All Courses
Get the App Signup / Login
Sign in Open App
Class 10 Exam  >  Class 10 Notes  >  Artificial Intelligence for Class 10  >  Introduction to AI: Basics of AI

Introduction to AI: Basics of AI | Artificial Intelligence for Class 10 PDF Download

Download, print and study this document offline
Please wait while the PDF view is loading
 Page 1


 
 
Encyclopaedia Britannica 
Introduction to AI: Basics of AI 
As discussed in the last chapter, Artificial Intelligence has always been a term which intrigues people 
all over the world. Various organisations have coined their own versions of defining Artificial 
Intelligence. Some of them are mentioned below: 
  NITI Aayog: National Strategy for Artificial Intelligence 
AI refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, 
problem solving and decision making. Initially conceived as a technology that could mimic human 
intelligence, AI has evolved in ways that far exceed its original conception. With incredible advances 
made in data collection, processing and computation power, intelligent systems can now be deployed 
to take over a variety of tasks, enable connectivity and enhance productivity. 
  World Economic Forum 
Artificial intelligence (AI) is the software engine that drives the Fourth Industrial Revolution. Its impact 
can already be seen in homes, businesses and political processes. In its embodied form of robots, it 
will soon be driving cars, stocking warehouses and caring for the young and elderly. It holds the 
promise of solving some of the most pressing issues facing society, but also presents challenges such 
as inscrutable “black box” algorithms, unethical use of data and potential job displacement. As rapid 
advances in machine learning (ML) increase the scope and scale of AI’s deployment across all aspects 
of daily life, and as the technology itself can learn and change on its own, multi-stakeholder 
collaboration is required to optimize accountability, transparency, privacy and impartiality to create 
trust. 
  European Artificial Intelligence (AI) leadership, the path for an integrated vision 
AI is not a well-defined technology and no universally agreed definition exists. It is rather a cover term 
for techniques associated with data analysis and pattern recognition. AI is not a new technology, 
having existed since the 1950s. While some markets, sectors and individual businesses are more 
advanced than others, AI is still at a relatively early stage of development, so that the range of 
potential applications, and the quality of most existing applications, have ample margins left for 
further development and improvement. 
 
Artificial intelligence (AI), is the ability of a digital computer or computer-controlled robot to 
perform tasks commonly associated with intelligent beings. The term is frequently applied to the 
project of developing systems endowed with the intellectual processes characteristic of humans, such 
as the ability to reason, discover meaning, generalize, or learn from past experience. 
 
  
Page 2


 
 
Encyclopaedia Britannica 
Introduction to AI: Basics of AI 
As discussed in the last chapter, Artificial Intelligence has always been a term which intrigues people 
all over the world. Various organisations have coined their own versions of defining Artificial 
Intelligence. Some of them are mentioned below: 
  NITI Aayog: National Strategy for Artificial Intelligence 
AI refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, 
problem solving and decision making. Initially conceived as a technology that could mimic human 
intelligence, AI has evolved in ways that far exceed its original conception. With incredible advances 
made in data collection, processing and computation power, intelligent systems can now be deployed 
to take over a variety of tasks, enable connectivity and enhance productivity. 
  World Economic Forum 
Artificial intelligence (AI) is the software engine that drives the Fourth Industrial Revolution. Its impact 
can already be seen in homes, businesses and political processes. In its embodied form of robots, it 
will soon be driving cars, stocking warehouses and caring for the young and elderly. It holds the 
promise of solving some of the most pressing issues facing society, but also presents challenges such 
as inscrutable “black box” algorithms, unethical use of data and potential job displacement. As rapid 
advances in machine learning (ML) increase the scope and scale of AI’s deployment across all aspects 
of daily life, and as the technology itself can learn and change on its own, multi-stakeholder 
collaboration is required to optimize accountability, transparency, privacy and impartiality to create 
trust. 
  European Artificial Intelligence (AI) leadership, the path for an integrated vision 
AI is not a well-defined technology and no universally agreed definition exists. It is rather a cover term 
for techniques associated with data analysis and pattern recognition. AI is not a new technology, 
having existed since the 1950s. While some markets, sectors and individual businesses are more 
advanced than others, AI is still at a relatively early stage of development, so that the range of 
potential applications, and the quality of most existing applications, have ample margins left for 
further development and improvement. 
 
