Course Title: Introduction to AI and Applications Course Code: 25ET12TL
Module-1: Introduction to Artificial Intelligence
Introduction to Artificial Intelligence: Artificial Intelligence, How Does AI Work? Advantages
and Disadvantages of Artificial Intelligence, Types of Artificial Intelligence, Weak AI, Strong AI,
Reactive Machines, Limited Memory, Theory of Mind, Self-Awareness.
Machine Intelligence: Defining Intelligence, Components of Intelligence, Differences Between
Human and Machine Intelligence, Agent and Environment, Search, Uninformed Search
Algorithms, Informed Search Algorithms: Pure Heuristic Search, Best-First Search Algorithm
(Greedy Search).
Introduction:
What is artificial Intelligence?
In 2004, John McCarthy defined artificial intelligence (AI) as the science and
engineering of making intelligent machines, especially intelligent computer
programs.
However, much before this definition was coined, the birth of AI was marked by
Alan Turing’s seminal work, ‘Computing Machinery and Intelligence,’
published in 1950.
Alan Turing, also known as the ‘father of computer science,’ raised questions like
‘Can machines think?’
Few languages that are popularly used to code AI applications are
1. R language: is often used for statistical computing and graphical presentation
to analyze and visualize data.
2. Python language: is a high-level, general-purpose programming language
often used to build websites and software, automate tasks, and conduct data
analysis.
3. Java: is a high-level, object-oriented programming language used to build
web apps, mobile applications, and enterprise software systems.
How Does AI Work?
AI systems work effectively when fed with a large amount of labelled training
data. This data is thoroughly analyzed to discover correlations and patterns.
These patterns are then used to make predictions about future states.
1
,For example, a chatbot (chat box) fed with examples of text chats can learn to
converse with humans in real-world applications.
AI programming focuses on three cognitive skills:
1. Learning: AI programs focus on acquiring data and creating rules for turning that
data into actionable information. Rules, also known as algorithms, pro-vide step-by-
step instructions to complete a specific task.
2. Reasoning: The success of an AI program depends on choosing the right algorithm
to reach the desired outcome.
3. Self-correction: AI programs are designed to continually enhance their algorithms
to pro-vide the most accurate results.
Advantages of Artificial Intelligence:
1. Performs well on tasks that uses detailed data.
2. Takes less time to perform tasks that needs to process huge volumes of data.
3. Generates consistent and accurate results.
4. Can be used 24 X 7.
5. Optimizes tasks by better utilizing resources.
6. Automates complex processes.
7. Minimizes downtime by predicting maintenance needs.
8. Enables companies to produce new products having better quality and speed.
Disadvantages of Artificial Intelligence:
1. Involves more cost.
2. Technical expertise required to develop and use AI applications.
3. Lack of trained professionals.
4. Incomplete or inaccurate data may result in disastrous results.
5. Lacks the capability to generalize tasks.
2
, Types of Artificial Intelligence
We can classify an artificial intelligent system into one of the following categories as
shown in Figure 1.
FIGURE 1: Types of Artificial Intelligence
1. Weak AI / Narrow AI: is specifically designed to perform a specific type of task.
For example, Siri and Alexa are weak AI systems. These systems are already trained
with appropriate responses to classify things accordingly. When you instruct Alexa to
play a song, it responds by playing that song.
In fact, majority of AI applications that we use today (predicting weather, stock
prices, optimizing business, etc.) come under this category.
Weak AI systems operate within a limited context and are the most successful
realization of artificial intelligence to date.
Application of narrow AI has resulted in significant societal benefits. Google
search, Image recognition software, self-driving cars and IBM’s Watson are
some examples of such systems.
3
Module-1: Introduction to Artificial Intelligence
Introduction to Artificial Intelligence: Artificial Intelligence, How Does AI Work? Advantages
and Disadvantages of Artificial Intelligence, Types of Artificial Intelligence, Weak AI, Strong AI,
Reactive Machines, Limited Memory, Theory of Mind, Self-Awareness.
Machine Intelligence: Defining Intelligence, Components of Intelligence, Differences Between
Human and Machine Intelligence, Agent and Environment, Search, Uninformed Search
Algorithms, Informed Search Algorithms: Pure Heuristic Search, Best-First Search Algorithm
(Greedy Search).
Introduction:
What is artificial Intelligence?
In 2004, John McCarthy defined artificial intelligence (AI) as the science and
engineering of making intelligent machines, especially intelligent computer
programs.
However, much before this definition was coined, the birth of AI was marked by
Alan Turing’s seminal work, ‘Computing Machinery and Intelligence,’
published in 1950.
Alan Turing, also known as the ‘father of computer science,’ raised questions like
‘Can machines think?’
Few languages that are popularly used to code AI applications are
1. R language: is often used for statistical computing and graphical presentation
to analyze and visualize data.
2. Python language: is a high-level, general-purpose programming language
often used to build websites and software, automate tasks, and conduct data
analysis.
3. Java: is a high-level, object-oriented programming language used to build
web apps, mobile applications, and enterprise software systems.
How Does AI Work?
AI systems work effectively when fed with a large amount of labelled training
data. This data is thoroughly analyzed to discover correlations and patterns.
These patterns are then used to make predictions about future states.
1
,For example, a chatbot (chat box) fed with examples of text chats can learn to
converse with humans in real-world applications.
AI programming focuses on three cognitive skills:
1. Learning: AI programs focus on acquiring data and creating rules for turning that
data into actionable information. Rules, also known as algorithms, pro-vide step-by-
step instructions to complete a specific task.
2. Reasoning: The success of an AI program depends on choosing the right algorithm
to reach the desired outcome.
3. Self-correction: AI programs are designed to continually enhance their algorithms
to pro-vide the most accurate results.
Advantages of Artificial Intelligence:
1. Performs well on tasks that uses detailed data.
2. Takes less time to perform tasks that needs to process huge volumes of data.
3. Generates consistent and accurate results.
4. Can be used 24 X 7.
5. Optimizes tasks by better utilizing resources.
6. Automates complex processes.
7. Minimizes downtime by predicting maintenance needs.
8. Enables companies to produce new products having better quality and speed.
Disadvantages of Artificial Intelligence:
1. Involves more cost.
2. Technical expertise required to develop and use AI applications.
3. Lack of trained professionals.
4. Incomplete or inaccurate data may result in disastrous results.
5. Lacks the capability to generalize tasks.
2
, Types of Artificial Intelligence
We can classify an artificial intelligent system into one of the following categories as
shown in Figure 1.
FIGURE 1: Types of Artificial Intelligence
1. Weak AI / Narrow AI: is specifically designed to perform a specific type of task.
For example, Siri and Alexa are weak AI systems. These systems are already trained
with appropriate responses to classify things accordingly. When you instruct Alexa to
play a song, it responds by playing that song.
In fact, majority of AI applications that we use today (predicting weather, stock
prices, optimizing business, etc.) come under this category.
Weak AI systems operate within a limited context and are the most successful
realization of artificial intelligence to date.
Application of narrow AI has resulted in significant societal benefits. Google
search, Image recognition software, self-driving cars and IBM’s Watson are
some examples of such systems.
3
