QUESTION: 5

What is one of the positive stereotypes people have about Al?

Al is unbiased.
Al is suitable only in manufacturing sectors.
Al can leave humans behind.
Al can help businesses complete tasks around the clock 24/7.

Answer(s): D

Explanation:

24/7 Availability: AI systems can operate continuously without the need for breaks, which enhances productivity and efficiency. This is particularly beneficial for customer service, where AI chatbots can handle inquiries at any time.

Reference:

"AI's ability to function 24/7 offers significant advantages for business operations."
(Gartner, 2021)
Use Cases: Examples include automated customer support, monitoring and maintaining IT infrastructure, and processing transactions in financial services.
"AI enables round-the-clock operations, providing continuous support and monitoring." (Forrester, 2020)
Business Benefits: The continuous operation of AI systems can lead to cost savings, improved customer satisfaction, and faster response times, which are critical competitive advantages.
"Businesses benefit from AI's 24/7 capabilities through increased efficiency and customer satisfaction." (McKinsey & Company, 2019)

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QUESTION: 6

What is artificial intelligence?

The study of computer science
The study and design of intelligent agents
The study of data analysis
The study of human brain functions

Answer(s): B

Explanation:

Artificial intelligence (AI) is a broad field of computer science focused on creating systems capable of performing tasks that would normally require human intelligence. The correct answer is option B, which defines AI as "the study and design of intelligent agents." Here's a comprehensive breakdown:
Definition of AI: AI involves the creation of algorithms and systems that can perceive their environment, reason about it, and take actions to achieve specific goals. Intelligent Agents: An intelligent agent is an entity that perceives its environment and takes actions to maximize its chances of success. This concept is central to AI and encompasses a wide range of systems, from simple rule-based programs to complex neural networks. Applications: AI is applied in various domains, including natural language processing, computer vision, robotics, and more.

Reference:

Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson. Poole, D., Mackworth, A., & Goebel, R. (1998). Computational Intelligence: A Logical Approach.
Oxford University Press.

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QUESTION: 7

What is Artificial Narrow Intelligence (ANI)?

Al systems that can perform any task autonomously
Al systems that can process beyond human capabilities
Al systems that can think and make decisions like humans
Al systems that can perform a specific task autonomously

Answer(s): D

Explanation:

Artificial Narrow Intelligence (ANI) refers to AI systems that are designed to perform a specific task or a narrow set of tasks. The correct answer is option D. Here's a detailed explanation:
Definition of ANI: ANI, also known as weak AI, is specialized in one area. It can perform a particular function very well, such as facial recognition, language translation, or playing a game like chess. Characteristics: Unlike general AI, ANI does not possess general cognitive abilities. It cannot perform tasks outside its specific domain without human intervention or retraining. Examples: Siri, Alexa, and Google's search algorithms are examples of ANI. These systems excel in their designated tasks but cannot transfer their learning to unrelated areas.

Reference:

Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press. Kaplan, A., & Haenlein, M. (2019). Siri, Siri, in my hand: Who's the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15- 25.

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QUESTION: 8

Why is diversity important in Al training data?

To make Al models cheaper to develop
To reduce the storage requirements for data
To ensure the model can generalize across different scenarios
To increase the model's speed of computation

Answer(s): C

Explanation:

Diversity in AI training data is crucial for developing robust and fair AI models. The correct answer is option C. Here's why:
Generalization: A diverse training dataset ensures that the AI model can generalize well across different scenarios and perform accurately in real-world applications. Bias Reduction: Diverse data helps in mitigating biases that can arise from over-representation or under-representation of certain groups or scenarios.
Fairness and Inclusivity: Ensuring diversity in data helps in creating AI systems that are fair and inclusive, which is essential for ethical AI development.

Reference:

Barocas, S., Hardt, M., & Narayanan, A. (2019). Fairness and Machine Learning. fairmlbook.org. Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2021). A Survey on Bias and Fairness in Machine Learning. ACM Computing Surveys (CSUR), 54(6), 1-35.

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Free D-GAI-F-01 Exam Braindumps (page: 2)

QUESTION: 5

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QUESTION: 6

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QUESTION: 7

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QUESTION: 8

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