Every idea starts with the shortest useful explanation.
Each diagram shows what the concept actually does.
Practical examples and familiar analogies make the ideas easier to remember.
How the ideas fit together
One family. Different roles.
AI is the broad field. It includes learned systems and explicit rules, logic, planning and search. Machine learning learns from data; neural networks are one family of ML models; deep learning uses neural networks with many layers.
Generative AI describes a capability. It creates content and is not another nesting level. Many prominent generators use deep learning, but generative modelling also includes other approaches.
Modern LLMs are deep neural networks. Generative LLMs produce text token by token. An agent combines a model with instructions, tools, state and a control loop; it is not simply a larger LLM.
The one idea to keep
AI is powerful.
It is not magic.
It learns patterns, works within limits and needs clear goals, good information and thoughtful checks. Understanding those pieces is how you use it well.
Review the path ↑