Useful for diploma and degree computer engg

1. ARTIFICIAL INTELLIGENCE
HONEY VACHHARAJANI GURNANI

2. INTRODUCTION TO ARTIFICIAL INTELLIGENCE
 What is Artificial Intelligence?
 According to the father of Artificial Intelligence, John McCarthy, it is “The science and engineering of making
intelligent machines, especially intelligent computer programs”.
 Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think
intelligently, in the similar manner the intelligent humans think.
 AI is accomplished by studying how human brain thinks, and how humans learn, decide, and work while trying
to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and
systems.

3. PHILOSOPHY OF AI
 While exploiting the power of the computer systems, the curiosity of human, lead him to wonder, “Can a
machine think and behave like humans do?”
 Thus, the development of AI started with the intention of creating similar intelligence in machines that we find
and regard high in humans.

4. GOALS OF AI
• 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.

5. CAN MACHINES THINK?
 This is a difficult question and to answer it we need to define intelligence and thinking.Some aspects of intelligence:
• Planing
• Learning
• Reasoning
• Problem Solving
• Perception
 In the 1950's, a test was proposed by Alan Turing to determine whether a machine is intelligent or not - The Turing Test.

6. THE TURING TEST
 The basis of the turing test is for a person to attempt to distinguish between a machine and a human being. For fairness,
the machine and the human are isolated from the person carrying out the test and messages are exchanged via a keyboard
and screen. If the person can not distinguish between the computer and the human being, then the computer must be
intelligent. Each year, there is a Turing test contest called the Loebner Prize. This test is often criticised because it only
tests a limited aspect of intelligence.
 Some people think that even if a machine could pass the Turing Test it may still not be intelligent.

7. AI PROBLEMS
 Problems in AI early focused in on formal task with Applied Mathematical Theorem
 Another Early day focused on sort the problem is called Commonsense reasoning. - These include perception
natural language understanding, and problem solving in Specialized domains medical diagnosis and chemical
analysis.
 Now days AI problems and solution techniques it is important to discuss the following Question:
• 1. What are the underlying assumptions about intelligence?
• 2. What kinds of techniques will be useful for solving AI problems?
• 3. At what level human intelligence can be modelled?
• 4. When will it be realized when an intelligent program has been built?

8. TYPES OF AI TASKS
One possible classification of AI tasks is into 3 classes:
 Mundane problems,
 Formal problems
 Expert Problems.

9. MUNDANE TASKS
• Perception
• Vision
• Speech
• Natural Language understanding, generation and translation
• Common-sense Reasoning
• Simple reasoning and logical symbol manipulation
• Robot Control

10. FORMAL TASKS
 Games
• Chess
• Deep Blue recently beat Gary Kasparov Backgammon
• Draughts
• GO
 To solve these problems we must explore a large number of solutions quickly and choose the Best One.Mathematics
• Geometry and Logic
• Logic Theorist: It proved mathematical theorems. It actually proved several theorems from Classical Math TextbooksIntegral Calculus
 Programs such as Mathematica and Mathcad and perform complicated symbolic integration and differentiation.
-Proving Properties of Programs e.g. correctness
 Manipulate Symbols and reduce problem (usually recursively), until the answer is obvious. That is, it can be looked up in
a table.

11. EXPERT TASKS
 Engineering
• Design
• Fault finding
• Manufacturing
 Planning
 Scientific Analysis
 Medical Diagnosis
 Financial Analysis
 Rule based systems -
if (conditions) then action

12. THE UNDERLYING ASSUMPTION
 The Physical Symbol System Hypothesis - A physical symbol system has the necessary and sufficient means for general intelligent action
In other words: Computers (Turing Machines) have the power for general intelligent action.
 Physical Symbol -- A Physical Symbol entities called symbol.
 A physical symbol is machine that produces through time on evolving collection of symbol structures.
 Computer provides the perfect medium for this extermination can be programmed to physical symbols
 A physical Symbol include a visual perception its influence of sub symbolic process.
 Sub symbolic models are beginning to challenge symbolic ones at such low level tasks.
 The important of the physical symbol it’s a significant theory of the nature of human Intelligence and great interest to psychologists.
 That its possible to build programs that can perform the intelligent task performed by people

13. EXAMPLE
 Example of AI problem solving.
 Problem : A farmer has a hungry fox a fat goose and a bag of grain. The farmer needs to cross a river but his boat can
only carry two things.Constraints: Fox and goose cannot be left together Goose and grain cannot be left together.
 How to cross the river?
 English language representation is hard to solve.
 Try visual/graphical representation:

14. VISUAL APPROACH - TO SOLVE THIS PROBLEM WE NEED ONLY
FOLLOW THE TREE FROM ITS ROOT NODE TO ANY LEAF NODE.

15. WHAT IS AI TECHNIQUE?
 In the real world, the knowledge has some unwelcomed properties −
• Its volume is huge, next to unimaginable.
• It is not well-organized or well-formatted.
• It keeps changing constantly.
 AI Technique is a manner to organize and use the knowledge efficiently in such a way that −
• It should be perceivable by the people who provide it.
• It should be easily modifiable to correct errors.
• It should be useful in many situations though it is incomplete or inaccurate.
 AI techniques elevate the speed of execution of the complex program it is equipped with.