Artificial intelligence (AI), is the ability of a digital computer or computer-controlled robot to 
perform tasks commonly associated with intelligent beings. The term is frequently applied to the 
project of developing systems endowed with the intellectual processes characteristic of humans, such 
as the ability to reason, discover meaning, generalize, or learn from past experience. 
 
  
 
 
As you can see, Artificial Intelligence is a vast domain. Everyone looks at AI in a different way according 
to their mindset. Now, according to your knowledge of AI, start filling the KWLH chart: 
 
What do you know about Artificial Intelligence (AI)? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________  
What do you want to know about AI?  
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
What have you learnt about AI? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
How have you learnt this about AI? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
  
  
K
• What I Know?
W
• What I Want to know?
L
• What have I learned?
H
• How I learnt this?
Page 3


 
 
Encyclopaedia Britannica 
Introduction to AI: Basics of AI 
As discussed in the last chapter, Artificial Intelligence has always been a term which intrigues people 
all over the world. Various organisations have coined their own versions of defining Artificial 
Intelligence. Some of them are mentioned below: 
  NITI Aayog: National Strategy for Artificial Intelligence 
AI refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, 
problem solving and decision making. Initially conceived as a technology that could mimic human 
intelligence, AI has evolved in ways that far exceed its original conception. With incredible advances 
made in data collection, processing and computation power, intelligent systems can now be deployed 
to take over a variety of tasks, enable connectivity and enhance productivity. 
  World Economic Forum 
Artificial intelligence (AI) is the software engine that drives the Fourth Industrial Revolution. Its impact 
can already be seen in homes, businesses and political processes. In its embodied form of robots, it 
will soon be driving cars, stocking warehouses and caring for the young and elderly. It holds the 
promise of solving some of the most pressing issues facing society, but also presents challenges such 
as inscrutable “black box” algorithms, unethical use of data and potential job displacement. As rapid 
advances in machine learning (ML) increase the scope and scale of AI’s deployment across all aspects 
of daily life, and as the technology itself can learn and change on its own, multi-stakeholder 
collaboration is required to optimize accountability, transparency, privacy and impartiality to create 
trust. 
  European Artificial Intelligence (AI) leadership, the path for an integrated vision 
AI is not a well-defined technology and no universally agreed definition exists. It is rather a cover term 
for techniques associated with data analysis and pattern recognition. AI is not a new technology, 
having existed since the 1950s. While some markets, sectors and individual businesses are more 
advanced than others, AI is still at a relatively early stage of development, so that the range of 
potential applications, and the quality of most existing applications, have ample margins left for 
further development and improvement. 
 
Artificial intelligence (AI), is the ability of a digital computer or computer-controlled robot to 
perform tasks commonly associated with intelligent beings. The term is frequently applied to the 
project of developing systems endowed with the intellectual processes characteristic of humans, such 
as the ability to reason, discover meaning, generalize, or learn from past experience. 
 
  
 
 
As you can see, Artificial Intelligence is a vast domain. Everyone looks at AI in a different way according 
to their mindset. Now, according to your knowledge of AI, start filling the KWLH chart: 
 
What do you know about Artificial Intelligence (AI)? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________  
What do you want to know about AI?  
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
What have you learnt about AI? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
How have you learnt this about AI? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
  
  
K
• What I Know?
W
• What I Want to know?
L
• What have I learned?
H
• How I learnt this?
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
 
In other words, AI can be defined as: 
AI is a form of Intelligence; a type of technology and a field of study.  
AI theory and development of computer systems (both machines and software) enables machines to 
perform tasks that normally require human intelligence.  
Artificial Intelligence covers a broad range of domains and applications and is expected to impact every 
field in the future. Overall, its core idea is building machines and algorithms which are capable of 
performing computational tasks that would otherwise require human like brain functions. 
AI, ML & DL 
As you have been progressing towards building AI readiness, you must have come across a very 
common dilemma between Artificial Intelligence (AI) and Machine Learning (ML). Many times, these 
terms are used interchangeably but are they the same? Is there no difference in Machine Learning 
and Artificial Intelligence? Is Deep Learning (DL) Also Artificial Intelligence? What exactly is Deep 
Learning? Let us see. 
 
