Overview of Artificial Intelligence, Best AI Applications, Impact of AI on Different Industries and Guide to DS vs ML vs DL

1. AI Matters?
Can you emulate brain?
How this self created system of intelligency works?
How to represent AI?

2. Table of Contents
1. Introduction to Intelligence (AI)
2. Beginning of AI (Evolution)
3. AI Approach
4. Types of AI
a. Type1
b. Type2
5. Applications of AI
6. Technologies in Use
7. AI Advancements in different sectors
8. AI and IOT
9. Advantages & Disadvantages
10 .Data Science for AI
11. Data Science Life Cycle
12. Why ML for AI?
13. ML Types and Algorithms
14. Into Deep Learning
15. DS vs ML vs DL
16. Takeaways

3. Intelligence
The ability to learn, understand and think in a logical way
-Oxford
Learning
Reasoning
Problem Solving
Perception
Language
Human Intelligence
Artificial Intelligence
Human Being
Human Machines

4. Beginning of AI
Decoded Enigma Machine – Alan M. Turing
Turing Test (1950) – On whether a computer can “think”
When Human Machines tactically absorbs or imitates the super human qualities
at times far beyond is what we call Artificial Intelligence.
1956 – DartMouth Conference (AI term coined)
AI and Computers evolution hugely correlated
AI winters ( Computers sorrow -> No for AI)
Applied
Epistemology
Machine
Intelligence
Computational
Intelligence
Artificial
Intelligence

5. AI Approach
Top-Down Approach Bottom-Up Approach
Optical Scanner
Code comapares
each letter with
geometric
description

6. Types of AI

7. Applications of AI
Alexa
Ask me Anything

8. Technologies in Use
Text Analytics & NLP
Includes the process
of text mining, text
identification, text
parsing, text extraction
etc.
Text Analytics & NLP
Includes the process
of text mining, text
identification, text
parsing, text extraction
etc.
Decision Management
Makes structured
business decisions
with the help of data.
Decision Management
Makes structured
business decisions
with the help of data.
Speech Recognition
When the system
recognizes speech
and converts it into
text.
Speech Recognition
When the system
recognizes speech
and converts it into
text.
AI-Optimized Hardware
Alexa by Amazon
AI-Optimized Hardware
Alexa by Amazon
Biometrics
Identification and
access control
through human
characteristics.
Biometrics
Identification and
access control
through human
characteristics.
Robotic Process
Automation
These are software
bots that emulate
human interaction
within GUI, and
automated Business
workflows.
Robotic Process
Automation
These are software
bots that emulate
human interaction
within GUI, and
automated Business
workflows.
Computer Vision
To see and extract
meaning such as
Face Recognition,
Autonomous Vehicles
etc.
Computer Vision
To see and extract
meaning such as
Face Recognition,
Autonomous Vehicles
etc.
Virtual Agents
Chat bot serving
as a customer
service representative.
Virtual Agents
Chat bot serving
as a customer
service representative.

9. AI Advancements in different sectors
Cyber Security
Secure Systems
from digital attacks
Cyber Security
Secure Systems
from digital attacks
Business Intelligence
Best practices of
Analysis of systems
to better improve and
optimize business
decisions.
Business Intelligence
Best practices of
Analysis of systems
to better improve and
optimize business
decisions.
Education
Universal access
such as presentation
translator, Individualized
learning, Automate
admin tasks
etc.
Education
Universal access
such as presentation
translator, Individualized
learning, Automate
admin tasks
etc.
Management
AI automates
more routine tasks
thus privides insights
into workers
productivity.
Management
AI automates
more routine tasks
thus privides insights
into workers
productivity.
Supply Chain
Management
Machine Learning for
Warehouse management,
Autonomous vehicles for
Logistics & Shipping.
Supply Chain
Management
Machine Learning for
Warehouse management,
Autonomous vehicles for
Logistics & Shipping.
Manufacturing
Generative Design,
Computer Vision
Manufacturing
Generative Design,
Computer Vision
City Planning
Systems easily
identify million of
elements such as
people, cars,
Public workers, trash
accidents allowing
autonomous
monitoring.
City Planning
Systems easily
identify million of
elements such as
people, cars,
Public workers, trash
accidents allowing
autonomous
monitoring.
Devops and
Cloud Hosting
Automating software
delivery process
Devops and
Cloud Hosting
Automating software
delivery process
Retail
Smart Analytics,Natural
Language Processing
to streamline
shopping experience
Retail
Smart Analytics,Natural
Language Processing
to streamline
shopping experience
Healthcare
Virtual Nursing
Assistants, Robotic
Surgery, administrative
tasks, Image Analysis
etc.
Healthcare
Virtual Nursing
Assistants, Robotic
Surgery, administrative
tasks, Image Analysis
etc.

