Review Questions Artificial Intelligence

Which of the following best defines Artificial Intelligence?

• A robot made of metal and wires

• A program that makes computers perform tasks that seem intelligent

• Any mobile app that uses the internet

• A video game with advanced graphics

What are the 5 Big Ideas of AI?

• Think, Speak, Move, Work, Earn

• Perceive, Reason/Plan, Learn, Interact, Impact

• Input, Process, Output, Feedback, Memory

• Sense, Logic, Store, Retrieve, Act

How does a self-driving car “perceive” the world around it?

• By using sensors and cameras to detect objects and surroundings

• By asking passengers for directions

• By following a pre-set route without any feedback

• By using only GPS signals

Give one positive and one negative impact of self-driving cars on society.

• Positive: Increased accidents; Negative: More free time for drivers

• Positive: Reduced traffic congestion; Negative: Job loss for drivers

• Positive: Higher fuel consumption; Negative: Improved road safety

• Positive: More pollution; Negative: Faster travel times

What is a dataset?

• A collection of numbers only

• A collection of data that could be text, numbers, images, or videos

• A prediction made by a machine

• A machine learning algorithm

In unsupervised learning, the machine:

• Learns from labeled examples

• Learns from trial and error

• Finds patterns in data without labels

• Waits for human instructions

Which best describes clustering?

• Grouping similar data points together

• Finding rules in data like “if X then Y”

• Learning from teacher-provided answers

• Choosing random categories

Which is NOT a component of reinforcement learning?

• Agent

• Environment

• Action

• Clustering

Give a real-world example of association.

• Market basket analysis to find products frequently bought together

• Measuring the height of students in a class

• Drawing a bar graph of monthly sales

• Counting the number of cars in a parking lot

In reinforcement learning, explain the role of the policy.

• The policy determines the actions an agent takes in each state to maximize rewards

• The policy stores the data collected during training

• The policy measures the accuracy of predictions

• The policy is used to clean and preprocess data