Artificial Intelligence True or False Questions
True/False Quiz
Time Remaining: 05:00
Question 1
AI systems can be used to automate the process of financial planning and investment decision-making.
Question 2
AI personalizes social media feeds based on user interests and engagement patterns.
Question 3
Reinforcement learning is a type of machine learning where the AI system learns by being rewarded or punished for its actions.
Question 4
AI can be used to personalize product recommendations in e-commerce.
Question 5
AI systems can be biased and reflect the biases present in the data used to train them.
Question 6
All AI systems require physical sensors to interact with their environment.
Question 7
AI-powered robots can assist in archaeological excavations and artifact preservation.
Question 8
Artificial intelligence (AI) is a field of computer science that aims to create intelligent machines that can perform tasks that typically require human intelligence.
Question 9
AI systems can detect and prevent cross-site scripting (XSS) attacks and web application vulnerabilities.
Question 10
AI can analyze medical data to predict patient risk of complications and adverse events.
Question 11
Reinforcement learning is a type of machine learning where an agent learns from its environment.
Question 12
AI systems can never be creative or innovative.
Question 13
AI generates realistic 3D clothing models for virtual fashion shows and e-commerce.
Question 14
AI can be used to improve the efficiency of public transportation systems.
Question 15
AI-powered smart homes can automate and optimize energy consumption.
Question 16
AI systems can generate realistic 3D models of scientific instruments and laboratory equipment for research and development.
Question 17
AI-powered drones are used for search and rescue operations.
Question 18
AI can identify patients at risk of certain diseases by analyzing their medical records.
Question 19
AI-powered virtual fitting rooms allow customers to try on clothes digitally.
Question 20
AI can be used for predictive maintenance of power grids and electrical networks.
Score: 0/20