01 · The discovery
The idea, in everyday language
A neural network is a set of connected computational units. Its connections determine how information moves and what patterns the system can recognise. Hopfield showed how a network could store memories as stable collective states.
Hinton used ideas from statistical physics to develop networks that learn the structure of data. These early models helped establish principles behind modern machine learning, though today’s systems are much larger and use many additional techniques.
See the idea
A memory from an imperfect cue
Change how many pixels are obscured.
A simplified nearest-pattern demonstration: compare a damaged letter with two stored patterns. This illustrates associative recall; it is not a simulation of Hopfield dynamics or an AI model.
Why it matters
Learning useful representations from examples became central to image recognition and many other applications of neural networks.
