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1. 1
Machine
Intelligence
Your Company Name

2. Artificial Intelligence outline
2
Artificial Intelligence Introduction
Artificial Intelligence Objectives
Artificial Intelligence Components
Artificial Intelligence Key Statistics
Reasons for Using Artificial Intelligence
Survey on Adoption of Emerging Technologies
Artificial Intelligence & Investment by Sector
Artificial Intelligence in Various Sectors
Driving Force Behind Artificial Intelligence Maturity
Core Areas of Artificial Intelligence
Artificial Intelligence Value Chain Elements
Artificial Intelligence Development Phases
Artificial Intelligence Themes
Artificial Intelligence Approaches
› Logic & Rules-based Approach
› Machine Learning (Pattern Based)
Machine Learning Description
Machine Learning Process
Machine Learning Use Cases
Artificial Narrow Intelligence vs Artificial
General Intelligence
Potential Use Cases of AI in Healthcare
Challenges in Adoption of Artificial Intelligence
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3. Artificial Intelligence Introduction
3
Sense Comprehend Act
Computer
Vision
Audio
Processing
Natural
Language
Processing
Knowledge
Representation
Machine
Learning
Expert
Systems
AI
Technologies
Illustrative
Solutions
Virtual
Agents
Identity
Analytics
Cognitive
Robotics
Speech
Analytics
Recommendation
Systems
Data
Visualization
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4. Artificial Intelligence Objectives
4
Achieve the objectives of company
XX by 2020
Boost organizational Performance
at all levels
Use an integrated smart digital system that can overcome
challenges and provide quick efficient solutions
Make company XX the first in the field of AI investments
in various sectors
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5. Artificial Intelligence Components Template 1
5
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Strategy
• Aligning with strategic
goals
Design
• Software design is transparent & auditable
Development
• Iterative development
• Managing data dependency
Operating Model
• Data as your key intellectual property

6. Artificial Intelligence Components Template 2
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6
Technology
• AI Analytical Engine
• Interface for data upload
Data
• Pay per Click
• Search console data
• Customer service Transcripts
• Social feedback
Strategy
• Select optimal AI Engine
• Instruct AI Engine
• Create a training strategy

7. Artificial Intelligence Key Statistics
7
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65%
45%
69%
Two- third of senior decision- makers agree
that AI is fundamental to the success of their
organization’s strategy
By 2022, those currently or planning to use AI
technology anticipate a 39% boost to their
organization’s revenue, on average
7 in 10 organizations that have replaced, or
plan to replace, roles with technology will retain
or redeploy those who are displaced

8. Reasons for Using Artificial Intelligence
8
Automated communications that give
firms data they can use to make
effective business decisions,
Other,
All of the above Automated
data-driven reporting,
Monitoring and alerts about the health of
the business , Automation that eliminates manual and
repetitive tasks,
Automated Communications that give
consumers data they can use to effective
decisions,
Automated data- driven reporting,
7.6%6.6%
18%
12.8%
5%
45%
5%
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9. Survey on Adoption of Emerging Technologies
9
20%
25%
30%
32%
35%
38%
42%
55%
63%
0 10 20 30 40 50 60 70
Artificial Intelligence
Blockchain
ARVR
Robotics/
Autonomous Robots
3D Printing
Wearables
Text Here
IoT/ Smart Sensors
Autonomous Vehicles
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10. Artificial Intelligence & Investment by Sector
10
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
Leading Sectors
Falling Behind
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11. Artificial Intelligence in Various Sectors
11
To reduce accidents and cut
operational costs
Transport Health
To minimize chronic and
dangerous diseases
Water
To conduct analysis and
studies to provide water
sources
Technology
To increase productivity and
help with general spending
Environment
To increase forestation
rate
Traffic
To reduce accidents & traffic
jams & draw more effective
traffic policies
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12. Driving Force Behind Artificial Intelligence Maturity
12
5%
7%
9%
13%
18%
22%
26%
Offshoot of Another Project
Unexpected Solution to Problem
Customer Demands
Internal Experiment
Particular Business, Operational or Technical Problem
Executive-led Decision
Competitor Advantage
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13. Core Areas of Artificial Intelligence
13
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Sensory AI such as Internet of Things
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Physical AI like Industrial Automation
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Cognitive AI such as worker training
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General AI
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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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14. Artificial Intelligence Value Chain Elements
14
Curation, Labelling
& Standardization
Data
Capture
Creation of ML
model for use case
Testing of model on
new data
Cleansing of
raw data
Annotation of raw data
for ML models
Training of ML model with
annotated data with
computational resources
Deployment of solution
on computational
infrastructure
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15. Artificial Intelligence Development Phases
15
By Q3
FY20
Phase 2
By Q1
FY21
Phase 3
By Q1
FY19
Phase 1
• Public use of Artificial
Intelligence across various
domains
• Your text here
• Ecosystem is built by
connecting various domains
• Your text here
• 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
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16. Artificial Intelligence Themes
16
Formation of the artificial intelligence department
Workshops, program me, initiatives and field visits
Develop capabilities and skills of all staff operating in the
field of technology and organize training
Provide all services via artificial intelligence
Integration of AI into different departments
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17. Artificial Intelligence Approaches
17
Machine
intelligence
Logic & Rules-Based Approach
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Machine Learning
(Pattern Based Approach)
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18. Logic & Rules-Based Approach
18
Representing process
or system using
logical rules
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Top-Down rules are
created for
computer
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Computers
reason about
these rules
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Can be used to
automate process
E.g. Personal Income
tax laws
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19. Machine Learning (Pattern Based)
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19
01 02 03 04
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Machine learning is a dominant form of AI today

