Page 159 - AI Computer 10

Answers

1. F 2. T 3. T 4. F 5. F 6. T
7. F 8. F
D. Very short answer type questions.

1. Which field of computer science focuses on replicating parts of the complexity of the human vision
system?
Ans: Computer Vision.

2. What happens if data used to train AI systems is biased?
Ans: AI systems become biased and produce incorrect results.
3. In Natural Language Processing, what can be the input and output data?
Ans: Voice or written text.
4. What is the purpose of Data Acquisition in AI?
Ans: Data Acquisition is the process of identifying and gathering data requirements for an AI project.
5. What is Data Exploration in the AI Project Cycle?

Ans: Data Exploration is the phase of understanding the nature of data in terms of quality and characteristics.
6. What is the step before deployment in the AI project life cycle?
Ans: Evaluation
7. What happens in the Modelling phase of AI projects?
Ans: In the Modelling phase, collected data is analysed based on the gathered project requirements.
8. Name any two real-life applications of NLP.
Ans: Email spam filters and Google Translate.

E. Short answer type questions.
1. How does Data Exploration contribute to the AI Project Cycle?
Ans: Data Exploration helps understand the nature of data, ensuring its quality and characteristics align with
project goals.
2. Why is Evaluation essential before deploying an AI model?
Ans: Evaluation determines the efficiency of the model, ensuring its accuracy and performance meet the
desired standards before deployment.
3. What is the significance of the Modelling phase in AI projects?
Ans: The Modelling phase involves analysing collected data based on project requirements and training the
model using machine-learning algorithms.
4. What is the main goal of Natural Language Processing (NLP)?
Ans: NLP aims to enable computers to understand and interact with humans using natural language, whether
spoken or written.
5. Explain the domain of AI that involves interpretation of digital images and videos.
Ans: Computer Vision is the domain of AI that focuses on replicating the complexity of human vision, allowing
computers to understand the content of digital images and videos.
6. What is the core of AI systems, and what problem may arise in AI systems that make decisions based on
biased data?
Ans: Data is the core of AI systems. The problem of inclusion may arise when AI systems make decisions based
on biased data, such as inaccuracy in facial recognition for darker-skinned faces.

25
25