Artificial Intelligence (AI) 
Refers to any technique that enables computers to mimic human intelligence.  It gives the ability to 
machines to recognize a human’s face; to move and manipulate objects; to understand the voice 
commands by humans, and also do other tasks. The AI-enabled machines think algorithmically and 
execute what they have been asked for intelligently. 
Machine Learning (ML) 
It is a subset of Artificial Intelligence which enables machines to improve at tasks with experience 
(data). The intention of Machine Learning is to enable machines to learn by themselves using the 
provided data and make accurate Predictions/ Decisions. 
Page 4


 
 
Encyclopaedia Britannica 
Introduction to AI: Basics of AI 
As discussed in the last chapter, Artificial Intelligence has always been a term which intrigues people 
all over the world. Various organisations have coined their own versions of defining Artificial 
Intelligence. Some of them are mentioned below: 
  NITI Aayog: National Strategy for Artificial Intelligence 
AI refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, 
problem solving and decision making. Initially conceived as a technology that could mimic human 
intelligence, AI has evolved in ways that far exceed its original conception. With incredible advances 
made in data collection, processing and computation power, intelligent systems can now be deployed 
to take over a variety of tasks, enable connectivity and enhance productivity. 
  World Economic Forum 
Artificial intelligence (AI) is the software engine that drives the Fourth Industrial Revolution. Its impact 
can already be seen in homes, businesses and political processes. In its embodied form of robots, it 
will soon be driving cars, stocking warehouses and caring for the young and elderly. It holds the 
promise of solving some of the most pressing issues facing society, but also presents challenges such 
as inscrutable “black box” algorithms, unethical use of data and potential job displacement. As rapid 
advances in machine learning (ML) increase the scope and scale of AI’s deployment across all aspects 
of daily life, and as the technology itself can learn and change on its own, multi-stakeholder 
collaboration is required to optimize accountability, transparency, privacy and impartiality to create 
trust. 
  European Artificial Intelligence (AI) leadership, the path for an integrated vision 
AI is not a well-defined technology and no universally agreed definition exists. It is rather a cover term 
for techniques associated with data analysis and pattern recognition. AI is not a new technology, 
having existed since the 1950s. While some markets, sectors and individual businesses are more 
advanced than others, AI is still at a relatively early stage of development, so that the range of 
potential applications, and the quality of most existing applications, have ample margins left for 
further development and improvement. 
 
Artificial intelligence (AI), is the ability of a digital computer or computer-controlled robot to 
perform tasks commonly associated with intelligent beings. The term is frequently applied to the 
project of developing systems endowed with the intellectual processes characteristic of humans, such 
as the ability to reason, discover meaning, generalize, or learn from past experience. 
 
  
 
 
As you can see, Artificial Intelligence is a vast domain. Everyone looks at AI in a different way according 
to their mindset. Now, according to your knowledge of AI, start filling the KWLH chart: 
 
What do you know about Artificial Intelligence (AI)? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________  
What do you want to know about AI?  
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
What have you learnt about AI? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
How have you learnt this about AI? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
  
  
K
• What I Know?
W
• What I Want to know?
L
• What have I learned?
H
• How I learnt this?
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
 
In other words, AI can be defined as: 
AI is a form of Intelligence; a type of technology and a field of study.  
AI theory and development of computer systems (both machines and software) enables machines to 
perform tasks that normally require human intelligence.  
Artificial Intelligence covers a broad range of domains and applications and is expected to impact every 
field in the future. Overall, its core idea is building machines and algorithms which are capable of 
performing computational tasks that would otherwise require human like brain functions. 
AI, ML & DL 
As you have been progressing towards building AI readiness, you must have come across a very 
common dilemma between Artificial Intelligence (AI) and Machine Learning (ML). Many times, these 
terms are used interchangeably but are they the same? Is there no difference in Machine Learning 
and Artificial Intelligence? Is Deep Learning (DL) Also Artificial Intelligence? What exactly is Deep 
Learning? Let us see. 
 
