Quiz on Artificial Intelligence

What is artificial intelligence (AI) primarily used for?

• Enhancing video game graphics

• Forecasting travel prices and predicting the next word in a sentence

• Cooking recipes

• Building physical structures

What is the role of data in AI systems?

• Data is used to create physical models

• Data is the raw material for AI systems to analyze and make predictions

• Data is irrelevant to AI systems

• Data is only used for storing information

What is an algorithm in the context of AI?

• A random set of numbers

• A set of step-by-step instructions that guide an AI model to perform tasks

• A type of hardware component

• A visual representation of data

What is machine learning?

• A process by which machines learn from data and improve their performance over time

• A method of creating physical machines

• A type of computer hardware

• A way to store large amounts of data

What does an AI model represent?

• The physical structure of a computer

• The patterns and relationships discovered by a machine learning algorithm during training

• A random collection of data

• The user interface of an application

What is the main goal of feature extraction in AI models?

• To increase the number of features processed

• To select the least relevant attributes

• To improve performance by reducing features

• To add more data to the model

What does feature engineering involve?

• Removing all features from the data

• Selecting and modifying features

• Ignoring patterns in the data

• Decreasing the AI model's performance

What is the difference between prediction and classification?

• Prediction assigns labels, classification guesses outcomes

• Prediction guesses outcomes, classification assigns labels

• Both involve guessing future outcomes

• Both involve assigning labels

What are neural networks particularly effective for?

• Text editing

• Image and speech recognition

• Data deletion

• Simple calculations

Why is training and testing important for AI models?

• To ensure the model can generalize new data

• To make the model overfit the data

• To avoid using any data subsets

• To ensure the model only works on old data