WGU D685-PRACTICAL APPLICATIONS OF PROMPT
ACTUAL EXAM QUESTIONS AND CORRECT
DETAILED ANSWERS LATEST UPDATES 2026
(VERIFIED ANSWERS) ALREADY GRADED A+
The limitations of AI can be categorized into three main areas:Answers
- fundamental limitations of AI
- practical limitations and challenges
- societal concerns and implications.
Fundamental limitations of AI include:Answers
- dependence on training data
- limited common sense
- lack of emotional sense.
Practical limitations of AI include:Answers
- perpetuating bias
- lack of ethics
- understanding nuances of language and humans.
,Societal concerns on AI include:Answers
- data privacy
- safety
- security concerns
artificial intelligence (AI)-Answers
the study of creating machines and computer systems capable of performing tasks that
typically require human intelligence
narrow AI-Answers
artificial intelligence that is designed and trained for a specific task or narrow set of tasks
general AI-Answers
a hypothetical future AI system that would possess human-level intelligence
algorithms-Answers
defined methods or processes employed to train models, generate predictions, and execute
tasks using data
machine learning-Answers
,a branch of AI that enables computers to improve their performance through experience
without needing explicit programming
AI model-Answers
a computer program designed to make predictions or decisions based on input data
supervised learning-Answers
a technique where a model is trained using data that includes labeled examples, such as
images with tagged objects or text with marked entities
unsupervised learning-Answers
a type of machine learning where the model is trained on unlabeled data without explicit
guidance or supervision
reinforcement learning-Answers
a type of machine learning wherein an AI agent learns through interactions with an
environment, garnering rewards or penalties contingent upon its actions
neural networks-Answers
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
, deep learning-Answers
a powerful subset of machine learning that uses artificial neural networks to learn from large
amounts of data
generative AI-Answers
AI systems that can create new content
large language models (LLMs)-Answers
a type of machine learning model that is trained on massive amounts of text data to
understand and generate human-like language
natural language processing (NLP)-Answers
the field of AI concentrated on enabling computers to understand and engage with human
language, mirroring the intricacies of human communication
chatbots-Answers
AI programs designed to engage in natural conversations with people, providing information,
answering questions, and even offering emotional support
computer vision-Answers
ACTUAL EXAM QUESTIONS AND CORRECT
DETAILED ANSWERS LATEST UPDATES 2026
(VERIFIED ANSWERS) ALREADY GRADED A+
The limitations of AI can be categorized into three main areas:Answers
- fundamental limitations of AI
- practical limitations and challenges
- societal concerns and implications.
Fundamental limitations of AI include:Answers
- dependence on training data
- limited common sense
- lack of emotional sense.
Practical limitations of AI include:Answers
- perpetuating bias
- lack of ethics
- understanding nuances of language and humans.
,Societal concerns on AI include:Answers
- data privacy
- safety
- security concerns
artificial intelligence (AI)-Answers
the study of creating machines and computer systems capable of performing tasks that
typically require human intelligence
narrow AI-Answers
artificial intelligence that is designed and trained for a specific task or narrow set of tasks
general AI-Answers
a hypothetical future AI system that would possess human-level intelligence
algorithms-Answers
defined methods or processes employed to train models, generate predictions, and execute
tasks using data
machine learning-Answers
,a branch of AI that enables computers to improve their performance through experience
without needing explicit programming
AI model-Answers
a computer program designed to make predictions or decisions based on input data
supervised learning-Answers
a technique where a model is trained using data that includes labeled examples, such as
images with tagged objects or text with marked entities
unsupervised learning-Answers
a type of machine learning where the model is trained on unlabeled data without explicit
guidance or supervision
reinforcement learning-Answers
a type of machine learning wherein an AI agent learns through interactions with an
environment, garnering rewards or penalties contingent upon its actions
neural networks-Answers
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
, deep learning-Answers
a powerful subset of machine learning that uses artificial neural networks to learn from large
amounts of data
generative AI-Answers
AI systems that can create new content
large language models (LLMs)-Answers
a type of machine learning model that is trained on massive amounts of text data to
understand and generate human-like language
natural language processing (NLP)-Answers
the field of AI concentrated on enabling computers to understand and engage with human
language, mirroring the intricacies of human communication
chatbots-Answers
AI programs designed to engage in natural conversations with people, providing information,
answering questions, and even offering emotional support
computer vision-Answers
