CORE–13: Artificial Intelligence (Unit–1)
Introduction to Artificial Intelligence: Artificial Intelligence (AI) is a branch of
Science which deals with helping machines to find solutions to complex problems in
a more human-like fashion. This generally involves borrowing characteristics from
human intelligence, and applying them as algorithms in a computer friendly way.
AI can be defined as: “AI is the science and engineering of making intelligent
machines that can think like humans, act like humans, think rationally and can act
rationally”. It can be viewed from a variety of perspectives:
From the perspective of intelligence, artificial intelligence is making machines
"intelligent" -- acting as we would expect people to act.
The inability to distinguish computer responses from human responses is
called the Turing test.
Intelligence requires knowledge
From a business perspective AI is a set of very powerful tools, and
methodologies for using those tools to solve business problems.
From a programming perspective, AI includes the study of symbolic
programming, problem solving, and search.
Components of Artificial Intelligence:
Reasoning, problem-solving: Researchers had developed machines with
algorithms that enable machines to solve puzzles or quiz similar to humans. AI
can also deal with uncertain or incomplete information through advanced
algorithms.
Knowledge Representation: It is the representation of all the knowledge
which is stored by an agent to make an expert system. Knowledge can be a
set of objects, relations, concepts, or properties.
Planning: Intelligent agents should be able to set goals and make plans to
achieve those goals. They should be able to visualize the future and make
predictions about their actions taken for achieving the goal.
Learning: It is the study of the computer algorithms which improve
automatically through experiences. This concept is known as Machine
Learning.
Natural Language Processing: This processing enables a machine to read
and understand human language by processing the human language into
machine language.
Perception: An ability of the machine to use input from sensors, microphones,
wireless signals, etc. for understanding different aspects of the world.
Manas Ku Mishra, Asst. Prof. of Comp. Sc., FM (A) College, BLS. Page 1 of 12
, Types of AI: Artificial Intelligence
Type – 1 Type – 2
Based on Capabilities Based on functionality
Narrow General Strong Reactive Limited Theory Self
AI AI AI Machines Memory of mind Awareness
AI type-1: Based on Capabilities
1. Weak AI or Narrow AI: Narrow AI is a type of AI which is able to perform a
dedicated task with intelligence. The most common and currently available AI is
Narrow AI in the world of Artificial Intelligence. Narrow AI cannot perform beyond its
field or limitations, as it is only trained for one specific task. Hence it is also termed
as weak AI. Narrow AI can fail in unpredictable ways if it goes beyond its limits.
Some Examples of Narrow AI are playing chess, purchasing suggestions on e-
commerce site, self-driving cars, speech recognition, and image recognition.
2. General AI: General AI is a type of intelligence which could perform any
intellectual task with efficiency like a human. The idea behind the general AI is to
make such a system which could be smarter and think like a human by its own.
Currently, there is no such system exist which could come under general AI and can
perform any task as perfect as a human. The worldwide researchers are now
focusing on developing machines with General AI.
3. Super AI: Super AI is a level of Intelligence of Systems at which machines could
surpass human intelligence, and can perform any task better than human with
cognitive properties. It is an outcome of general AI. Some key characteristics of
strong AI include capability include the ability to think, to reason, solve the
puzzle, make judgments, plan, learn, and communicate by its own. Super AI is
still a hypothetical concept of Artificial Intelligence. Development of such systems in
real is a changing task.
Artificial Intelligence type-2: Based on functionality:
1. Reactive Machines: Purely reactive machines are the most basic types of
Artificial Intelligence. Such AI systems do not store past experiences for future
actions. These machines only focus on current scenarios and react on it as per
possible best action. IBM's Deep Blue system and Google’s AlphaGo are the
examples of reactive machines.
2. Limited Memory: Limited memory machines can store past experiences or
some data for a short period of time. These machines can use stored data for a
limited time period only. Self-driving cars is one of the best examples of Limited
Memory systems. These cars can store recent speed of nearby cars, the distance of
other cars, speed limit, and other information to navigate the road.
