2. TIMELINE OF AI
3. CATEGORIES OF AI
4. BRANCHES OF AI
5. APPLICATIONS OF AI
6. TOOLS USED IN AI
7. MODERN APPLICATIONS OF AI
8. FIFTH GENERATION COMPUTING
9. AMERICAN ASSOCIATION FOR ARTIFICIAL INTELLIGENCE (AAAI)
10. FUTURE SCOPE
“The capacity to learn and solve problems” in particular.
The ability to solve novel problems.
The ability to act rationally.
The ability to act like humans.
Intelligence exhibited by an artificial entity.
Basically : Putting human intelligence into a machine.
Artificial intelligence (AI) is the intelligence exhibited by machines or software.
Major AI researchers and textbooks define this field as "the study and design of intelligent
agents", in which an intelligent agent is a system that perceives its environment and takes
actions that maximize its chances of success.
John McCarthy, who coined the term in 1955, defines
it as “the science and engineering of making intelligent machines’’.
Some say it’s putting the human mind into computers.
The field was founded on the claim that a central property of humans, human intelligence --
the sapience of Homo sapiens—"can be so precisely described that a machine can be made
to simulate it.
Artificial Intelligence and general artificial intelligence
are distinct areas of research.
General Intelligence is still among the field’s long term
Artificial intelligence refers to intelligence exhibited by
They can be broken down into:
Ability to move and
The AI field is interdisciplinary,
in which a number of sciences
and professions converge.
INTELLIGENCE (weak AI)
INTELLIGENCE (strong AI)
ARTIFICIAL SUPER INTELLIGENCE
BRANCHES OF AI
Common sense knowledge and
APPLICATIONS OF AI
Hospitals and medicine
Understanding natural language
The first expert systems were created in the 1970s and then proliferated
in the 1980s.
Expert systems were introduced by the Stanford Heuristic
Programming Project led by Edward Albert Feigenbaum , who is
sometimes referred to as the "Father of expert systems".
In artificial intelligence, an expert system is a computer system that
emulates the decision-making ability of a human expert.
A computer application that performs a task that would otherwise be
performed by a human expert.
For example, there are expert systems that can diagnose human
illnesses, make financial forecasts, and schedule routes for delivery
Some expert systems are designed to take the place of human experts,
while others are designed to aid them.
An expert system is divided into two sub-systems:
The knowledge base represents facts and rules.
To design an expert system, one needs a knowledge engineer, an
individual who studies how human experts make decisions and translates
the rules into terms that a computer can understand.
The inference engine applies the rules to the known facts to deduce new
facts. Inference engines can also include explanation and debugging
A ``knowledge engineer'' interviews experts in a certain domain and tries to embody their
knowledge in a computer program for carrying out some task.
How well this works depends on whether the intellectual mechanisms required for the task are
within the present state of AI.
When this turned out not to be so, there were many disappointing results.
One of the first expert systems was MYCIN in 1974, which diagnosed bacterial infections of the
blood and suggested treatments.
It did better than medical students or practicing doctors, provided its limitations were observed.
Namely, its ontology included bacteria, symptoms, and treatments and did not include patients,
doctors, hospitals, death, recovery, and events occurring in time. Its interactions depended on a
single patient being considered.
Since the experts consulted by the knowledge engineers knew about patients, doctors, death,
recovery, etc., it is clear that the knowledge engineers forced what the experts told them into a
In the present state of AI, this has to be true. The usefulness of current expert systems depends on
their users having common sense.
Natural Language Processing
Three basic types of processing occur during human/ computer voice interaction,
Using a computer to recreate the sound of human speech
Using a computer to recognize the words spoken by a human
Natural language comprehension
Using a computer to apply a meaningful interpretation to human communication
TOOLS USED IN AI
In the course of 50 years of research, AI has developed a large number of tools to
solve the most difficult problems in computer science. A few of the most general
of these methods are discussed below.
Search and optimization
Probabilistic methods for uncertain reasoning
Classifiers and statistical learning methods
A neural network is an interconnected group of nodes, akin to the vast
network of neurons in the human brain.
AIML (Artificial Intelligence Markup Language) for use with A.L.I.C.E.-type chatterbots.
IPL was the first language developed for artificial intelligence.
Lisp is a practical mathematical notation for computer programs based on lambda calculus. There
are many dialects of Lisp in use today, among them are Common Lisp, Scheme, and Clojure .
Prolog is a declarative language where programs are expressed in terms of relations, and execution
occurs by running queries over these relations. Prolog is widely used in AI today.
STRIPS is a language for expressing automated planning problem instances
Planner is a hybrid between procedural and logical languages. It gives a procedural interpretation to
Python is very widely used for Artificial Intelligence. They have a lot of different AIs with
corresponding packages: General AI, Machine Learning, Natural Language Processing and Neural
AI applications are also often written in standard languages like C++ and languages designed for
mathematics, such as MATLAB and Lush.
FIFTH GENERATION COMPUTING
The term "fifth generation" was intended to convey the system as being a leap
beyond existing machines.
In the history of computing hardware,
First generation(1940 -1956) : Computers using vacuum tubes.
Second generation(1956 -1963): Computers using transistors and diodes.
Third generation(1964 -1971): Computers using integrated circuits.
Fourth generation(1971- present): Computers using microprocessors.
Whereas previous computer generations had focused on increasing the number of
logic elements in a single CPU, the fifth generation (present and beyond),
instead turn to massive numbers of CPUs for added performance.
FIFTH GENERATION COMPUTING
The Fifth Generation Computer Systems project (FGCS) was an initiative by
Japan's Ministry of International Trade and Industry, begun in 1982, to create a computer
using massively parallel computing/processing.
It aimed to create an "epoch-making computer" with-supercomputer-like performance
and to provide a platform for future developments in artificial intelligence.
Fifth generation computing devices, based on artificial intelligence, are still in
development, though there are some applications, such as voice recognition, that are
being used today. The use of parallel processing and superconductors is helping to make
artificial intelligence a reality.
Association for the Advancement of Artificial
Founded in 1979, the Association for the Advancement
of Artificial Intelligence (AAAI) (formerly the
American Association for Artificial Intelligence) is a
nonprofit scientific society devoted to advancing the
scientific understanding of the mechanisms underlying
thought and intelligent behavior and their embodiment
AAAI aims to promote research in, and responsible
use of, artificial intelligence.
• Artificial minds will just single mindedly pursue their aims and these aims may not
necessarily coincide with ours.
• “WE’RE UNLIKELY EVER TO BE ABLE TO EFFECTIVELY
CONTROL ANY SUPER INTELLIGENCE WE CREATE”.
• A machine would’nt
specifically want to kill us but
its ammortality would mean that
it would be willing to cause our
extinction if necessary.
But,according to the optimists,in a world of artificial super intelligence
machines will still be our servants.
• The immediate priority of super intelligence would beto help us to create FREE ENERGY.
• In turn dramatically reducing the prices of almost everything.
• Everything currently costly,would drop to almost zero!!
• The way data costs now.