Artificial Intelligence (AI) 
Refers to any technique that enables computers to mimic human intelligence.  It gives the ability to 
machines to recognize a human’s face; to move and manipulate objects; to understand the voice 
commands by humans, and also do other tasks. The AI-enabled machines think algorithmically and 
execute what they have been asked for intelligently. 
Machine Learning (ML) 
It is a subset of Artificial Intelligence which enables machines to improve at tasks with experience 
(data). The intention of Machine Learning is to enable machines to learn by themselves using the 
provided data and make accurate Predictions/ Decisions. 
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
 
Deep Learning (DL) 
It enables software to train itself to perform tasks with vast amounts of data. In Deep Learning, the 
machine is trained with huge amounts of data which helps it in training itself around the data. Such 
machines are intelligent enough to develop algorithms for themselves. Deep Learning is the most 
advanced form of Artificial Intelligence out of these three. Then comes Machine Learning which is 
intermediately intelligent and Artificial Intelligence covers all the concepts and algorithms which, in 
some way or the other mimic human intelligence. 
There are a lot of applications of AI out of which few are those which come under ML out of which 
very few can be labelled as DL. Therefore, Machine Learning (ML) and Deep Learning (DL) are part of 
Artificial Intelligence (AI), but not everything that is Machine learning will be Deep learning. 
Introduction to AI Domains 
Artificial Intelligence becomes intelligent according to the training which it gets. For training, the 
machine is fed with datasets. According to the applications for which the AI algorithm is being 
developed, the data which is fed into it changes. With respect to the type of data fed in the AI 
model, AI models can be broadly categorised into three domains: 
Data Sciences 
Data sciences is a domain of AI related to data systems and processes, in which the system collects 
numerous data, maintains data sets and derives meaning/sense out of them.  
The information extracted through data science can be used to make a decision about it.  
Example of Data Science 
Price Comparison Websites  
These websites are being driven by lots and lots of data. If you have 
ever used these websites, you would know, the convenience of 
comparing the price of a product from multiple vendors at one 
place. PriceGrabber, PriceRunner, Junglee, Shopzilla, DealTime are 
some examples of price comparison websites. Now a days, price 
comparison website can be found in almost every domain such as 
technology, hospitality, automobiles, durables, apparels etc. 
 
 
Computer Vision 
Computer Vision, abbreviated as CV, is a domain of AI that depicts the capability of a machine to get 
and analyse visual information and afterwards predict some decisions about it. The entire process 
involves image acquiring, screening, analysing, identifying and extracting information. This extensive 
processing helps computers to understand any visual content and act on it accordingly. In computer 
vision, Input to machines can be photographs, videos and pictures from thermal or infrared sensors, 
indicators and different sources.  
Data Sciences Natural Language Processing Computer Vision 
Page 5


 
 
Encyclopaedia Britannica 
Introduction to AI: Basics of AI 
As discussed in the last chapter, Artificial Intelligence has always been a term which intrigues people 
all over the world. Various organisations have coined their own versions of defining Artificial 
Intelligence. Some of them are mentioned below: 
  NITI Aayog: National Strategy for Artificial Intelligence 
AI refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, 
problem solving and decision making. Initially conceived as a technology that could mimic human 
intelligence, AI has evolved in ways that far exceed its original conception. With incredible advances 
made in data collection, processing and computation power, intelligent systems can now be deployed 
to take over a variety of tasks, enable connectivity and enhance productivity. 
  World Economic Forum 
Artificial intelligence (AI) is the software engine that drives the Fourth Industrial Revolution. Its impact 
can already be seen in homes, businesses and political processes. In its embodied form of robots, it 
will soon be driving cars, stocking warehouses and caring for the young and elderly. It holds the 
promise of solving some of the most pressing issues facing society, but also presents challenges such 
as inscrutable “black box” algorithms, unethical use of data and potential job displacement. As rapid 
advances in machine learning (ML) increase the scope and scale of AI’s deployment across all aspects 
of daily life, and as the technology itself can learn and change on its own, multi-stakeholder 
collaboration is required to optimize accountability, transparency, privacy and impartiality to create 
trust. 
  European Artificial Intelligence (AI) leadership, the path for an integrated vision 
AI is not a well-defined technology and no universally agreed definition exists. It is rather a cover term 
for techniques associated with data analysis and pattern recognition. AI is not a new technology, 
having existed since the 1950s. While some markets, sectors and individual businesses are more 
advanced than others, AI is still at a relatively early stage of development, so that the range of 
potential applications, and the quality of most existing applications, have ample margins left for 
further development and improvement. 
 