20. Machine Learning Description
20
Output
optimum Model
Input Data
Information (+ Answers)
Algorithms + Techniques
Relationships Patterns
Dependencies
Hidden
Structures
Machine Learning
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21. Machine Learning Process
21
Cleaning data to
have
homogeneity
STEP 2
Model Building-
Selecting the right ML
algorithm
STEP 3
Gaining insights
from the model’s
results
STEP 4
Data Visualization-
Transforming
results into visuals
graphs
STEP 5
Gathering data
from various
sources
STEP 1
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22. Machine Learning Main Points
22
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Learning
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Pattern Detection
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Data
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Self-Programming
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23. Machine Learning Use Cases
23
Manufacturing
• Predictive maintenance or condition
monitoring
• Demand forecasting
• Process optimization
• Telematics
Retail
• Predictive inventory planning
• Recommendation engines
• Your text here
• Customer Roil & lifetime value
Healthcare & Life Sciences
• Alerts & diagnostics from real-time patient
data
• Your text here
• Proactive health management
• Healthcare provider sentiment analysis
Travel & Hospitality
• Aircraft scheduling
• Dynamic pricing
• Your text here
• Traffic patterns & congestion management
Financial Services
• Risk analytics & regulation
• Customer segmentation
• Your text here
• Credit worthiness evaluation
Energy, Feedstock & Utilities
• Power usage analytics
• Seismic data processing
• Smart grid management
• Energy demand & supply optimization
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24. Artificial Narrow Intelligence vs Artificial General
24
Artificial General
Intelligence
Understand Abstract Concepts
Explain Why
Be Creative Like Children
Tell Right From Wrong
Have Emotions
Beat Go World Champions
Read Facial Expressions
Write Music
Diagnose Mental Disorders
Comfort Earthquake Survivors
Artificial Narrow
Intelligence
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25. Potential Use Cases of AI in Healthcare
25
Training
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Research
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End of Life Care
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Treatment
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AI &
ROBOTICS
Keeping Well
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Diagnosis
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Early Detection
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Decision Making
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26. Challenges in Adoption of Artificial Intelligence
26
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Low Intensity of AI
research
Lack of enabling
data ecosystem
Inadequate availability of
expertise, technology &
research
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

27. Machine Intelligence Icons Slide
27

28. Machine Intelligence Icons Slide Cont…
28

29. Coffee
BreakLet’s Start Again in 15 Minutes
29

30. 30
Additional
Slides

31. Agenda 01
Agenda 02
Agenda 03
Agenda 04
Agenda 05
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Agenda
31

32. Comparison
32
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Comparison
60%
40%
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33. This slide is 100% editable. Adapt it
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Meet Our
Team
Name Here
Name Here
33

34. Business Timeline
34
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35. Puzzle
35
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01
0203
04

36. 36
About usThis slide is 100% editable. Adapt it to your needs and capture your
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37. Our Target
37
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Text Here
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75%
100%
50%

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38
FinanceThis slide is 100% editable. Adapt it to your needs and
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39. Circular
39
01
02
03
04
05
06
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40. Comparison
40
85%
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98%
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41. 41
It’s not just about being
better. It’s about being
different. You need to
give people a reason
to choose your
business.
Quotes
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42. Lego
42
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01
02
03
04

43. Silhouettes
43
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44. 44
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45. Bulb or Idea
45
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46. Pie Chart
46
10%
20%
32%
38%
Low
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10%
50%
32%
8%
Medium
8%
15%
62%
15%
High
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47. 47
Address
# street number, city, state
Email Address:
emailaddress@123.com
Contact Numbers:
0123456789
Thank You