The document discusses what artificial intelligence is, including defining it as machines that can exhibit intelligent behavior like learning and problem solving. It also discusses how AI works by using large data to train algorithms that can then be used to make predictions, and gives examples of goals for AI like creating expert systems and developing machines that can perform human-like tasks.

1. ARTIFICIAL
INTELLIGENCE

3. What is Intelligence
(1) the ability to learn or understand or to deal with new or
trying situations : reason also : the skilled use of reason.
(2) the ability to apply knowledge to manipulate one's
environment or to think abstractly as measured by
objective criteria (such as tests)
What is artificial intelligence
Artificial intelligence (AI) is the simulation of human
intelligence processes by machines, especially computer
systems. Specific applications of AI include expert systems,
natural language processing (NLP), speech recognition
and machine vision.

4. Define Artificial intelligence
"It is a branch of computer science by which we can create
intelligent machines which can behave like a human, think like
humans, and able to make decisions”.
Artificial Intelligence exists when a machine can have human
based skills such as learning, reasoning, and solving problems
With Artificial Intelligence you do not need to preprogram a
machine to do some work, despite that you can create a
machine with programmed algorithms which can work with
own intelligence.

5. Why Artificial Intelligence?
 With the help of AI, you can create such software or devices
which can solve real-world problems very easily and with
accuracy such as health issues, marketing, traffic issues, etc.
 you can create your personal virtual Assistant, such as
Cortana, Google Assistant, Siri, etc.
 With the help of AI, you can build such Robots which can work
in an environment where survival of humans can be at risk.
 AI opens a path for other new technologies, new devices, and
new Opportunities.

6.  AI programming focuses on three cognitive skills: learning,
reasoning and self-correction.
 Learning processes. This aspect of AI programming
focuses on acquiring data and creating rules for how to turn
the data into actionable information. The rules, which are
called algorithms, provide computing devices with step-by-
step instructions for how to complete a specific task.
 Reasoning processes. This aspect of AI programming
focuses on choosing the right algorithm to reach a desired
outcome.
 Self-correction processes. This aspect of AI programming
is designed to continually fine-tune algorithms and ensure
they provide the most accurate results possible.

7. How does Artificial Intelligence work?
Computers are good at following processes, i.e.,
sequences of steps to execute a task. If we give a
computer steps to execute a task, it should easily be
able to complete it. The steps are nothing but
algorithms. An algorithm can be as simple as printing
two numbers or as difficult as predicting who will win
elections in the coming year!

8.  Let’s take an example of predicting the weather forecast for 2020.
 First of all, what we need is a lot of data! Let’s take the data from
2006 to 2019.
 Now, we will divide this data in an 80:20 ratio. 80 percent of the
data is going to be our labeled data, and the rest 20 percent will be
our test data. Thus, we have the output for the entire 100 percent
of the data that has been acquired from 2006 to 2019.
 What happens once we collect the data? We will feed the labeled
data, i.e., 80 percent of train data, into the machine. Here, the
algorithm is learning from the data which has been fed into it.
 Next, we need to test the algorithm. Here, we feed the test data,
i.e., the remaining 20 percent of the data, to the machine. The
machine gives us the output. Now, we cross verify the output given
by the machine with the actual output of the data and check for its
accuracy. While checking for accuracy if we are not satisfied with
the model, we tweak the algorithm to give us the precise output or
at least somewhere close to the actual output. Once we are
satisfied with the model, we then feed the data to the model so
that it can predict the weather forecast for the year 2020.

