AI 3.6A and 3.6B

What is the difference between AI and ML?

• AI is a subfield of ML
• ML is a subfield of AI
• AI and ML are the same thing.
• None of these

What are the 4 main types of AI?

• Narrow, domain-specific, strong and super.
• Machine learning, deep learning, pattern recognition and natural language processing
• Robotics, automation, voice recognition and computer vision.
• None of these

Which of the following is NOT an area of AI?

• Computer vision/image recognition
• Voice recognition
• Web design
• Robotics

Which of these does NOT use machine learning/AI?

• Driverless cars
• SIRI/Alexa
• Sonos wireless speakers
• Facial recognition on your phone

What is the process that allows computers to learn and make decisions like humans?

• Machine learning
• Deep learning
• Natural language processing
• Domain-specific AI

What are two characteristics of artificial intelligence?

• It is an agile, responsive network technology that scales easily and adapts to meet business requirements
• It uses systems that mimic human cognitive functions such as learning and problem solving.
• It uses intelligent agents that interact with the environment and make decisions to reach specific goals
• It translates intent into policies and then uses automation to deploy appropriate network configurations

Which of these is a type of AI? Choose any that are correct.

• Narrow
• Domain-specific
• Super
• Supervised

Which one of these is not a type of machine learning?

• Supervised learning
• Unsupervised learning
• Reinforcement learning
• Super learning

What is deep learning?

• A type of machine learning that uses neural networks with many layers to learn from data
• A type of machine learning that uses decision trees to learn from data
• A type of machine learning that uses clustering algorithms to learn from data
• None of these

What is reinforcement learning?

• A type of machine learning that involves training a model on labeled data
• A type of machine learning that involves training a model on unlabeled data
• A type of machine learning that involves training a model to make decisions based on rewards or punishments
• None of these