BTM GUILLIAMS EXAM 2 FALL, UPDATED ACTUAL
QUESTIONS AND CORRECT ANSWERS
Question:
1. AI
Answer:
Software that enables an IS to mimic or simulate human intelligence
Question:
2. Knowledge Base
Answer:
a body of knowledge in a particular area that makes it easier to master new information in that area.
Question:
3. Inference Engine
Answer:
Part of the expert system that seeks information and relationships from the knowledge base and provides
answers, predictions, and suggestions similar to the way a human expert would.
Question:
4. User Interface
Answer:
The visual elements of an program through which a user controls or communications the application. Often
abbreviated UI.
Question:
5. Neural Networks (AI)
Answer:
A neural network (NN) is a technique of AI inspired by the networks of neurons in our brains and central
nervous systems.
Question:
6. Deep Learning
Answer:
A type of machine learning that uses multiple layers of interconnections among data to identify patterns
and improve predicted results. Deep learning most often uses a set of techniques known as neural networks
and is popularly applied in tasks like speech recognition, image recognition, and computer vision; when AI
adjusts weights at different layers.
Question:
7. Natural Language Processing
, Answer:
An aspect of artificial intelligence that involves technology that allows computers to understand, analyze,
manipulate, and/or generate "natural" languages, such as English; Natural language processing studies how
AI systems acquire, store, and apply natural language data, and how computers make sense out of human
language.
Question:
8. Broad AI (General AI)
Answer:
Flexible and general intelligence that is applied across a broad set of tasks such as counseling, planning, or
goal setting. ex) Siri, ChatGPT, Alexa, etc...
Question:
9. Ambient AI
Answer:
An inconspicuous, omnipresent system that automatically responds to our inputs via voice, gesture, or
other natural means; Recognizes its environment and reacts to it. (Smart thermostats, etc...)
Question:
10. Singularity
Answer:
When computers no longer need humans. Computers can learn and operate on their own.
Question:
11. Supervised Learning
Answer:
When you have an objective, and desired outcome, and sort outputs for what is desired. Humans teach the
computer.
Question:
12. Unsupervised Learning
Answer:
We do not know the structure of our data beforehand; When computer is learning on its own. No prior
hypothesis. No objective to measure right or wrong.
Question:
13. Turing Test
Answer:
An AI passes the Turing Test if it can fool half of all individuals into thinking they're talking with a real
person. (Nowadays, AI can fail this because the output is too good)
Question:
14. Phishing
Answer:
Technique for obtaining unauthorized data that uses pretexting via email. The phisher pretends to be a
legitimate company and sends an email requesting confidential data (SSN, account numbers, passwords)
QUESTIONS AND CORRECT ANSWERS
Question:
1. AI
Answer:
Software that enables an IS to mimic or simulate human intelligence
Question:
2. Knowledge Base
Answer:
a body of knowledge in a particular area that makes it easier to master new information in that area.
Question:
3. Inference Engine
Answer:
Part of the expert system that seeks information and relationships from the knowledge base and provides
answers, predictions, and suggestions similar to the way a human expert would.
Question:
4. User Interface
Answer:
The visual elements of an program through which a user controls or communications the application. Often
abbreviated UI.
Question:
5. Neural Networks (AI)
Answer:
A neural network (NN) is a technique of AI inspired by the networks of neurons in our brains and central
nervous systems.
Question:
6. Deep Learning
Answer:
A type of machine learning that uses multiple layers of interconnections among data to identify patterns
and improve predicted results. Deep learning most often uses a set of techniques known as neural networks
and is popularly applied in tasks like speech recognition, image recognition, and computer vision; when AI
adjusts weights at different layers.
Question:
7. Natural Language Processing
, Answer:
An aspect of artificial intelligence that involves technology that allows computers to understand, analyze,
manipulate, and/or generate "natural" languages, such as English; Natural language processing studies how
AI systems acquire, store, and apply natural language data, and how computers make sense out of human
language.
Question:
8. Broad AI (General AI)
Answer:
Flexible and general intelligence that is applied across a broad set of tasks such as counseling, planning, or
goal setting. ex) Siri, ChatGPT, Alexa, etc...
Question:
9. Ambient AI
Answer:
An inconspicuous, omnipresent system that automatically responds to our inputs via voice, gesture, or
other natural means; Recognizes its environment and reacts to it. (Smart thermostats, etc...)
Question:
10. Singularity
Answer:
When computers no longer need humans. Computers can learn and operate on their own.
Question:
11. Supervised Learning
Answer:
When you have an objective, and desired outcome, and sort outputs for what is desired. Humans teach the
computer.
Question:
12. Unsupervised Learning
Answer:
We do not know the structure of our data beforehand; When computer is learning on its own. No prior
hypothesis. No objective to measure right or wrong.
Question:
13. Turing Test
Answer:
An AI passes the Turing Test if it can fool half of all individuals into thinking they're talking with a real
person. (Nowadays, AI can fail this because the output is too good)
Question:
14. Phishing
Answer:
Technique for obtaining unauthorized data that uses pretexting via email. The phisher pretends to be a
legitimate company and sends an email requesting confidential data (SSN, account numbers, passwords)
