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Define Artificial Intelligence.
Define Artificial Intelligence.
Artificial Intelligence (AI) is the ability of machines to do cognitive tasks such as thinking, perceiving, learning, problem solving, and decision making.
Explain the meaning of 'Artificial' in Artificial Intelligence.
Explain the meaning of 'Artificial' in Artificial Intelligence.
Artificial refers to something created or produced by humans rather than existing naturally.
What is the significance of 'Intelligence' in the term Artificial Intelligence?
What is the significance of 'Intelligence' in the term Artificial Intelligence?
Intelligence refers to the ability to acquire and use knowledge and skills.
According to NITI Aayog, how is Artificial Intelligence defined?
According to NITI Aayog, how is Artificial Intelligence defined?
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How has the World Economic Forum described Artificial Intelligence?
How has the World Economic Forum described Artificial Intelligence?
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What branch of artificial intelligence allows computers to learn and develop without being explicitly programmed?
What branch of artificial intelligence allows computers to learn and develop without being explicitly programmed?
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Who coined the phrase 'artificial intelligence' and hosted the first AI conference in 1956 at Dartmouth College?
Who coined the phrase 'artificial intelligence' and hosted the first AI conference in 1956 at Dartmouth College?
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What area of artificial intelligence focuses on assisting computers in understanding human language and communication?
What area of artificial intelligence focuses on assisting computers in understanding human language and communication?
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What type of computer software can handle complex issues and make decisions like a human expert?
What type of computer software can handle complex issues and make decisions like a human expert?
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In the context of artificial intelligence, what does computer vision enable computers and systems to do?
In the context of artificial intelligence, what does computer vision enable computers and systems to do?
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What is problem scoping in the AI Project Cycle?
What is problem scoping in the AI Project Cycle?
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Explain the 4 W's of Problem Scoping in AI projects.
Explain the 4 W's of Problem Scoping in AI projects.
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What is the significance of the Problem Canvas in the AI Project Cycle?
What is the significance of the Problem Canvas in the AI Project Cycle?
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How does the AI Project Cycle help in deriving value from AI projects?
How does the AI Project Cycle help in deriving value from AI projects?
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Why is it essential to acquire data from various sources in the AI Project Cycle?
Why is it essential to acquire data from various sources in the AI Project Cycle?
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What is the purpose of the 'What' section in problem analysis?
What is the purpose of the 'What' section in problem analysis?
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Define 'Data Acquisition' in the context of AI project cycle.
Define 'Data Acquisition' in the context of AI project cycle.
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What is the difference between structured and unstructured data?
What is the difference between structured and unstructured data?
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Explain what a 'Dataset' is and provide an example.
Explain what a 'Dataset' is and provide an example.
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What is the purpose of 'Acquiring Data from Reliable Sources' in an AI project cycle?
What is the purpose of 'Acquiring Data from Reliable Sources' in an AI project cycle?
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Study Notes
Defining Artificial Intelligence
- Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, and decision-making.
- The term "Artificial" in Artificial Intelligence refers to the creation of human-like intelligence that is not natural, but rather machine-made.
- The significance of "Intelligence" in the term Artificial Intelligence lies in the ability of machines to perform tasks that require reasoning, problem-solving, and learning.
Definitions of Artificial Intelligence
- According to NITI Aayog, Artificial Intelligence is defined as the ability of machines to perform tasks that typically require human intelligence.
- The World Economic Forum has described Artificial Intelligence as the ability of machines to perform tasks that typically require human intelligence, such as visual perception, speech recognition, and decision-making.
Branches of Artificial Intelligence
- Machine Learning is a branch of Artificial Intelligence that allows computers to learn and develop without being explicitly programmed.
- Natural Language Processing (NLP) is an area of Artificial Intelligence that focuses on assisting computers in understanding human language and communication.
History of Artificial Intelligence
- The phrase "Artificial Intelligence" was coined by John McCarthy, who hosted the first AI conference in 1956 at Dartmouth College.
Applications of Artificial Intelligence
- Expert Systems are a type of computer software that can handle complex issues and make decisions like a human expert.
- Computer Vision is a field of Artificial Intelligence that enables computers and systems to interpret and understand visual information from the world.
AI Project Cycle
- Problem Scoping is a stage in the AI Project Cycle that involves defining the problem and identifying the objectives of the project.
- The 4 W's of Problem Scoping in AI projects are: What, Why, Where, and When.
- The Problem Canvas is a tool used in the AI Project Cycle to visualize and structure the problem definition.
- The AI Project Cycle helps in deriving value from AI projects by providing a structured approach to problem-solving.
- Acquiring data from various sources is essential in the AI Project Cycle to ensure that the model is trained on diverse and representative data.
- The 'What' section in problem analysis involves identifying the problem statement and defining the objectives of the project.
- Data Acquisition is a stage in the AI Project Cycle that involves collecting and gathering data from various sources.
- Structured data is highly organized and easily searchable, whereas unstructured data lacks a predefined format.
- A Dataset is a collection of data used to train and test machine learning models, for example, a dataset of images used to train a computer vision model.
- Acquiring data from reliable sources is crucial in an AI project cycle to ensure that the model is trained on accurate and trustworthy data.
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Description
Get comprehensive notes on Introduction to Artificial Intelligence for Class 9, based on the CBSE Skill Education curriculum. Learn about the basics of Artificial Intelligence as per the NCERT Textbook code 417.