9. Goals of Artificial Intelligence
• To Create Expert Systems − The systems which exhibit intelligent
behavior, learn, demonstrate, explain, and advice its users.
• To Implement Human Intelligence in Machines − Creating
systems that understand, think, learn, and behave like humans.
 Building a machine which can perform tasks that requires
human intelligence such as:
Proving a theorem
Playing chess
Plan some surgical operation
Driving a car in traffic

10.  In early days Artificial intelligence was used to develop reasoning
and problem-solving skills.
 With Artificial intelligence knowledge representation has
become easy. Knowledge representation is representing
information that machine or computer can understand.
 Artificial planning helps agents sequence of actions to perform
to achieve goals.
 Artificial intelligence main goal is develop intelligent machines
that could learn on their own. No more human intervention for
feeding data to machines.
 With artificial intelligence one can develop machines that can
read and understand human languages are known as Natural
learning processing.

11.  Artificial Intelligence helps to develop that could act on sensors
(take input from sensors) and react accordingly.
 Robotics has transformed thanks to artificial intelligence, that
help robots acquire intelligence and perform task smartly.
 Develop systems that can recognize, interpret, process and
simulate human effects. All these can be achieved when
intelligent systems can predict their motive and emotions.
Quality of interpreting human affect could help in better
decision making

13. Term coined by John McCarthy, 1956
Definition: “Developing Computer programs to
solve complex problems by applications of
processes that are analogous to human reasoning
processes”.
Has two parts 1. Computer solutions for complex
problems can be done by conventional
programs
2. Process that is analogous to human reasoning
processes can be done by AI programs

14. AI Program Conventional Program
Symbolic process Numeric process
Heuristic search, steps
are implicitly defined
Steps are explicitly defined as
Algorithms
Control structure
separate from domain
knowledge
Information and control are
integrated together
Incorrect answers are
tolerable
Correct answers are required
Satisfactory answers are
acceptable
Best possible answers are
expected
Difference between AI program and Conventional
program

15. What is Artificial Intelligence ?
Systems that act
rationally
Systems that think
like humans
Systems that think
rationally
Systems that act
like humans
THOUGHT
BEHAVIOUR
HUMAN RATIONAL

16. Acts Like Human – Turing Test

20. Thinks like Human – human like patterns of
thinking steps
Sophia is a social humanoid robot developed by Hong
Kong based company Hanson Robotics. Sophia was
activated on February 14, 2016, and made her first
public appearance at South by Southwest
Festival (SXSW) in mid-March 2016 in Austin, Texas,
United States.
She is able to display more than 50 facial expressions.
Robot Sophia was given Saudia citizenship in 2017
'Sophia' the robot tells UN_ 'I am here to help humanity
create the future' - YouTube (720p).mp4

21. Advantages
Sophia can be used for health care sectors
Sophia can solve CBI and FBI cases very easily
Sophia can be a good friend to those children and adults
who feel lonely.
She can be a good teacher in villages and city colleges.
She can be a business robot.
As she has artificial intelligence she can generates for
million of years
Disadvantages
People worry that they will replace jobs.
If they take over middle class citizens jobs our economy
will be negatively affected.
It makes people to become lazy.

22. Acts or think rationally (logically or
Correctly)
 Thinking rationally — the use of logic. Need to worry about
modeling uncertainty and dealing with complexity.
 Acting rationally — the study of rational agents: agents that
maximize the expected value of their performance measure
given what they currently know.

24. Best 10 examples of AI in day to day life
1. Open Your Phone With Face ID- uses neural engine and face recognition
2. Email -Google gave us a smarter inbox, categorizing all the emails on its own, into
folders such as Primary, Social, Promotions, Updates and more.
3. Entertainment and Social Apps-identifying friends from photos, newsfeed
personalization. ,Netflix - recommendations
Google Navigation- Maps uses Machine Learning
4. Banking & Finance- AI & ML provides security features (Fraud preventions E-payments,
Mobile Banking)
5. Google predictive search algorithms-Google Auto complete forms- RankBrain is the
algorithm name
6. E-commerce – pattern matching , product recommendations
7. Mobile use- Speech recognition with Natural Language Processing (voice to text,
chatbot)
8. Video games-AI controlled Non-playable characters (NPC), ML for BGM
9. Smart Personal Assistant- Google Assistant , Alexa, SIRI (Online shopping, Controlling
lights and other internet-enabled equipment ,Setting reminders and alarms , Booking
cabs, flights and trains, Playing music and videos )

