Learn the workings of using intelligent machines for your processes using content-ready Artificial Intelligence PowerPoint Presentation Slides. Processes like learning, reasoning, self-correction, etc. are executed by artificial intelligent machines. Incorporate ready-made artificial intelligence PPT presentation templates and maximize the chance of achieving the organizational goals. This deck comprises of templates such as artificial intelligence objectives, artificial intelligence components, artificial intelligence statistics, artificial intelligence & investment by sector, artificial intelligence in various sectors, core areas of artificial intelligence, artificial intelligence value chain elements, artificial intelligence development phases, artificial intelligence approaches, machine learning (pattern based), machine learning description, machine learning process, machine learning use cases, and more. These templates are customizable. Edit color, text, icon and font size as per your need. Grab easy-to-understand artificial intelligence PowerPoint presentation slideshow and perform tasks associated with intelligent beings. Find solutions to the business problems without human intervention. Provide better products and services with the help of AI PPT templates. Click the download button to perform difficult tasks with ease using ready-made artificial intelligence PowerPoint presentation slides. Our Artificial Intelligence Powerpoint Presentation Slides team will alert you about changing demands. Their eyes and ears are always open.
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01. Agenda
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02. Agenda
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03. Agenda
Agenda
3. Artificial Intelligence outline
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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4. Artificial Intelligence Introduction
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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5. 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
Text here
Text here
Artificial Intelligence objectives
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6. Artificiel Intelligence Components Template 1
Strategy
› Aligning with strategic goals
› Text here
Design
› Software design is transparent & auditable
› Text here
Development
› Iterative development
› Managing data dependency
operating Model
› Data as your key intellectual property
› Text here
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7. Artificiel Intelligence Components Template 2
7
Data
Technology
Strategy
› Pay per Click
› Search console data
› Customer service Transcripts
› Social feedback
› AI Analytical Engine
› Interface for data upload
› Select optimal AI Engine
› Instruct AI Engine
› Create a training strategy
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8. Artificial Intelligence Key Statistics
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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
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9. Reasons for using Artificial Intelligence
Automated communications that give
firms data they can use to make
effective business decisions, 45%
Other, 5%
All of the above Automated
data-driven reporting, 18%
Monitoring and alerts about the health of
the business , 6.6%
Automation that eliminates manual and
repetitive tasks, 7.6%
Automated Communications that give
consumers data they can use to
effective decisions, 12.8%
Automated data- driven reporting, 5%
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10. Survey on Adoption of Emerging Technologies
10
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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11. Artificial Intelligence & Investment by Sector
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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12. Artificial Intelligence in various Sectors
12
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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13. Driving Force behind Artificial Intelligence Maturity
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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14. Core Areas of Artificial Intelligence
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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Explainable AI
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Research on new algorithms
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High precision learning from small data sets
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14
15. Artificiel Intelligence Value Chain Eléments
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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
Testing of model on
new data
Deployment of solution
on computational
infrastructure
16. Artificial Intelligence Development Phases
› Public use of Artificial
Intelligence across various
domains
› Your text here
By Q3
FY20
Phase 2
› Ecosystem is built by
connecting various domains
› Your text here
By Q1
FY21
Phase 3
› 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
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Artificial Intelligence Themes
17
Formation of the artificial intelligence department
Workshops, programmes, 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
Text here
18. Artificial Intelligence Approaches
Artificial
intelligence
Logic & Rules-Based Approach
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Machine Learning
(Pattern Based Approach)
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19. Logic & Rules-Based Approach
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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
20. Machine Learning (Pattern based)
Machine learning is a dominant form of AI today
Learn from data &
improve overtime
These patterns can be
used for automation or
prediction
Text here Text here
04
03
02
01
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21. Machine Learning Description
OUTPUT
optimum Model
INPUT DATA
Information (+ Answers)
Algorithms + Techniques
Relationships Patterns
Dependencies
Hidden
Structures
MACHINE LEARNING
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22. Machine Learning Process
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STEP 1 STEP 2 STEP 3 STEP 4 STEP 5
Gathering data
from various
sources
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Cleaning data
to have
homogeneity
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Model Building-
Selecting the right
ML algorithm
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Gaining insights
from the model’s
results
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Data Visualization-
Transforming results
into visuals graphs
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23. Machine Learning Main Points
Learning Pattern Detection
Data Self-Programming
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24. Machine Learning Use Cases
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 Intelligence Vs Artificial General Intelligence
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Artificial Narrow Intelligence
Beat Go World Champions
Read Facial Expressions
Write Music
Diagnose Mental Disorders
Comfort Earthquake Survivors
Artificial General Intelligence
Understand Abstract Concepts
Explain Why
Be Creative Like Children
Tell Right From Wrong
Have Emotions
26. Potential Use cases of AI in Healthcare
AI &
ROBOTICS
Keeping Well
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Decision Making
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Diagnosis
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Early Detection
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Training
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Treatment
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End of Life Care
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Research
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27. Challenges in adoption of Artificial Intelligence
Lack of enabling data ecosystem
Low Intensity of AI research
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
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28. 28
11:00 To 11:30
Let’s Have a
Coffee Break!
Let’s Start again in 30 Minutes
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33. Meet our Team
33
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Name Here
Designation
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Designation
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Name Here
Designation
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About us
35. Comparison
35
VS
79%
21%
Female
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Male
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36. Financial
%50 %95%75
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37. Business Timeline
2018
2017
2016
2014
2015
2013
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38. Puzzle
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01
03
0204
38
39. 39
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Our Target
40. Circular
40
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01
02
03
04
05
06
Text
Here
41. Venn
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04
05
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42. Matrix
High Low
HighLow
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43. SWOT Analysis
43
S
O
W
T
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Strengths
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Opportunities
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Weaknesses
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Threats
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44. Lego
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01
02
03
04
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45. 45
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Magnifying Glass
46. Silhouettes
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47. Bulb or Idea
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70%
55%
40%
30%
0 10 20 30 40 50 60 70 80 90 100
2014
2015
2016
2017
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