10. AI & IOT
Data Discovery
Data Preparation
Visualization of
● Streaming Data
Predictive and
● Advance Analytics
Time Series
● Accuracy of Data
Real-Time Geospatial
● and Location

11. Advantages & Disadvantages of AI
Advantages
● Reduce time taken for a task
● Overcome Human limitations
● Multi-Tasking
● Ease workload
● Deployed across Industries
● Has no downtime, 24*7 working
Disadvantages
● Machines require high cost to create,
run, maintain & repair
● Cannot replicate human on moral and
emotional level
● Daily basis tasks difficult to acheive
through AI
● Resonse altering is difficult for
machines as compared to humans
● Affects Industry 4.0

12. Data Science for AI
Is there a Science that experiments with data?
Yes
And AI helps
Process
Maintain
Analyze
Data Science Artificial Intelligence

13. Data Science Life Cycle

14. Why Machine Learning For AI
ML is the method behind how machines learn from data .
AI to grow and get sharpen results it needs to learn from huge data
for eg..
Machine Learning Grinder is Algorithms
Kiwi ?
Machine Learning
Algorithms

15. Machine Learning Types & Algorithms

16. Into Deep Learning
Deep Learning subset of Machine Learning require Artificial Neural network & Algorithms
to learn from large amount of Data
Applications of DL in AI
● Drones
● Autonomous Cars
● Virtual Assistants
● Facial Recognition
● Chatbots
● Personalized Shopping
● Medicine & Pharmaceuticals

17. Data Science vs Machine Learning vs Deep Learning
Data Science Machine Learning Deep Learning
A field encompassing several
subfield including AI,ML & DL.
A Multidisciplinary field
Talks about – AI, ML, DL, Data
Visualization, Statistics, EDA,
Data Mining etc.
Tools – Apache Spark, Matlab,
Tableau, Apache Haddop, Scala,
Apache Hive etc.
A field encompassing several
subfield including AI,ML & DL.
A Multidisciplinary field
Talks about – AI, ML, DL, Data
Visualization, Statistics, EDA,
Data Mining etc.
Tools – Apache Spark, Matlab,
Tableau, Apache Haddop, Scala,
Apache Hive etc.
A specialization or a subset
for AI totally into its core.
A subfield of AI
Talks about – A lot of Algorithms,
data dependencies, Features etc.
Tools – TenserFlow, Pytorch,
Scikit-learn, NLTK, Tenserboard etc.
A specialization or a subset
for AI totally into its core.
A subfield of AI
Talks about – A lot of Algorithms,
data dependencies, Features etc.
Tools – TenserFlow, Pytorch,
Scikit-learn, NLTK, Tenserboard etc.
A specialization or a subset
for ML totally into its core.
A subfield of ML
Talks About – Few Algorithms,
large training datasets, high
data dependencies.
Tools – CNTK, Caffe, MXNet,
Chainer, Keras, Deeplearning4j
A specialization or a subset
for ML totally into its core.
A subfield of ML
Talks About – Few Algorithms,
large training datasets, high
data dependencies.
Tools – CNTK, Caffe, MXNet,
Chainer, Keras, Deeplearning4j

18. Takeaways
AI Matters? Yes
Can you emulate brain? No, not fully
How this self created system of intelligency works? Hope you
understand it by now
How to represent AI? Alexa, Siri