Understanding Artificial Intelligence

This set of flashcards covers key concepts, definitions, and important details related to Artificial Intelligence as outlined in the lecture notes.

What is Artificial Intelligence (AI)?

AI refers to systems that perform tasks that normally require human intelligence, such as recognizing patterns, making predictions, understanding language, and making decisions based on data.

What are the four core types of AI?

1. Rule-Based AI 2. Machine Learning 3. Deep Learning 4. Generative AI

What is Rule-Based AI?

The oldest type of AI that follows predefined rules to make decisions, examples include IF statements without learning from past data.

What is Machine Learning (ML)?

A type of AI that learns patterns from data to make predictions, for example, predicting future house prices based on past data.

What does Deep Learning (DL) involve?

A subset of machine learning that uses neural networks to handle complex patterns, such as in face or speech recognition.

What is Generative AI?

AI that creates new content by learning language patterns, examples include generating text, images, and summaries.

What is the primary fuel for AI?

Data is critical for AI functionality, which can include numbers, text, images, and audio.

Define a model in the context of AI.

A model is a mathematical structure trained on data, mapping input to output.

What is the difference between training and inference in AI?

Training involves teaching the model using data, while inference is the process of using the trained model to make predictions.

What is Supervised Learning?

A type of machine learning where data has labels used for prediction and classification.

What is Unsupervised Learning?

A type of machine learning where there are no labels, and AI finds structure in the data.

What does Reinforcement Learning entail?

A type of AI learning where the system learns through trial and error and receives rewards based on actions.

Give an example of a spam filter in AI.

Input: email text; Model: classifier; Output: spam or not spam.

What is the Core Stack for AI tools?

The main tools include Python (programming language), ChatGPT (tutor/debugger), VS Code (coding environment), and APIs (to connect AI to real applications).

What is the Learning Loop?

A process where one learns a concept, explains it, applies it to a real example, and automates something small daily.

What is the importance of data quality in AI?

Better data leads to better AI, as poor data can result in bad predictions.

Why is mastering AI not just about reading?

Mastering AI requires building small, imperfect systems repeatedly to gain practical experience.