Artificial Intelligence

Contents

Overview
Applications
Languages
A.I. Introduction

Introduction
Claiming to be able to recreate the capabilities of
the human mind, is both a challenge and an
inspiration for philosophy.

• It is the science and engineering of making
intelligent machines, especially intelligent
computer programs.

Are there limits to how intelligent
machines can be?
 Intelligence:
“the capacity to learn and solve problems”
 Artificial Intelligence:
◦ Artificial intelligence (AI) is
the intelligence of machines and robots
and the branch of computer science that
aims to create it
 the ability to solve problems
 the ability to act rationally
 the ability to act like humans

Philosophy of A.I.
 Searle's strong AI hypothesis:
"The appropriately
programmed computer with
the right inputs & outputs
would thereby have a mind in
exactly the same sense
human beings have minds."
 The artificial brain argument:
The brain can be simulated.
 Technologically feasible to
copy the brain directly into
hardware and software, and
that such a simulation will be
essentially identical to the
original.

History of artificial intelligence
 Classical philosophers
 Programmable Digital Computers
(1940)
 1943-1956:
• McCulloch & Pitts: Boolean circuit model of
brain
• Dartmouth meeting: "Artificial Intelligence“
name adopted
 The golden years 1956−1974

 1986-- Rise of machine learning
◦ Neural networks return to popularity
◦ Major advances in machine learning
algorithms and applications
 1995-- AI as Science
◦ Integration of learning, reasoning,
knowledge representation
◦ AI methods used in vision, language, data
mining, etc

 2006: face recognition software
available in consumer cameras
 2003-2007 Robot driving: DARPA
grand challenge

 Feb 2011 there came question
answering robot.

Can AI System
Work As
Efficient As
Human

 How complicated is our brain?
◦ Neuron
◦ 10 12 neurons in a human brain
◦ many more synapses (10 14) connecting these
neurons
◦ cycle time: 10 -3 seconds (1 millisecond)
 Howcomplex can we make
computers?
◦ 108 or more transistors per CPU
◦ supercomputer: hundreds of CPUs, 1012 bits of
RAM
◦ cycle times: order of 10 - 9 seconds
 Conclusion
YES

Languages
Artificial intelligence researchers have developed several
specialized programming languages for artificial intelligence
which include IPL, Lisp, Prolog, STRIPS, Planner, POP-11 etc.

LISP (Introduction)
Lisp is a family of computer
programming languages with a long
history and a distinctive, fully
parenthesized Polish prefix
notation.
The name LISP derives from "List
Processing". Linked lists are one of
Lisp languages' major data
structures, and Lisp source code is
itself made up of lists. As a result,
Lisp programs can manipulate
source code as a data structure,
giving rise to the macro systems
that allow programmers to create
new syntax or even new domain-
specific languages embedded in

LISP (Syntax & Semantics)
Lisp is an expression-oriented language.
Unlike most other languages, no distinction is
made between "expressions" and
"statements"; all code and data are written as
expressions. McCarthy's 1958 paper
introduced two types of syntax:
 S-expressions (Symbolic expressions)
(car (cons A B))
 M-expressions (Meta Expressions)
car[cons[A,B]]

LISP connection to A.I.
 LISP is an important language for artificial
Intelligence programming.
 LISP programs define how to perform an
algorithm on the expressions.
 Frames, networks and objects are
responsible for LISP’s popularity in the AI
community.
 Lisp is widely used in implementing the
tools of Artificial Intelligence.

PROLOG (Introduction)
Prolog is a general purpose logic programming language
associated with AI and computational linguistics.
Prolog has its roots in first-order and formal logic. It
is declarative and expressed in terms of relations,
represented as facts and rules.

PROLOG (Syntax &
Semantics)
In Prolog, program logic is expressed in terms of
relations, and a computation is initiated by running a
query over these relations.
In syntax and semantics following are considered:
 Data types
 Rules and facts
 Evaluation
 Loops
 Negation

PROLOG (Data Types)
 An atom, whose meanings is not defined.
 Numbers can be floats or integers.
 Variables are strings consisting of letters, numbers and
underscore characters, and beginning with an upper-case
letter or underscore(_).

Comparison
LISP PROLOG

Functional language Logical language

General purpose Specific uses

Handles wide variety of tasks, easier
Smaller language, easier to learn
to use

Dn’t support compared to prolog Supports multidirectional reasoning

Parent disciplines of AI:
It is a broad field with so many subareas.

Applications of AI:
 Natural Language
Understanding
 Expert Systems
 Planning and Robotics
 Machine Learning
 Game Playing

Natural Language Processing
 To design and build software that will
analyze understand and generate
languages that human use naturally.

Modes of communication

 Text based.

 Dialogue based.

Speech Recognition

 Process of converting sound signal
captured by microphone or
mobile/telephone to a set of words.

 70-100 words / min with accuracy of
90%

Computer Vision
 Ability of a machine to extract
information from an image that is
necessary to solve a task

 Image Acquisition
 Image Processing
 Image Analysis
 Image understanding

Intelligent Robot
 Tend to mimic
human sensing
and decision
making abilities so
that they can adopt
themselves to
certain conditions
and modify their
actions.

Expert Systems
 These are
Softwares used for
decision making .
 Automated
Reasoning and
Theorem Proving.
 Troubleshooting
Expert Systems.
 Stock Market
Expert System.

Artificial Intelligence the need of
hour
 "Many thousands of AI applications
are deeply embedded in the
infrastructure of every industry."
 The late 90s and early 21st century, AI
technology became widely used as
elements of larger systems, but the
field is rarely credited for these
successes.

Fields of AI
Computer science:
 Graphical User Interface
 Automatic Storage management
 Object Oriented Programming
 Data miming
 computer gaming

 Telecommunication:
 Automated Online Assistants
 Voice dialing
 Speech Recognization

Fields of AI
Aviation & Automation:

 NASA's fight research
centre
 Voice recognition in fighter
jets
 Directions to A.I pilots
through air traffic
controllers
 Automatic Gearing System
in Cars

Fields of AI
Robotics:
 Assembling Robots
 Welding Robots
 Behavior based
robotics
 Dancing Robots
 Robot navigation

Daily life applications

 Home Security  News and
 Bank publishing
 Post office  Financial trades

 Websites  Health and

 Digital cameras medicine
 Games and toys

How AI is different????????
Artificial Intelligence Natural Intelligence

Non Creative Creative

Precise May Contain Error

Consistency Non Consistent

Multitasking Can’t Handle

Drawbacks of A.I

 Limited Ability
 Slow Real Time
Response
 Can’t Handle
Emergency
Situation
 Difficult code
 High Cost

Artificial Intelligence

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