Artificial intelligence (AI), is the ability of a digital computer or computer-controlled robot to 
perform tasks commonly associated with intelligent beings. The term is frequently applied to the 
project of developing systems endowed with the intellectual processes characteristic of humans, such 
as the ability to reason, discover meaning, generalize, or learn from past experience. 
 
  
 
 
As you can see, Artificial Intelligence is a vast domain. Everyone looks at AI in a different way according 
to their mindset. Now, according to your knowledge of AI, start filling the KWLH chart: 
 
What do you know about Artificial Intelligence (AI)? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________  
What do you want to know about AI?  
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
What have you learnt about AI? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
How have you learnt this about AI? 
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________
__________________________________________________________________________________ 
  
  
K
• What I Know?
W
• What I Want to know?
L
• What have I learned?
H
• How I learnt this?
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
 
In other words, AI can be defined as: 
AI is a form of Intelligence; a type of technology and a field of study.  
AI theory and development of computer systems (both machines and software) enables machines to 
perform tasks that normally require human intelligence.  
Artificial Intelligence covers a broad range of domains and applications and is expected to impact every 
field in the future. Overall, its core idea is building machines and algorithms which are capable of 
performing computational tasks that would otherwise require human like brain functions. 
AI, ML & DL 
As you have been progressing towards building AI readiness, you must have come across a very 
common dilemma between Artificial Intelligence (AI) and Machine Learning (ML). Many times, these 
terms are used interchangeably but are they the same? Is there no difference in Machine Learning 
and Artificial Intelligence? Is Deep Learning (DL) Also Artificial Intelligence? What exactly is Deep 
Learning? Let us see. 
 
Artificial Intelligence (AI) 
Refers to any technique that enables computers to mimic human intelligence.  It gives the ability to 
machines to recognize a human’s face; to move and manipulate objects; to understand the voice 
commands by humans, and also do other tasks. The AI-enabled machines think algorithmically and 
execute what they have been asked for intelligently. 
Machine Learning (ML) 
It is a subset of Artificial Intelligence which enables machines to improve at tasks with experience 
(data). The intention of Machine Learning is to enable machines to learn by themselves using the 
provided data and make accurate Predictions/ Decisions. 
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
 
Deep Learning (DL) 
It enables software to train itself to perform tasks with vast amounts of data. In Deep Learning, the 
machine is trained with huge amounts of data which helps it in training itself around the data. Such 
machines are intelligent enough to develop algorithms for themselves. Deep Learning is the most 
advanced form of Artificial Intelligence out of these three. Then comes Machine Learning which is 
intermediately intelligent and Artificial Intelligence covers all the concepts and algorithms which, in 
some way or the other mimic human intelligence. 
There are a lot of applications of AI out of which few are those which come under ML out of which 
very few can be labelled as DL. Therefore, Machine Learning (ML) and Deep Learning (DL) are part of 
Artificial Intelligence (AI), but not everything that is Machine learning will be Deep learning. 
Introduction to AI Domains 
Artificial Intelligence becomes intelligent according to the training which it gets. For training, the 
machine is fed with datasets. According to the applications for which the AI algorithm is being 
developed, the data which is fed into it changes. With respect to the type of data fed in the AI 
model, AI models can be broadly categorised into three domains: 
Data Sciences 
Data sciences is a domain of AI related to data systems and processes, in which the system collects 
numerous data, maintains data sets and derives meaning/sense out of them.  
The information extracted through data science can be used to make a decision about it.  
Example of Data Science 
Price Comparison Websites  
These websites are being driven by lots and lots of data. If you have 
ever used these websites, you would know, the convenience of 
comparing the price of a product from multiple vendors at one 
place. PriceGrabber, PriceRunner, Junglee, Shopzilla, DealTime are 
some examples of price comparison websites. Now a days, price 
comparison website can be found in almost every domain such as 
technology, hospitality, automobiles, durables, apparels etc. 
 
 
Computer Vision 
Computer Vision, abbreviated as CV, is a domain of AI that depicts the capability of a machine to get 
and analyse visual information and afterwards predict some decisions about it. The entire process 
involves image acquiring, screening, analysing, identifying and extracting information. This extensive 
processing helps computers to understand any visual content and act on it accordingly. In computer 
vision, Input to machines can be photographs, videos and pictures from thermal or infrared sensors, 
indicators and different sources.  
Data Sciences Natural Language Processing Computer Vision 
 
* Images shown here are the property of individual organisations and are used here for reference purpose only. 
 
