecommunication
0
2
4
6
8
10
12
14
0 5 10 15 20 25 30
Falling Behind
Leading Sectors
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12. Artificial
Intelligence in
various Sectors
To reduce accidents and cut operational costs
Transport
To minimize chronic and dangerous diseases
Health
To conduct analysis and studies to provide water
sources
Water
To increase productivity and help with general spending
Technology
To increase forestation rate
Environment
To reduce accidents & traffic jams & draw more
effective traffic policies
Traffic
12

13. Driving Force behind Artificial Intelligence Maturity 13
This graph/chart is linked to excel, and changes automatically based on data. Just left click on it and select “Edit Data”.
80%
60%
45%
40%
30%
25%
15%
0%
20%
40%
60%
80%
IoT/ Smart Sensors Artificial Intelligence Blockchain AR/VR Robotics/Autonomous Robots 3D Printing Autonomous Vehicles

14. Core Areas of Artificial Intelligence 14
High precision learning
from small data sets
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Research On New
Algorithms
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Explainable
AI
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General
AI
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Cognitive AI such
as worker training
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Physical AI Like
Industrial Automation
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Sensory AI such as
Internet of Things
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15. Artificiel Intelligence
Value Chain Eléments
15
Data
Capture
Cleansing of
raw data
Curation, Labelling &
Standardization
Annotation of raw
data for ML models
Creation of ML
model for use case
Training of ML model with
annotated data with
computational resources
Deployment of solution
on computational
infrastructure
Testing of
model on
new data
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16. 16
• Utilization & application of data-driven artificial intelligence
developed in various domains
• Utilization of AI will increase together with new possibilities of
growth in related service industry
By Q1 FY19
• Public use of Artificial Intelligence across
various domains
• Your text here
By Q3 FY20
• Ecosystem is built by connecting various
domains
• Your text here
By Q1 FY21
Phase 1
Phase 2
Phase 3
Artificial
Intelligence
Development
Phases

17. Artificial Intelligence Themes 17
Formation Of The
Artificial Intelligence
Department
Develop Capabilities And
Skills Of All Staff
Operating In The Field Of
Technology And Organize
Training
Add Your Text
Here
Workshops,
Programmed,
Initiatives And Field
Visits
Courses Provide All
Services Via Artificial
Intelligence
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18. Click to edit
Master title style
Artificial Intelligence Approaches 18
Logic & Rules-
Based Approach
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Machine Learning
(Pattern Based Approach)
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Artificial
Intelligence

19. Logic & Rules-
Based Approach
19
Representing
process or system
using logical rules
Top-Down rules
are created for
computer
Computers
reason about
these rules
Can be used to
automate process
E.g. Personal
Income tax laws

20. Machine
Learning
(pattern based)
Learn From Data &
Improve Overtime
These Patterns Can Be
Used For Automation Or
Prediction
Text here
Text here
Machine learning is a dominant form of AI today
20

21. Machine Learning Description 21
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Algorithms + Techniques
Machine
Learning
Relationships Patterns
Dependencies Hidden Structures
Input Data
Information
(+ Answer)
Output
Optimum
Model

22. Machine Learning Process
Gathering data
from various
sources
Cleaning data
to have
homogeneity
Model Building-
Selecting the right
ML algorithm
Gaining insights
from the
model’s results
Data Visualization-
Transforming results
into visuals graphs
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22

23. Machine Learning Main Points 23
Learning
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Pattern Detection
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Data
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Self-Programming
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24. Machine Learning Use Cases 24
Manufacturing
• Predictive maintenance or
condition monitoring
• Your text here
• Demand forecasting
• Process optimization
• Telematics
Retail
• Predictive inventory planning
• Recommendation engines
• Your text here
• Customer ROI & lifetime value
Healthcare & Life Sciences
• Alerts & diagnostics from real-
time patient data
• Your text here
• Proactive health management
• Healthcare provider sentiment
analysis
Energy, Feedstock &
Utilities
• Power usage analytics
• Seismic data processing
• Your text here
• Smart grid management
• Energy demand & supply
optimization
Financial Services
• Risk analytics &
regulation
• Customer segmentation
• Your text here
• Credit worthiness
evaluation
Travel & Hospitality
• Aircraft scheduling
• Dynamic pricing
• Your text here
• Traffic patterns & congestion
management
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25. Artificial narrow Intelligence Vs Artificial General Intelligence 25
Artificial General
Intelligence
Understand Abstract Concepts
Explain Why
Be Creative Like Children
Tell Right From Wrong
Have Emotions
Artificial Narrow
Intelligence
Beat Go World Champions
Read Facial Expressions
Write Music
Diagnose Mental Disorders
Comfort Earthquake Survivors
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26. Potential Use cases of AI in Healthcare 26
Keeping Well
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Early Detection
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Training
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Research
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Diagnosis
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Decision Making
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End of Life Care
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Treatment
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27. Challenges in adoption of Artificial Intelligence 27
High Resource Cost & Low Awareness For
Adopting AI In Business Processes
Unclear Privacy, Security
And Ethical Regulations
Unattractive Intellectual Property Regime To
Incentivize Research & Adoption Of AI
Lack Of Enabling Data
Ecosystem
Inadequate Availability Of Expertise,
Technology & Research
Low Intensity Of AI
Research
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28. Coffee Break!
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32. About
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33. Financial 33
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35. Timeline 35
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36. Venn 36
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