25.  Advantages of Artificial Intelligence
 Following are some main advantages of Artificial Intelligence:
• High Accuracy with less errors: AI machines or systems are prone to less
errors and high accuracy as it takes decisions as per pre-experience or
information.
• High-Speed: AI systems can be of very high-speed and fast-decision making,
because of that AI systems can beat a chess champion in the Chess game.
• High reliability: AI machines are highly reliable and can perform the same
action multiple times with high accuracy.
• Useful for risky areas: AI machines can be helpful in situations such as defusing
a bomb, exploring the ocean floor, where to employ a human can be risky.
• Digital Assistant: AI can be very useful to provide digital assistant to the users
such as AI technology is currently used by various E-commerce websites to show
the products as per customer requirement.
• Useful as a public utility: AI can be very useful for public utilities such as a
self-driving car which can make our journey safer and hassle-free, facial
recognition for security purpose, Natural language processing to communicate
with the human in human-language, etc.

26.  Disadvantages of Artificial Intelligence
 Every technology has some disadvantages, and the same goes for Artificial
intelligence. Being so advantageous technology still, it has some
disadvantages which we need to keep in our mind while creating an AI
system. Following are the disadvantages of AI:
• High Cost: The hardware and software requirement of AI is very costly
as it requires lots of maintenance to meet current world requirements.
• Can't think out of the box: Even we are making smarter machines with
AI, but still they cannot work out of the box, as the robot will only do that
work for which they are trained, or programmed.
• No feelings and emotions: AI machines can be an outstanding
performer, but still it does not have the feeling so it cannot make any kind
of emotional attachment with human, and may sometime be harmful for
users if the proper care is not taken.
• Increase dependency on machines: With the increment of technology,
people are getting more dependent on devices and hence they are losing
their mental capabilities.
• No Original Creativity: As humans are so creative and can imagine some
new ideas but still AI machines cannot beat this power of human
intelligence and cannot be creative and imaginative.


27. Internal Representation
In order to act intelligently, a computer must have
the knowledge about the domain of interest.
Knowledge is the body of facts and principles
gathered or the act, fact, or state of knowing.
This knowledge needs to be presented in a form,
which is understood by the machine.
This unique format is called internal
representation.
Thus plain English sentences could be translated
into an internal representation and they could be
used to answer based on the given sentences.

28. Properties of Internal Representation
Internal representation must remove all
referential ambiguity.
Referential ambiguity is the ambiguity about
what the sentence refers to
Example:’Raj said that Ram was not well. He must
by lying”
Who does he refers to..?
Internal representation should avoid word sense
ambiguity
Word sense ambiguity arise because of multiple
meaning of words.

29. Example
‘Raj caught a pen .
Raj caught a train.
Raj caught fever’
Internal representation must explicitly mention
functional structure
Functional structure is the word order used in the
language to express an idea.
Example:’Ram killed Ravan. Ravan was killed by Ram.
Thus internal representation may not use the order of
the original sentence
Internal representation should be handle complex
sentence without losing meaning attached with it.

30. Problem representation in AI
Define the problem precisely
Analyze the problem
Isolated and represent
Choose
State space representation: set of all possible states
for a given problem.

31. Example of problem space
to make a cup of coffee.
• Analyze the problem
• Check necessary ingrediants are available
or not
• If they are available, apply procedure for
making coffee.

32. • Ingrediants (initial state)
• Sequence of steps(states)
• Cup of coffee (goal)
• Coffee powder, milk powder, sugar
(operators)

34. We started with Ingredients i.e the Initial state.
 Followed by sequence of Steps.
 We added only needed amount of coffee
powder, milk & sugar. These are Operators/
Actions.
At last had a cup of coffee –Goal state.