WGU D184 ARTIFICIAL INTELLIGENCE (AI) FOUNDATIONS
EXAM COMPLETE QUESTIONS AND 100% VERIFIED
ANSWERS (LATEST VERSION)
1. What is Artificial Intelligence? AI is the simulation of human intelligence
processes by machines, especially computer systems, including learning,
reasoning, and self-correction.
2. Who is considered the father of Artificial Intelligence? John McCarthy is
credited as the father of AI. He coined the term "Artificial Intelligence" in 1956.
3. What was the Dartmouth Conference? The 1956 Dartmouth Conference
was a workshop where the term "Artificial Intelligence" was coined and the
field was formally established.
4. What is the Turing Test? A test proposed by Alan Turing to determine if a
machine can exhibit intelligent behavior indistinguishable from a human.
5. What are the four main approaches to AI? Acting humanly, thinking
humanly, thinking rationally, and acting rationally.
6. What is Narrow AI (Weak AI)? AI designed to perform a specific task,
such as facial recognition or internet searches.
7. What is General AI (Strong AI)? AI with the ability to understand, learn,
and apply knowledge across a wide range of tasks at a human level.
8. What is Superintelligence? A hypothetical AI that surpasses human
intelligence in virtually all domains.
9. What are the main branches of AI? Machine Learning, Natural Language
Processing, Computer Vision, Robotics, and Expert Systems.
10. What is an intelligent agent? An entity that perceives its environment
through sensors and acts upon it through actuators to achieve specific goals.
11. What is the Chinese Room Argument? A thought experiment by John
Searle arguing that a computer executing a program cannot have understanding
or consciousness.
,12. What are the ethical concerns in AI? Bias, privacy, job displacement,
accountability, transparency, and safety.
13. What is the AI winter? Periods in AI history when funding and interest in
AI research significantly declined due to unmet expectations.
14. What is symbolic AI? An approach to AI based on high-level symbolic
representations of problems and logic.
15. What is the Physical Symbol System Hypothesis? The theory that a
physical symbol system has the necessary and sufficient means for general
intelligent action.
16. What is computational intelligence? An approach to AI involving learning
and adaptation, including neural networks, fuzzy systems, and evolutionary
computation.
17. What is embodied intelligence? The theory that intelligence emerges from
the interaction between an agent's body and its environment.
18. What is the frame problem? The challenge of representing the effects of
actions in logic without having to represent explicitly all non-effects.
19. What is common sense reasoning? The ability to make inferences about
everyday situations using implicit knowledge that humans naturally possess.
20. What is the knowledge representation problem? The challenge of
encoding information about the world in a form that AI systems can utilize to
solve complex tasks.
21. What is reactive AI? AI systems that respond to current inputs without
memory or ability to learn from past experiences.
22. What is limited memory AI? AI that can use past experiences to inform
future decisions, but only temporarily.
23. What is theory of mind AI? A hypothetical type of AI that can understand
emotions, beliefs, and thought processes of other entities.
24. What is self-aware AI? A theoretical form of AI that has consciousness
and self-awareness.
25. What is the Moravec's Paradox? The observation that high-level
reasoning requires little computation while low-level sensorimotor skills require
enormous computational resources.
, 26. What is the combinatorial explosion problem? The rapid growth in
complexity as the number of variables in a problem increases, making
exhaustive search impractical.
27. What is heuristic search? A problem-solving technique that uses practical
methods to find satisfactory solutions when optimal solutions are impractical.
28. What is the difference between AI and machine learning? AI is the
broader concept of machines performing tasks intelligently; machine learning is
a subset focused on machines learning from data.
29. What is cognitive computing? Systems that simulate human thought
processes to solve complex problems.
30. What is the singularity in AI? A hypothetical point when AI surpasses
human intelligence, leading to unforeseeable changes in civilization.
Section 2: Machine Learning Fundamentals (Questions 31-80)
31. What is Machine Learning? A subset of AI that enables systems to learn
and improve from experience without being explicitly programmed.
32. What are the three main types of machine learning? Supervised learning,
unsupervised learning, and reinforcement learning.
33. What is supervised learning? Learning from labeled training data where
the correct output is provided for each input.
34. What is unsupervised learning? Learning from unlabeled data to find
hidden patterns or structures without predefined outputs.
35. What is reinforcement learning? Learning through trial and error using
feedback from actions and experiences in an environment.
36. What is a training dataset? A collection of data used to train a machine
learning model.
37. What is a test dataset? Data used to evaluate the performance of a trained
model on unseen examples.
38. What is a validation dataset? Data used during training to tune model
parameters and prevent overfitting.
39. What is overfitting? When a model learns the training data too well,
including noise, resulting in poor performance on new data.
