Intro To AI Unit 1 Quiz

What does human intelligence involve?

Reasoning, creativity, problem-solving, adaptation, abstract thought, and innovation.

What are machines good at?

Speed, automation, recognizing patterns in large datasets.

Key overlap and difference between humans and machines?

Both process information; humans bring meaning and context, machines focus on efficiency and scale.

What is AI?

Using computers to simulate aspects of human intelligence (reasoning, learning, problem-solving).

What is symbolic AI?

An approach that uses explicitly coded rules, logic, and symbols to represent knowledge. Problems are solved through step-by-step reasoning rather than learning from data.

What is machine learning?

Finds patterns in data.

What is generative AI?

A branch of AI that uses machine learning models (especially neural networks) to create new content such as text, images, music, or video, based on patterns learned from large datasets.

Name 3 everyday uses of AI.

Virtual assistants (Siri, Alexa), autocorrect/predictive text, email spam filters.

Examples of AI in media/entertainment?

Social media feeds, Netflix/Spotify recommendations, video game NPCs, chatbots like ChatGPT.

1950s AI milestone?

Alan Turing and the Turing Test.

1960s–70s AI milestone?

Early rule-based systems.

1970s AI milestone?

Growth of symbolic AI.

1980s AI milestone?

Expert systems boom.

2010s AI milestone?

Deep learning breakthroughs in image recognition.

2015 AI milestone?

Advances in speech recognition.

2020s AI milestone?

Generative AI tools (ChatGPT, DALL-E, MidJourney).

2023 AI milestone?

AI integrated into everyday life.

What is the main function of machine learning?

Identify patterns and make predictions from data.

How do ML algorithms improve?

They evolve and adapt as they process more information.

Example of ML?

Spam filter that learns from flagged emails and corrections.

What does Natural Language Processing (NLP) do?

Interprets, analyzes, and responds to human language.

Applications of NLP?

Translation apps, sentiment analysis, ChatGPT.

Impact of NLP?

Bridges the gap between human communication and machine understanding.

What are neural networks inspired by?

The human brain.

How do neural networks work?

Nodes process inputs, pass them forward, adjust through training.

Applications of neural networks?

Deep learning models for image recognition, speech processing, generative AI.