Foundations

Artificial intelligence is the field of computer science that builds systems capable of tasks normally thought to require human intelligence, such as understanding language, recognizing images, or making decisions.

Deep learning is machine learning using neural networks with many layers ("deep" = many layers). It powers nearly every recent breakthrough in AI, including LLMs and image generators.

A foundation model is a single large model pretrained on broad data that can be adapted to many downstream tasks. LLMs are the most common type.

Generative AI refers to models that produce new content — text, images, audio, video, or code — rather than classifying or predicting from a fixed set of labels.

A large language model is a neural network trained on huge amounts of text to predict the next token in a sequence. GPT-4, Claude, and Gemini are all LLMs.

Machine learning is the branch of AI in which models learn patterns from data instead of being explicitly programmed. The training process adjusts model parameters to reduce error on examples.

A neural network is a stack of simple mathematical units ("neurons") that learn to transform inputs into outputs by adjusting numeric weights during training.