Test 8 - AI & Machine Learning

What is Artificial Intelligence (AI)?

• 1. The ability of machines to perform tasks without human intervention.

• 1. A computer program that simulates human intelligence.

• 1. The study of algorithms that can improve automatically through experience.

• 1. The ability of machines to understand and respond to natural language.

What is Machine Learning (ML)?

• 1. A subset of AI that focuses on training machines to learn from data.

• 1. The ability of machines to understand and respond to natural language.

• 1. The study of algorithms that can improve automatically through experience.

• 1. A computer program that simulates human intelligence.

What is the main objective of AI and ML?

• 1. To replace human intelligence with machine intelligence.

• 1. To automate all tasks and eliminate human involvement.

• 1. To enhance human capabilities and improve decision-making.

• 1. To create machines that can think and feel like humans.

How does ML learn from data?

• 1. By using pre-programmed rules and instructions.

• 1. By observing and imitating human behavior.

• 1. By analyzing patterns and making predictions.

• 1. By processing large amounts of structured and unstructured data.

Which of the following is an example of AI in action?

• 1. Self-driving cars

• 1. Email spam filters

• 1. Virtual personal assistants (e.g., Siri, Alexa)

• All of the above

Which of these are not the key features of robo-advisors ?

• Automated Portfolio Construction

• Portfolio Rebalancing

• User Friendly Interface

• None of these

What is the concept of reinforcement learning in AI?

• 1. Training machines to understand and respond to natural language.

• 1. Using algorithms to automatically improve through experience and feedback.

• 1. Teaching machines to make decisions and take actions based on rewards and penalties.

• 1. Simulating human-like intelligence in machines.

What are the potential ethical concerns associated with AI and ML?

• 1. Bias and discrimination in decision-making algorithms.

• 1. Invasion of privacy and data security risks.

• 1. Job displacement and unemployment.

• 1. All of the above