AI/ML Foundations

AI vs ML vs Deep Learning vs Generative AI

AI is the broad goal of making machines behave intelligently; ML is the data-driven subset; deep learning is ML with layered neural networks; generative AI produces new content such as text, code, images, audio, or structured data.

AI is the umbrella, not one specific technique
Machine learning replaces explicit rules with learned patterns
Deep learning learns representations, not just predictions
Generative AI models produce artifacts, not just labels
LLMs are generative models trained mainly through token prediction
Use the narrowest accurate term

The vocabulary stack
Term	What it means	Concrete example
AI	Broad goal: intelligent behavior	Planning, search, robotics, ML
ML	Behavior learned from data	Spam classifier, price predictor
Deep learning	ML with layered neural networks	Image classifier, speech recognizer
Generative AI	Models that synthesize new content	LLM answer, generated image
LLM	Generative language model over tokens	Chat, summarization, code assistant

Relationship between the terms

Not every AI system uses ML, and not every ML system is generative.