Computer vision related projects translate digital visual data into descriptions. This data is then turned 
into computer-readable language to aid the decision-making process. The main objective of this 
domain of AI is to teach machines to collect information from pixels.  
Examples of Computer Vision 
Self-Driving cars/ Automatic Cars 
CV systems scan live objects and analyse them, based on whether 
the car decides to keep running or to stop. 
 
 
 
 
Face Lock in Smartphones 
Smartphones nowadays come with the feature of face locks in 
which the smartphone’s owner can set up his/her face as an 
unlocking mechanism for it. The front camera detects and captures 
the face and saves its features during initiation. Next time onwards, 
whenever the features match, the phone is unlocked. 
 
 
Natural Language Processing 
Natural Language Processing, abbreviated as NLP, is a branch of artificial intelligence that deals with 
the interaction between computers and humans using the natural language. Natural language refers 
to language that is spoken and written by people, and natural language processing (NLP) attempts to 
extract information from the spoken and written word using algorithms.  
The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages 
in a manilr that is valuable. 
Examples of Natural Language Processing 
 
Email filters 
Email filters are one of the most basic and 
initial applications of NLP online. It started 
out with spam filters, uncovering certain 
words or phrases that signal a spam 
message.
Read More
40 videos|35 docs|6 tests
Join Course for Free

Top Courses for Class 10

FAQs on Introduction to AI: Basics of AI - Artificial Intelligence for Class 10

1. What is AI and what are its basic principles?
Ans. AI, or Artificial Intelligence, refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. The basic principles of AI include machine learning, where machines are trained to learn from data and improve performance over time, and natural language processing, which enables machines to understand and interact with human language.
2. How is AI different from traditional programming?
Ans. AI differs from traditional programming in that traditional programming involves explicitly writing code to perform specific tasks, while AI allows machines to learn and adapt on their own. AI systems can analyze large amounts of data, make decisions, and improve their performance through iterations, whereas traditional programming relies on fixed instructions.
3. What are some real-life applications of AI?
Ans. AI has various real-life applications, including virtual assistants like Siri and Alexa, which use natural language processing to understand and respond to user queries. AI is also used in autonomous vehicles, fraud detection systems, recommendation engines, and medical diagnosis tools. Additionally, AI is utilized in industries such as finance, retail, and manufacturing for process automation and optimization.
4. What are the ethical concerns surrounding AI?
Ans. Ethical concerns related to AI include issues such as job displacement and the impact on employment due to automation. There are also concerns about privacy and data security, as AI systems often require access to large amounts of personal data. Bias and fairness in AI algorithms are additional concerns, as the decisions made by AI systems can reflect and perpetuate existing biases present in the data they were trained on.
5. How can individuals and organizations benefit from AI?
Ans. AI has the potential to bring numerous benefits to individuals and organizations. For individuals, AI can enhance everyday life by providing personalized recommendations, improving healthcare diagnostics, and enabling smart home automation. Organizations can utilize AI to optimize business processes, improve customer service, and gain valuable insights from large datasets. Additionally, AI has the potential to drive innovation and create new job opportunities in various industries.
Related Exams
About this Document
4.63/5 Rating
Dec 22, 2024 Last updated
Document Description: Introduction to AI: Basics of AI for Class 10 2024 is part of Artificial Intelligence for Class 10 preparation. The notes and questions for Introduction to AI: Basics of AI have been prepared according to the Class 10 exam syllabus. Information about Introduction to AI: Basics of AI covers topics like and Introduction to AI: Basics of AI Example, for Class 10 2024 Exam. Find important definitions, questions, notes, meanings, examples, exercises and tests below for Introduction to AI: Basics of AI.
Introduction of Introduction to AI: Basics of AI in English is available as part of our Artificial Intelligence for Class 10 for Class 10 & Introduction to AI: Basics of AI in Hindi for Artificial Intelligence for Class 10 course. Download more important topics related with notes, lectures and mock test series for Class 10 Exam by signing up for free. Class 10: Introduction to AI: Basics of AI | Artificial Intelligence for Class 10
Description
Full syllabus notes, lecture & questions for Introduction to AI: Basics of AI | Artificial Intelligence for Class 10 - Class 10 | Plus excerises question with solution to help you revise complete syllabus for Artificial Intelligence for Class 10 | Best notes, free PDF download
Information about Introduction to AI: Basics of AI
In this doc you can find the meaning of Introduction to AI: Basics of AI defined & explained in the simplest way possible. Besides explaining types of Introduction to AI: Basics of AI theory, EduRev gives you an ample number of questions to practice Introduction to AI: Basics of AI tests, examples and also practice Class 10 tests
40 videos|35 docs|6 tests
Join Course for Free
Download as PDF
Explore Courses for Class 10 exam

