1.
Introduction to Artificial
Intelligence
By
Vaibhav Raja
Research Scholar
Object Automation Software Solutions

2.
What is
AI?
 According to Britannica, Artificial intelligence (AI), the ability of a
digital computer or computer-controlled robot to perform tasks
commonly associated with intelligent beings. The term is frequently
applied to the project of developing systems endowed with the
intellectual processes characteristic of humans, such as the ability to
reason, discover meaning, generalize, or learn from past experience.
Humans have been obsessed with automation since the beginning of technology
adoption. AI enables machines to think without any human intervention. It is a
broad area of computer science. AI systems fall into three types: ANI: Artificial
Narrow Intelligence, which is goal-oriented and programmed to perform a single
task. AGI (Artificial General Intelligence) which allows machines to learn,
understand, and act in a way that is indistinguishable from humans in a given
situation. ASI (Artificial Super Intelligence) is a hypothetical AI where machines are
capable of exhibiting intelligence that surpasses brightest humans.

3.
Impact of AI in day to day
life
 Social media
 Digital Assistants
 Self-Driving And Parking
Vehicles
 Email communications
 Web searching
 Stores and services
 Offline experiences

4.
How
Artificial
Intelligence
Improves
Social Media
•Twitter
• From tweet recommendations to fighting inappropriate
or racist content and enhancing the user experience,
Twitter has begun to use artificial intelligence behind the
scenes to enhance their product.
• Facebook
• Deep learning is helping Facebook draw value
from a larger portion of its unstructured datasets
created by almost 2 billion people updating their
statuses 293,000 times per minute.
•Instagram
• Instagram also uses big data and artificial intelligence to
target advertising and fight cyberbullying and delete
offensive comments.
•Chatbots
• Chatbots recognize words and phrases in order to
(hopefully) deliver helpful content to customers who
have common questions

5.
How Artificial Intelligence Helps You Every
Day Through Parking Your Car And Driving
It
 Self-driving and parking cars
use deep learning, a subset of
AI, to recognize the space
around a vehicle.
 Technology company Nvidia
uses AI to give cars “the
power to see, think, and
learn, so they can navigate a
nearly infinite range of
possible driving scenarios,” .
 The company’s AI-powered
technology is already in use in
cars made by Toyota,
Mercedes-Benz, Audi, Volvo,
and Tesla , and is sure to
revolutionize how people drive
and enable vehicles to drive
themselves.

6.
How Artificial Intelligence Improves
Email Communications
 Smart Replies in Gmail
 Smart replies offer users a way to respond to emails with simple phrases
like
“Yes, I’m working on it.” or “No I have not. ” with the click of a button.
 Email Filters in Gmail
 Google uses AI to ensure that nearly all of the email landing in your inbox is
authentic. Their filters attempt to sort emails into the following
categories: Primary, Social, Promotions, Updates, Forums, Spam.

7.
How Artificial Intelligence Helps With
Web Searches
 Google Predictive Searches:
 When you begin typing a search term and Google makes recommendations
for
you to choose from, that’s AI in action.

8.
Google’s
Algorithm
 Google search engines evolved over time by studying the linguistics used in
searches. Its AI learns from results and adapts over time to better meet
the needs of users.
 For example, a search of “what are neural networks and how are they related
to synapses” offers Google’s choice of “best answer” highlighted at the top,
followed by a list of sources that answer the question.

9.
How Artificial Intelligence Improves Your
Experience at Online Stores and Services?
 Product Recommendations
 Amazon and other online retailers use AI to gather information about
your preferences and buying habits. Then, they personalize your
shopping experience by suggesting new products tailored to your habits.
 Below is an example of AI-powered recommendations on Amazon.com.

10.
What are the different types of
recommendations?
There are basically three important types of
recommendation engines:
• Collaborative filtering
• Content-Based Filtering
• Hybrid Recommendation Systems

11.
How AI can have an impact on
Employee Lifecycle Management
• AI automation in Talent Acquisition and HR
Practices
• AI in Recruitment Process
• AI in Interviewing
• AI in onboarding
• AI in giving Feedback
• AI in Employee Attrition
• AI in Employee Joining

12.
Machine Learning
 Machine Learning is the field of study that gives computers the capability to
learn without being explicitly programmed.
 ML is one of the most exciting technologies that one would have ever come
across.
 As it is evident from the name, it gives the computer that makes it more
similar to humans: The ability to learn.
 Machine learning is actively being used today, perhaps in many more places
than one would expect.
ML is a subset of AI that uses statistical learning algorithms to build smart systems.
The ML systems can automatically learn and improve without explicitly being
programmed. The recommendation systems on music and video streaming services are
examples of ML. The machine learning algorithms are classified into three categories:
supervised, unsupervised and reinforcement learning.

13.
Applications of Machine Learning
 1. Image Recognition:
 Image recognition is one of the most common applications of machine learning. It is used
to identify objects, persons, places, digital images, etc. The popular use case of image
recognition and face detection is, Automatic friend tagging suggestion:
 Facebook provides us a feature of auto friend tagging suggestion. Whenever we upload a photo
with our Facebook friends, then we automatically get a tagging suggestion with name, and the
technology behind this is machine learning's face detection and recognition algorithm.
 2. Speech Recognition
 While using Google, we get an option of "Search by voice," it comes under speech
recognition,
and it's a popular application of machine learning.
 3. Traffic prediction:
 If we want to visit a new place, we take help of Google Maps, which shows us the correct
path
with the shortest route and predicts the traffic conditions.