Manas Ku Mishra, Asst. Prof. of Comp. Sc., FM (A) College, BLS. Page 2 of 12
Introduction to Artificial Intelligence: Artificial Intelligence (AI) is a branch of
Science which deals with helping machines to find solutions to complex problems in
a more human-like fashion. This generally involves borrowing characteristics from
human intelligence, and applying them as algorithms in a computer friendly way.
AI can be defined as: “AI is the science and engineering of making intelligent
machines that can think like humans, act like humans, think rationally and can act
rationally”. It can be viewed from a variety of perspectives:
From the perspective of intelligence, artificial intelligence is making machines
"intelligent" -- acting as we would expect people to act.
The inability to distinguish computer responses from human responses is
called the Turing test.
Intelligence requires knowledge
From a business perspective AI is a set of very powerful tools, and
methodologies for using those tools to solve business problems.
From a programming perspective, AI includes the study of symbolic
programming, problem solving, and search.
Components of Artificial Intelligence:
Reasoning, problem-solving: Researchers had developed machines with
algorithms that enable machines to solve puzzles or quiz similar to humans. AI
can also deal with uncertain or incomplete information through advanced
algorithms.
Knowledge Representation: It is the representation of all the knowledge
which is stored by an agent to make an expert system. Knowledge can be a
set of objects, relations, concepts, or properties.
Planning: Intelligent agents should be able to set goals and make plans to
achieve those goals. They should be able to visualize the future and make
predictions about their actions taken for achieving the goal.
Learning: It is the study of the computer algorithms which improve
automatically through experiences. This concept is known as Machine
Learning.
Natural Language Processing: This processing enables a machine to read
and understand human language by processing the human language into
machine language.
Perception: An ability of the machine to use input from sensors, microphones,
wireless signals, etc. for understanding different aspects of the world.
Manas Ku Mishra, Asst. Prof. of Comp. Sc., FM (A) College, BLS. Page 1 of 12
, Types of AI: Artificial Intelligence
Type – 1 Type – 2
Based on Capabilities Based on functionality
Narrow General Strong Reactive Limited Theory Self
AI AI AI Machines Memory of mind Awareness
AI type-1: Based on Capabilities
1. Weak AI or Narrow AI: Narrow AI is a type of AI which is able to perform a
dedicated task with intelligence. The most common and currently available AI is
Narrow AI in the world of Artificial Intelligence. Narrow AI cannot perform beyond its
field or limitations, as it is only trained for one specific task. Hence it is also termed
as weak AI. Narrow AI can fail in unpredictable ways if it goes beyond its limits.
Some Examples of Narrow AI are playing chess, purchasing suggestions on e-
commerce site, self-driving cars, speech recognition, and image recognition.
2. General AI: General AI is a type of intelligence which could perform any
intellectual task with efficiency like a human. The idea behind the general AI is to
make such a system which could be smarter and think like a human by its own.
Currently, there is no such system exist which could come under general AI and can
perform any task as perfect as a human. The worldwide researchers are now
focusing on developing machines with General AI.
3. Super AI: Super AI is a level of Intelligence of Systems at which machines could
surpass human intelligence, and can perform any task better than human with
cognitive properties. It is an outcome of general AI. Some key characteristics of
strong AI include capability include the ability to think, to reason, solve the
puzzle, make judgments, plan, learn, and communicate by its own. Super AI is
still a hypothetical concept of Artificial Intelligence. Development of such systems in
real is a changing task.
Artificial Intelligence type-2: Based on functionality:
1. Reactive Machines: Purely reactive machines are the most basic types of
Artificial Intelligence. Such AI systems do not store past experiences for future
actions. These machines only focus on current scenarios and react on it as per
possible best action. IBM's Deep Blue system and Google’s AlphaGo are the
examples of reactive machines.
2. Limited Memory: Limited memory machines can store past experiences or
some data for a short period of time. These machines can use stored data for a
limited time period only. Self-driving cars is one of the best examples of Limited
Memory systems. These cars can store recent speed of nearby cars, the distance of
other cars, speed limit, and other information to navigate the road.
Manas Ku Mishra, Asst. Prof. of Comp. Sc., FM (A) College, BLS. Page 2 of 12
