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WGU D685 - PRACTICAL APPLICATIONS
OF PROMPT OA AND PA | FREQUENTLY
TESTED QUESTIONS WITH CORRECT
ANSWERS | BRAND NEW!(UPDATED
2026-2027)- GUARANTEED A+ PASS
STARTS HERE
The limitations of AI can be categorized into three main
areas:
- ANSWER- fundamental limitations of AI
- practical limitations and challenges
- societal concerns and implications.
Fundamental limitations of AI include:-
- ANSWER- dependence on training data
- limited common sense
- lack of emotional sense.
Practical limitations of AI include:
- ANSWER-
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- perpetuating bias
- lack of ethics
- understanding nuances of language and humans.
Societal concerns on AI include:
- ANSWER-
- data privacy
- safety
- security concerns
The study of creating machines and computer systems
capable of performing tasks that typically require human
intelligence
- ANSWER-artificial intelligence (AI)
Artificial intelligence that is designed and trained for a
specific task or narrow set of tasks
- ANSWER-narrow AI
A hypothetical future AI system that would possess
human-level intelligence
- ANSWER-general AI
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Defined methods or processes employed to train models,
generate predictions, and execute tasks using data
- ANSWER-algorithms
A branch of AI that enables computers to improve their
performance through experience without needing
explicit programming
- ANSWER-machine learning
A computer program designed to make predictions or
decisions based on input data
- ANSWER-AI model
A technique where a model is trained using data that
includes labeled examples, such as images with tagged
objects or text with marked entities
- ANSWER-supervised learning
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A type of machine learning where the model is trained
on unlabeled data without explicit guidance or
supervision
- ANSWER-unsupervised learning
A type of machine learning wherein an AI agent learns
through interactions with an environment, garnering
rewards or penalties contingent upon its actions
- ANSWER-reinforcement learning
Computational models inspired by the structure and
function of the human brain's neural networks that learn
from data called training to recognize patterns, make
predictions, and perform tasks such as classification,
regression, and pattern recognition
- ANSWER-neural networks
A powerful subset of machine learning that uses artificial
neural networks to learn from large amounts of data
- ANSWER-deep learning
WGU D685 - PRACTICAL APPLICATIONS
OF PROMPT OA AND PA | FREQUENTLY
TESTED QUESTIONS WITH CORRECT
ANSWERS | BRAND NEW!(UPDATED
2026-2027)- GUARANTEED A+ PASS
STARTS HERE
The limitations of AI can be categorized into three main
areas:
- ANSWER- fundamental limitations of AI
- practical limitations and challenges
- societal concerns and implications.
Fundamental limitations of AI include:-
- ANSWER- dependence on training data
- limited common sense
- lack of emotional sense.
Practical limitations of AI include:
- ANSWER-
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- perpetuating bias
- lack of ethics
- understanding nuances of language and humans.
Societal concerns on AI include:
- ANSWER-
- data privacy
- safety
- security concerns
The study of creating machines and computer systems
capable of performing tasks that typically require human
intelligence
- ANSWER-artificial intelligence (AI)
Artificial intelligence that is designed and trained for a
specific task or narrow set of tasks
- ANSWER-narrow AI
A hypothetical future AI system that would possess
human-level intelligence
- ANSWER-general AI
,3|Page
Defined methods or processes employed to train models,
generate predictions, and execute tasks using data
- ANSWER-algorithms
A branch of AI that enables computers to improve their
performance through experience without needing
explicit programming
- ANSWER-machine learning
A computer program designed to make predictions or
decisions based on input data
- ANSWER-AI model
A technique where a model is trained using data that
includes labeled examples, such as images with tagged
objects or text with marked entities
- ANSWER-supervised learning
, 4|Page
A type of machine learning where the model is trained
on unlabeled data without explicit guidance or
supervision
- ANSWER-unsupervised learning
A type of machine learning wherein an AI agent learns
through interactions with an environment, garnering
rewards or penalties contingent upon its actions
- ANSWER-reinforcement learning
Computational models inspired by the structure and
function of the human brain's neural networks that learn
from data called training to recognize patterns, make
predictions, and perform tasks such as classification,
regression, and pattern recognition
- ANSWER-neural networks
A powerful subset of machine learning that uses artificial
neural networks to learn from large amounts of data
- ANSWER-deep learning
