Imagine you use a music app that suggests songs you might like. Which of the following best explains how the app decides what to recommend?
Think about how apps learn from your behavior and others' to make suggestions.
Recommendation systems analyze your past choices and compare them with patterns from many users to suggest songs you might like. This is called collaborative filtering.
Consider a voice assistant that processes your request in steps: 1) Listen to your voice, 2) Convert speech to text, 3) Understand the request, 4) Find the answer, 5) Speak the answer back.
Which step comes immediately after converting speech to text?
Think about what the assistant needs to do to know what you asked.
After converting speech to text, the assistant must understand the request before finding an answer.
Which of the following statements best describes a key difference between AI assistants and traditional software?
Consider how AI assistants handle new situations compared to fixed programs.
AI assistants use learning algorithms to improve from experience, while traditional software executes fixed code without adapting.
A streaming service suggests movies based on your watch history and ratings. Which AI feature is primarily used here?
Think about how the system uses your and others' preferences to suggest movies.
Collaborative filtering analyzes user preferences to recommend items similar users liked.
Consider a simplified AI assistant that decides what to do based on your command:
command = "play music"
if "play" in command:
action = "start music player"
elif "call" in command:
action = "dial contact"
else:
action = "ask for clarification"
print(action)What will be printed if the command is "play music"?
Check which condition matches the command string first.
The command contains "play", so the first condition is true and the assistant will print "start music player".