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2. Agenda 01This slide is 100% editable. Adapt it to your needs and capture
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Agenda 02This slide is 100% editable. Adapt it to your needs and capture
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Our Agenda
2
3. 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
Artificial Intelligence Outline 3
4. Artificial Intelligence Introduction 4
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Comprehend ActSense
AI
Technologies
Illustrative
Solutions
Virtual
Agents
Identity
Analytics
Recommendation
Systems
Data
Visualization
Speech
Analytics
Cognitive
Robotics
Computer
Vision
Audio
Processing
Natural Language
Processing
Knowledge
Representation
Machine
Learning
Expert
Systems
5. Use an integrated smart digital
system that can overcome
challenges and provide quick
efficient solutions
Boost organizational
Performance at all levels
Achieve the objectives of
company XX by 2020
Make company XX the first
in the field of AI investments
in various sectors
Artificial Intelligence Objectives 5
Objectives
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6. Artificiel Intelligence ComponentsTemplate 1 6
01Strategy
• Aligning with strategic goals
• Text Here
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02Design
• Software design is transparent &
auditable
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03Development
• Iterative development
• Managing data dependency
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04Operating Model
• Data as your key intellectual property
• Text here
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7. Artificiel Intelligence ComponentsTemplate 2 7
Data
• Pay per Click
• Search console data
• Customer service Transcripts
• Social feedback
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Technology
• AI Analytical Engine
• Interface for data upload
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Strategy
• Select optimal AI Engine
• Instruct AI Engine
• Create a training strategy
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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
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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%
10. Survey on Adoption of EmergingTechnologies 10
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10%
20%
30%
32%
30%
38%
40%
50%
60%
0 10 20 30 40 50 60 70
Text Here
Wearables
Autonomous Vehicles
3D Printing
Robotics/Autonomous Robots
ARVR
Blockchain
Aritificial Intellgence
IOT/ Smart Sensors
11. Artificial Intelligence & Investment by Sector 11
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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
12. Artificial Intelligence in various Sectors 12
Water
To conduct analysis and
studies to provide water
sources
Transport
To reduce accidents and cut
operational costs
Traffic
To reduce accidents & traffic jams
& draw more effective traffic
policies
Health
To minimize chronic and
dangerous diseases
Environment
To increase forestation
rate
Technology
To increase productivity and
help with general spending
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13. Driving Force behind Artificial Intelligence Maturity 13
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6%
8%
10%
12%
15%
25%
30%
Offshoot of Another Project
Unexpected Solution to Problem
Customer Demands
Internal Experiment
Particular Business, Operational or Technical Problem
Executive-led Decision
Competitor Advantage
14. Core Areas of Artificial Intelligence 14
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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15. Artificiel IntelligenceValue Chain Elements 15
Data Capture
Curation, Labelling
& Standardization
Creation Of ML Model
For Use Case
Testing Of Model
On New Data
Annotation Of Raw
Data For ML Models
Cleansing Of Raw
Data
Training Of ML Model
With Annotated Data
With Computational
Resources
Deployment Of Solution
On Computational
Infrastructure
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16. Artificial Intelligence Development Phases 16
• 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
By Q1
FY19
Phase 1
By Q3
FY20
Phase 2
By Q1
FY21
Phase 3
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17. Artificial IntelligenceThemes 17
Artificial Intelligence
Formation Of The
Artificial Intelligence
Department
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Workshops, programmes,
initiatives and field visits
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Develop capabilities and
skills of all staff operating
in the field of technology
and organize training
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Provide all services
via artificial
intelligence
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Integration of AI
into different
departments
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18. Artificial Intelligence Approaches 18
Machine Learning
(Pattern Based Approach)
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Logic & Rules-Based Approach
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Artificial
Intelligence
19. Logic & Rules-Based Approach 19
04
Can be used to
automate process
E.g. Personal
Income tax laws
01
Representing
process or system
using logical rules
03
Computers reason
about these rules
02
Top-Down rules are
created for computer
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20. Machine Learning (Pattern based) 20
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Learn From Data &
Improve Overtime
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These Patterns Can Be Used
for Automation or Prediction
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Text Here
Machine Learning Is A Dominant Form of AI Today
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 22
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STEP 2
Cleaning data to have
homogeneity
STEP 1
Gathering data from
various sources
STEP 3
Model Building-
Selecting the right ML
algorithm
STEP 4
Gaining insights from
the model’s results
STEP 5
Data Visualization-
Transforming results
into visuals graphs
23. Machine Learning Main Points 23
Machine
Learning Main
Points
Learning 01 Pattern
Detection02
Data 04 Self-
Programming03
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24. Machine Learning Use Cases 24
Manufacturing
• Predictive maintenance or condition monitoring
• 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
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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25. Artificial Narrow IntelligenceVs Artificial General Intelligence 25
Artificial Narrow
Intelligence
Artificial General
Intelligence
Understand Abstract ConceptsBeat Go World Champions
Explain WhyRead Facial Expressions
BE Creative Like ChildrenWrite Music
Tell Right From WrongDiagnose Mental Disorders
Have EmotionsComfort 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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Diagnosis
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Decision Making
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Training
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Research
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End of Life Care
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Treatment
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Al &
Robotics
27. Challenges in adoption of Artificial Intelligence 27
Lack of enabling data ecosystem
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Low Intensity of AI research
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Inadequate availability of
expertise, technology & research
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High resource cost & low awareness
for adopting AI in business processes
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Unclear privacy, security and
ethical regulations
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Unattractive Intellectual Property regime to
incentivize research & adoption of AI
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31. Our Goal
31
Goal 01This slide is 100% editable. Adapt it to your needs and capture
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Goal 02This slide is 100% editable. Adapt it to your needs and capture
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32. Africa
Male Female
60% 70%
America
Male Female
60% 70%
Australia
Male Female
60% 70%
North America
Male Female
60% 70%
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Location
32
33. Financial
33
85%
65%
Maximum
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Minimum
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34. Venn 34
Text Here
Text Here
Text Here
Text Here
Text Here
Text Here
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Vision
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Mission
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Goal
Our Mission
35
36. Timeline
36
3 Jan 2016
5 Feb 2016
6 Mar 2016
2 Apr 2017
3 May 2017
4 June 2017
10 July 2018
15 Aug 2018
18 Sep 2018
26 Oct 2019
10 Nov 2019
16 Dec 2019
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