Language
Large language models read and write text — drafting, translating, summarising and answering questions in seconds.
A plain-English guide
Artificial intelligence, explained clearly
No hype, no jargon. Learn what AI actually is, how machines learn from data, where it is already part of your day, and the questions worth asking about it.
What is AI?
Artificial intelligence is software that learns patterns from examples instead of following rules written by a person. Show a system millions of photos of cats and it works out for itself what "cat" looks like. That shift — from instructing to teaching — is what makes modern AI feel so different.
1950s
First AI research programs
2012
Deep learning breakthrough
2020s
Generative AI goes mainstream
How it works
Almost every AI system follows the same four beats.
- 01
Data
Everything starts with examples — text, images, sound. The broader and cleaner the data, the better the result.
- 02
Training
A neural network adjusts millions of internal weights, slowly reducing its error across the examples it sees.
- 03
Inference
Once trained, the model applies what it learned to brand-new input — this is the part you interact with.
- 04
Feedback
Human ratings and real-world corrections steer the model toward answers that are useful, safe and honest.
What AI can do today
Vision
Computer vision spots patterns in images and video, from scanning medical results to guiding self-driving cars.
Prediction
Models learn from historical data to forecast demand, detect fraud and flag anomalies before people notice them.
Generation
Generative systems create new images, audio, code and video from a short description written in plain language.
Using it responsibly
Bias. A model inherits the blind spots of its training data. Good teams test for uneven outcomes before shipping.
Accuracy. Language models can state wrong things confidently. Verify anything that matters.
Privacy. Think before pasting personal or confidential information into a tool you do not control.