14.
 4. Product recommendations:
 Machine learning is widely used by various e-commerce and entertainment
companies such as Amazon, Netflix, etc., for product recommendation to the
user.
 5. Self-driving cars:
 One of the most exciting applications of machine learning is self-driving cars.
Machine learning plays a significant role in self-driving cars. Tesla, the
most popular car manufacturing company is working on self-driving car. It
is using unsupervised learning method to train the car models to detect
people and objects while driving.
 6. Stock Market trading:
 Machine learning is widely used in stock market trading. In the stock market,
there is always a risk of up and downs in shares, so for this machine
learning's long short term memory neural network is used for the prediction
of
stock market trends.
 7. Medical Diagnosis:
 In medical science, machine learning is used for diseases diagnoses. With
this, medical technology is growing very fast and able to build 3D models
that can predict the exact position of lesions in the brain.
 It helps in finding brain tumors and other brain-related diseases easily.

15.
Deep Learning
 Deep learning is an AI function that mimics the workings of the human brain in processing data for use in
detecting objects, recognizing speech, translating languages, and making decisions.
 Deep learning AI is able to learn without human supervision, drawing from data
that is both unstructured and unlabeled.
 Deep learning, a form of machine learning, can be used to help detect fraud or
money laundering, among other functions.
This subset of AI is a technique that is inspired by the way a human brain filters information. It is associated with learning
from examples. DL systems help a computer model to filter the input data through layers to predict and classify
information. Deep Learning processes information in the same manner as the human brain. It is used in technologies such
as driver-less cars. DL network architectures are classified into Convolutional Neural Networks, Recurrent Neural
Networks, and Recursive Neural Networks.
How Deep Learning Works?
 Deep learning has evolved hand-in-hand with the digital era, which has brought
about an explosion of data in all forms and from every region of the world.
 This data, known simply as big data, is drawn from sources like social media,
internet search engines, e-commerce platforms, and online cinemas, among
others. This enormous amount of data is readily accessible and can be
shared through fintech applications like cloud computing.

16.
Deep Learning vs. Machine Learning
 One of the most common AI techniques used for processing big data is
machine learning, a self-adaptive algorithm that gets increasingly better
analysis and patterns with experience or with newly added data.
 If a digital payments company wanted to detect the occurrence or potential
for fraud in its system, it could employ machine learning tools for this
purpose.
 Deep learning, a subset of machine learning, utilizes a hierarchical level of
artificial neural networks to carry out the process of machine learning. The
artificial neural networks are built like the human brain, with neuron nodes
connected together like a web.
 While traditional programs build analysis with data in a linear way, the hierarchical
function of deep learning systems enables machines to process data with a
nonlinear approach.

17.
OpenPOWER
AI
 OpenPOWER Foundation is an open development alliance based on IBM's
POWER microprocessor architecture. The Consortium intends to build
advanced server, networking, storage and GPU-acceleration technology
aimed at delivering more choice, control and flexibility to developers of
next- generation, hyper scale and cloud data centers.
 OpenPOWER AI , Cloud Virtual University YouTube Channel:
https://www.youtube.com/c/OpenPOWERAICloudVirtualUniversity/videos

18.
Some fascinating videos on AI and
other recent technologies:
 OpenPOWER AI and HPC Webinar from Virginia Tech
- https://youtu.be/IEXcJ2KM33g
 OpenPOWER Webinar Series : AI at Scale in Enterprise and
Containerizing
Applications: https://youtu.be/TCYC1eXUAb4
 OpenPOWER Workshop for AI and HPC at CINECA - https://youtu.be/-
xo8k_J_M54
 Open POWER ISA Cores- https://youtu.be/nejEA15xTnU
 OpenPOWER Webinar: OpenShift and Kubernetes on
POWER/OpenPOWER
systems by Industry experts - https://youtu.be/7xIQYVeIk40
 OpenPOWER Webinar from Berkeley Lab and IBM Weather.com
-
https://youtu.be/WGp-VM5TYek
 Machine Learning at Scale using OpenPOWER/POWER9 Systems
-
https://youtu.be/TzHf5hLbusU

19.
 Deep learning Fundamentals and Case Studies using IBM POWER systems -
https://youtu.be/JZu5lGCgbHM
 Deep learning fundamental and Research project on IBM POWER9 system
from NUS - https://youtu.be/MVlqyzVfDdE
 OpenPOWER Summit NA 2020 -
https://www.youtube.com/playlist?list=PLEqfbaomKgQpc
- jB5bVjluRdzh9Pdr3kY

20.
Conclusion
 Artificial Intelligence makes our lives more efficient every
day AI powers many programs and services that help us do
everyday things such as connecting with friends, using an
email program, or using a ride-share service.
 If you have reservations about the use of artificial
intelligence, it may be comforting to know that most of us
have been using AI on a daily basis for many years.

21.
Thank You!
We look forward to working together!
www.object-automation.com
Object Automation Software Solutions
Pvt. Ltd
No.1, Nehru Street, Second Floor,
Kooturavu Nagar, Adambakkam, Chennai
– 600 088
Contact:
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+91 7397784815