A practical path through artificial intelligence
Seven guides take you from the meaning of AI to responsible everyday use without requiring a technical background.
- 1
What Is Artificial Intelligence?
A plain-English introduction to artificial intelligence, what it can do, how it differs from ordinary software, and why human judgment still matters.
- 2
Machine Learning Basics
Learn how machine learning uses examples to find patterns, make predictions, and improve performance without relying only on hand-written rules.
- 3
Language Models and Transformers
A clear introduction to language models, transformer architecture, attention, pretraining, and why next-token prediction can produce useful conversation.
- 4
Generative AI Basics
Learn what generative AI creates, how it differs from predictive AI, and why generated output should be treated as a draft rather than verified evidence.
- 5
Using Generative AI Effectively
A practical method for using generative AI as a drafting, learning, and analysis assistant while keeping evidence and human judgment in control.
- 6
AI Hallucinations and Verification
Learn why AI systems can invent facts, quotations, citations, or reasoning, and use a practical verification method before relying on generated content.
- 7
Responsible AI and Ethics
A practical framework for purpose, proportionality, human oversight, safety, fairness, accountability, and stopping an AI system that causes harm.