40. What is underfitting? When a model is too simple to capture the
underlying patterns in the data.
EXAM COMPLETE QUESTIONS AND 100% VERIFIED
ANSWERS (LATEST VERSION)
1. What is Artificial Intelligence? AI is the simulation of human intelligence
processes by machines, especially computer systems, including learning,
reasoning, and self-correction.
2. Who is considered the father of Artificial Intelligence? John McCarthy is
credited as the father of AI. He coined the term "Artificial Intelligence" in 1956.
3. What was the Dartmouth Conference? The 1956 Dartmouth Conference
was a workshop where the term "Artificial Intelligence" was coined and the
field was formally established.
4. What is the Turing Test? A test proposed by Alan Turing to determine if a
machine can exhibit intelligent behavior indistinguishable from a human.
5. What are the four main approaches to AI? Acting humanly, thinking
humanly, thinking rationally, and acting rationally.
6. What is Narrow AI (Weak AI)? AI designed to perform a specific task,
such as facial recognition or internet searches.
7. What is General AI (Strong AI)? AI with the ability to understand, learn,
and apply knowledge across a wide range of tasks at a human level.
8. What is Superintelligence? A hypothetical AI that surpasses human
intelligence in virtually all domains.
9. What are the main branches of AI? Machine Learning, Natural Language
Processing, Computer Vision, Robotics, and Expert Systems.
10. What is an intelligent agent? An entity that perceives its environment
through sensors and acts upon it through actuators to achieve specific goals.
11. What is the Chinese Room Argument? A thought experiment by John
Searle arguing that a computer executing a program cannot have understanding
or consciousness.
,12. What are the ethical concerns in AI? Bias, privacy, job displacement,
accountability, transparency, and safety.
13. What is the AI winter? Periods in AI history when funding and interest in
AI research significantly declined due to unmet expectations.
14. What is symbolic AI? An approach to AI based on high-level symbolic
representations of problems and logic.
15. What is the Physical Symbol System Hypothesis? The theory that a
physical symbol system has the necessary and sufficient means for general
intelligent action.
16. What is computational intelligence? An approach to AI involving learning
and adaptation, including neural networks, fuzzy systems, and evolutionary
computation.
17. What is embodied intelligence? The theory that intelligence emerges from
the interaction between an agent's body and its environment.
18. What is the frame problem? The challenge of representing the effects of
actions in logic without having to represent explicitly all non-effects.
19. What is common sense reasoning? The ability to make inferences about
everyday situations using implicit knowledge that humans naturally possess.
20. What is the knowledge representation problem? The challenge of
encoding information about the world in a form that AI systems can utilize to
solve complex tasks.
21. What is reactive AI? AI systems that respond to current inputs without
memory or ability to learn from past experiences.
22. What is limited memory AI? AI that can use past experiences to inform
future decisions, but only temporarily.
23. What is theory of mind AI? A hypothetical type of AI that can understand
emotions, beliefs, and thought processes of other entities.
24. What is self-aware AI? A theoretical form of AI that has consciousness
and self-awareness.
25. What is the Moravec's Paradox? The observation that high-level
reasoning requires little computation while low-level sensorimotor skills require
enormous computational resources.
, 26. What is the combinatorial explosion problem? The rapid growth in
complexity as the number of variables in a problem increases, making
exhaustive search impractical.
27. What is heuristic search? A problem-solving technique that uses practical
methods to find satisfactory solutions when optimal solutions are impractical.
28. What is the difference between AI and machine learning? AI is the
broader concept of machines performing tasks intelligently; machine learning is
a subset focused on machines learning from data.
29. What is cognitive computing? Systems that simulate human thought
processes to solve complex problems.
30. What is the singularity in AI? A hypothetical point when AI surpasses
human intelligence, leading to unforeseeable changes in civilization.
Section 2: Machine Learning Fundamentals (Questions 31-80)
31. What is Machine Learning? A subset of AI that enables systems to learn
and improve from experience without being explicitly programmed.
32. What are the three main types of machine learning? Supervised learning,
unsupervised learning, and reinforcement learning.
33. What is supervised learning? Learning from labeled training data where
the correct output is provided for each input.
34. What is unsupervised learning? Learning from unlabeled data to find
hidden patterns or structures without predefined outputs.
35. What is reinforcement learning? Learning through trial and error using
feedback from actions and experiences in an environment.
36. What is a training dataset? A collection of data used to train a machine
learning model.
37. What is a test dataset? Data used to evaluate the performance of a trained
model on unseen examples.
38. What is a validation dataset? Data used during training to tune model
parameters and prevent overfitting.
39. What is overfitting? When a model learns the training data too well,
including noise, resulting in poor performance on new data.
40. What is underfitting? When a model is too simple to capture the
underlying patterns in the data.
