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NEW QUESTION # 62
Which of the following is a step for the Value Engineering Framework?
Answer: C
NEW QUESTION # 63
Artificial narrow intelligence ANI is also commonly expressed as ____.
Answer: D
Explanation:
The correct answer is A. Weak AI . Artificial Narrow Intelligence, or ANI, is commonly called Weak AI because it is designed to perform a specific task or a limited set of tasks within a defined domain. Examples include recommendation engines, search engines, spam filters, facial recognition systems, voice assistants, fraud detection tools, and chatbots. These systems can perform their assigned functions effectively, but they do not possess general intelligence, consciousness, self-awareness, or human-like understanding across all domains.
Strong AI and General AI refer to Artificial General Intelligence, which would be capable of broad reasoning, learning, and problem-solving across many tasks like a human. SuperAI refers to a theoretical level of intelligence beyond human capability. ExpertAI is not the standard expression for ANI. Since ANI is task- specific and limited in scope, it is correctly expressed as Weak AI .
NEW QUESTION # 64
Which of the following statement is CORRECT for RNN?
Answer: C
Explanation:
The correct answer is E. a, b and c only because all three statements correctly describe Recurrent Neural Networks and their limitation. RNNs are neural network models designed for sequential data such as text, speech, time-series data, and ordered events. They process information step by step and use previous hidden states to influence later outputs.
Statement A is correct because a major drawback of traditional RNNs is their difficulty in remembering information over many time steps. This happens mainly because of vanishing gradient problems during training. Statement B is also correct because standard RNNs generally struggle with long-term dependencies, meaning they may fail to retain important information from earlier parts of a sequence. Statement C is correct because Long Short-Term Memory networks are a specialized extension of RNNs designed to handle long- term memory more effectively using gates that control what information is stored, forgotten, and passed forward.
Therefore, the best answer is E. a, b and c only .
NEW QUESTION # 65
XAI stands for ______.
Answer: C
Explanation:
XAI stands for Explainable Artificial Intelligence. It refers to AI systems, models, and methods that help humans understand how an AI model reaches a decision, prediction, or recommendation. In business and responsible AI contexts, explainability is important because leaders, users, regulators, and stakeholders need to know why an AI system produced a specific result, especially in high-impact areas such as finance, healthcare, hiring, insurance, and public services.
Explainable AI supports transparency, accountability, trust, auditability, and risk management. It helps identify whether a model is relying on appropriate factors or producing biased, unfair, or unreliable outcomes.
"Extensible Artificial Intelligence" and "Exceptional Artificial Intelligence" are not standard meanings of XAI in artificial intelligence documentation. Since the accepted and correct expansion of XAI is Explainable Artificial Intelligence, the correct answer is B .
NEW QUESTION # 66
Choose the CORRECT example of Supervised Learning.
Answer: E
Explanation:
The correct answer is B. House price prediction . Supervised learning is a machine learning approach where a model is trained using labeled data. In a house price prediction problem, the training data usually contains property features such as size, location, number of rooms, age of the house, and past selling prices. The known selling price acts as the label or target value. The model learns the relationship between the input features and the price, then predicts prices for new houses.
A driverless car is not the best single example because autonomous driving uses a combination of AI techniques, including supervised learning, reinforcement learning, computer vision, sensor fusion, planning, and control systems. ChatGPT is a generative AI language model and is not typically used as the basic example of supervised learning in this context. Since house price prediction directly represents supervised learning with labeled input-output data, the correct answer is B .
NEW QUESTION # 67
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