Top Courses for Class 10

Signup for Free!
Signup to see your scores go up within 7 days! Learn & Practice with 1000+ FREE Notes, Videos & Tests.
10M+ students study on EduRev
Related Searches

Sample Paper

,

Exam

,

past year papers

,

Free

,

practice quizzes

,

ppt

,

Semester Notes

,

mock tests for examination

,

Introduction to AI: Basics of AI | Artificial Intelligence for Class 10

,

Introduction to AI: Basics of AI | Artificial Intelligence for Class 10

,

Previous Year Questions with Solutions

,

Viva Questions

,

video lectures

,

Important questions

,

MCQs

,

study material

,

shortcuts and tricks

,

Extra Questions

,

Summary

,

Objective type Questions

,

pdf

,

Introduction to AI: Basics of AI | Artificial Intelligence for Class 10

;
Additional Information about Introduction to AI: Basics of AI for Class 10 Preparation

Introduction to AI: Basics of AI Free PDF Download

The Introduction to AI: Basics of AI is an invaluable resource that delves deep into the core of the Class 10 exam. These study notes are curated by experts and cover all the essential topics and concepts, making your preparation more efficient and effective. With the help of these notes, you can grasp complex subjects quickly, revise important points easily, and reinforce your understanding of key concepts. The study notes are presented in a concise and easy-to-understand manner, allowing you to optimize your learning process. Whether you're looking for best-recommended books, sample papers, study material, or toppers' notes, this PDF has got you covered. Download the Introduction to AI: Basics of AI now and kickstart your journey towards success in the Class 10 exam.

Importance of Introduction to AI: Basics of AI

The importance of Introduction to AI: Basics of AI cannot be overstated, especially for Class 10 aspirants. This document holds the key to success in the Class 10 exam. It offers a detailed understanding of the concept, providing invaluable insights into the topic. By knowing the concepts well in advance, students can plan their preparation effectively. Utilize this indispensable guide for a well-rounded preparation and achieve your desired results.

Introduction to AI: Basics of AI Notes

Introduction to AI: Basics of AI Notes offer in-depth insights into the specific topic to help you master it with ease. This comprehensive document covers all aspects related to Introduction to AI: Basics of AI. It includes detailed information about the exam syllabus, recommended books, and study materials for a well-rounded preparation. Practice papers and question papers enable you to assess your progress effectively. Additionally, the paper analysis provides valuable tips for tackling the exam strategically. Access to Toppers' notes gives you an edge in understanding complex concepts. Whether you're a beginner or aiming for advanced proficiency, Introduction to AI: Basics of AI Notes on EduRev are your ultimate resource for success.

Introduction to AI: Basics of AI Class 10 Questions

The "Introduction to AI: Basics of AI Class 10 Questions" guide is a valuable resource for all aspiring students preparing for the Class 10 exam. It focuses on providing a wide range of practice questions to help students gauge their understanding of the exam topics. These questions cover the entire syllabus, ensuring comprehensive preparation. The guide includes previous years' question papers for students to familiarize themselves with the exam's format and difficulty level. Additionally, it offers subject-specific question banks, allowing students to focus on weak areas and improve their performance.

Study Introduction to AI: Basics of AI on the App

Students of Class 10 can study Introduction to AI: Basics of AI alongwith tests & analysis from the EduRev app, which will help them while preparing for their exam. Apart from the Introduction to AI: Basics of AI, students can also utilize the EduRev App for other study materials such as previous year question papers, syllabus, important questions, etc. The EduRev App will make your learning easier as you can access it from anywhere you want. The content of Introduction to AI: Basics of AI is prepared as per the latest Class 10 syllabus.
© EduRev
Education Revolution
Signup to see your scores go up within 7 days!
Access 1000+ FREE Docs, Videos and Tests
Takes less than 10 seconds to signup