16. TECHNOLOGIES BASED ON ARTIFICIAL INTELLIGENCE:
1. Machine Learning: A subfield of AI that uses algorithms to enable systems to learn from data and make predictions
or decisions without being explicitly programmed.
2. Natural Language Processing (NLP): A branch of AI that focuses on enabling computers to understand, interpret,
and generate human language.
3. Computer Vision: A field of AI that deals with the processing and analysis of visual information using computer
algorithms.
4. Robotics: AI-powered robots and automation systems that can perform tasks in manufacturing, healthcare, retail, and
other industries.
5. Neural Networks: A type of machine learning algorithm modeled after the structure and function of the human
brain.
6. Expert Systems: AI systems that mimic the decision-making ability of a human expert in a specific field.
7. Chatbots: AI-powered virtual assistants that can interact with users through text-based or voice-based interfaces.

17. THE LEVEL OF MODEL
Artifical Intelligence Model
• What is our goal in trying to produce programs that do the intelligent things that people do?’
• Are we trying to produce programs that do the tasks the same way that people do? OR Are we trying to
produce programs that simply do the tasks the easiest way that is possible?

18. THE LEVEL OF MODEL
. AI techniques is a search method .
To use the knowledge about the objects involved in the problem area and abstraction
• To allows the element of pruning to occur, and to enable a solution to be found in real time.
• Examples : EPAM (Elementary Perceiver and Memorizer) which memorized garbage syllables.
The second class of problems attempts to Human performance
• 1. To test psychological theories of human performance. Ex. PARRY [Colby, 1975]which exploited a model
of human paranoid behaviour to simulate the conversational behavior of a paranoid person.
• 2. To understand computer reasoning. In many circumstances, people are reluctant to rely on the output
of a computer unless they can understand how the machine arrived at its result.
• 3. To exploit what knowledge we can glean from people. Since people are the best-known performers of
most of the tasks with which we are dealing, it makes a lot of sense to look to them for clues as to how to
proceed.

19. CRITERIA FOR SUCCESS IN AI

21. APPLICATIONS OF A.I
 1. AI in Astronomy
• Artificial Intelligence can be very useful to solve complex universe problems. AI technology can be helpful for
understanding the universe such as how it works, origin, etc.
 2. AI in Healthcare
• In the last, five to ten years, AI becoming more advantageous for the healthcare industry and going to have a
significant impact on this industry.
• Healthcare Industries are applying AI to make a better and faster diagnosis than humans. AI can help doctors with
diagnoses and can inform when patients are worsening so that medical help can reach to the patient before
hospitalization.
 3. AI in Gaming
• AI can be used for gaming purpose. The AI machines can play strategic games like chess, where the machine needs to
think of a large number of possible places.
 4. AI in Finance
• AI and finance industries are the best matches for each other. The finance industry is implementing automation,
chatbot, adaptive intelligence, algorithm trading, and machine learning into financial processes.

22. • 5. AI in Data Security
• The security of data is crucial for every company and cyber-attacks are growing very rapidly in the digital world. AI can be used to
make your data more safe and secure. Some examples such as AEG bot, AI2 Platform,are used to determine software bug and cyber-
attacks in a better way.
• 6. AI in Social Media
• Social Media sites such as Facebook, Twitter, and Snapchat contain billions of user profiles, which need to be stored and managed in a
very efficient way. AI can organize and manage massive amounts of data. AI can analyze lots of data to identify the latest trends, hashtag,
and requirement of different users.
• 7. AI in Travel & Transport
• AI is becoming highly demanding for travel industries. AI is capable of doing various travel related works such as from making travel
arrangement to suggesting the hotels, flights, and best routes to the customers. Travel industries are using AI-powered chatbots which
can make human-like interaction with customers for better and fast response.
• 8. AI in Automotive Industry
• Some Automotive industries are using AI to provide virtual assistant to their user for better performance. Such as Tesla has introduced
TeslaBot, an intelligent virtual assistant.
• Various Industries are currently working for developing self-driven cars which can make your journey more safe and secure.
• 9. AI in Robotics:
• Artificial Intelligence has a remarkable role in Robotics. Usually, general robots are programmed such that they can perform some
repetitive task, but with the help of AI, we can create intelligent robots which can perform tasks with their own experiences without pre-
programmed.
• Humanoid Robots are best examples for AI in robotics, recently the intelligent Humanoid robot named as Erica and Sophia has been

23.  10. AI in Entertainment
• We are currently using some AI based applications in our daily life with some entertainment services such as
Netflix or Amazon. With the help of ML/AI algorithms, these services show the recommendations for programs
or shows.
 11. AI in Agriculture
• Agriculture is an area which requires various resources, labor, money, and time for best result. Now a day's
agriculture is becoming digital, and AI is emerging in this field. Agriculture is applying AI as agriculture
robotics, solid and crop monitoring, predictive analysis. AI in agriculture can be very helpful for farmers.
 12. AI in E-commerce
• AI is providing a competitive edge to the e-commerce industry, and it is becoming more demanding in the e-
commerce business. AI is helping shoppers to discover associated products with recommended size, color, or
even brand.
 13. AI in education:
• AI can automate grading so that the tutor can have more time to teach. AI chatbot can communicate with
students as a teaching assistant.
• AI in the future can be work as a personal virtual tutor for students, which will be accessible easily at any time
and any place.