20+ Important QnA AI Domains CBSE Class 10

Important QnA AI Domains CBSE Class 10 provides questions for the topic Introduction to AI Domains for class 10. So here let’s begin!

Important QnA AI Domains CBSE Class 10

Let’s start this article Important QnA AI Domains CBSE Class 10 with objective type questions and then subjective type questions.

Objective Type Questions (OTQs)

This section of Important QnA AI Domains CBSE Class 10 includes objective-type questions like fill-in-the-blanks, true/false and MCQ. So here we go!

1. Which of the following is not a domain of AI?
   1. Data Science
   2. Computer Vision
   3. Natural Language Processing
   4. Neural Network
2. The information extracted through data science can be used to make a decision about it. (True/False)
3. ________ 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. (Ans. Data Science)
4. Which of the following is an example of data science?
   1. Social media websites
   2. Price Comparison websites
   3. Online Shopping websites
   4. Blog web sites
5. CV stands for _____________. (Ans. Computer Vision)
6. The ________ is the domain of AI that depicts the capability of a machine to get and analyse visual information and afterwards predict some decisions about it. (Ans. Computer Vision/CV)
7. Which of the following translates digital visual data into descriptions and then turned into a computer-readable language to aid the decision-making?
   1. Computer Vision
   2. PixelLab
   3. Pixel It
   4. Pixar
8. Which of the following is an example of a CV?
   1. Self-driving cars
   2. Smart Interactions
   3. Face Locks
   4. All of these
9. NLP stands for ___________________. (Ans. Natural Language Processing)
10. _________ is a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language. (Ans. Natural Language Processing/NLP)
11. Which of the following is an example of NLP?
    1. Online translators
    2. Email filters
    3. Smart Assistants
    4. All of these
12. Which of the following component of NLP establish linkage with natural language inputs and analyse different aspects of language?
    1. NLU
    2. NLG
    3. NLTK
    4. NLC
13. ___________ produces meaningful phrases and sentences in the form of natural language. (Ans. NLG)
14. The full form of NLU is _____________
    1. Natural Language Understanding
    2. Natural Language Utilization
    3. Natural Langauge Unity
    4. Natural Language Union
15. The full form of NLG is ___________
    1. Natural Language Group
    2. Natural Langauge Gap
    3. Natural Language Generation
    4. Natural Language gaming

In the next section of QnA AI Domains CBSE Class 10, we will see subjective-type questions.

Subjective Type Questions (STQs)

1. What do you mean by AI Domains?
   • AI become intelligent according to the training given through data. The machine requires a dataset to train and learn itself. As the machine receives the data it processes it and then makes a decision. These data models are known as different domains of AI.
2. Enlist the three domains of AI.
   • Data Science
   • Computer Vision (CV)
   • Natural Language Processing (NLP)
3. What is data with respect to the AI domain of Data Science?
   • Every AI system heavily relies on data. Data is the core of almost every AI system. AI systems need data for functioning, learning and growing. It is basically input in the system.
4. What do you mean by data science? Illustrate your answer with an example.
   • Data science is one of the domains of AI. It processes the data for the AI systems. It collects the data input, maintains them into accurate datasets, and prepares the output in the proper and appropriate format. The final output or information extracted through data science can be used to make a decision.
   • For example, price comparison websites like PriceGrabber, PriceRunner, Junglee, Shopzilla, and DealTime are totally driven by data, compares the price of a product from different vendors and then the user can make a suitable decision.
   • The digital marketing spectrum is also a good example of data science. It shows the targeted ads to the audience according to their data.
5. What do you mean by Computer Vision?
   • Computer Vision is of the three domains of AI. It gets the visual data and analyses them to make a decision. This process includes acquiring images, screening, analysing, identifying and extracting information. In computer vision, input to the machines are photographs, videos taken from thermal, or infrared sensors, indicators and other sources.
   • In this process, the visual data can be translated into descriptions and turned into computer-readable language to make a decision.
   • The examples of computer visions are as follows:
     • Face recognition systems: Apps such as Google Photos, Snapchat, Facebook, Interpol
     • Content-Based Image Retrieval (CBIR): Search engines such as Google, Bing, CT scans and MRI scans in hospitals, Earth science etc.
     • Smart Interactions: Gaming
6. How does the face lock system work in a smartphone?
   • The face lock system in a smartphone detects and captures the image.
   • It saves the features of the face at the beginning or the first time when the lock is applied.
   • After that whenever the features matched it will unlock the smartphone.
7. What is Natural Language Processing?
   • Natural language processing is capable to communicate between machines and human beings. It uses natural language for both oral and spoken languages.
   • Natural Language Processing tries to capture the information from spoken or written words in the system.
   • It has two main components:
     • Natural Language Understanding: It interprets the words and establish a link with natural input and analyse the different aspects of language.
     • Natural Langauge Generation: It generates meaningful phrases and sentences in Natural Language. It includes the processes of text planning, sentence planning, and text realization.
   • NLU is easier than NLG.
   • Examples are Email filters, smart assistants, translators etc.

Follow the below-given link to read QnA Unit 1 Introduction to AI.

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