Collection
The field concerned with building systems that exhibit intelligent behaviour. Spanning machine learning, neural networks, and natural language processing, AI raises deep empirical and philosophical questions about what intelligence is and how it can arise from physical substrates.
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Key principles
A model trained to detect skin cancer learned to look for rulers instead. The explainability problem is not a glitch. It is Goodhart's Law running at machine speed — and the gap between what AI systems can do and what we understand about how they do it is where the most consequential work in the field is now happening.
In 2012, a neural network cracked image recognition in a way that reshaped the entire AI field. Andreas Møgelmose traces what neural networks actually are, how convolutional architectures build understanding in layers, and why a cancer-detection model that learned to spot rulers instead tells us something important about where the field still cannot go.
E20
ComputationE19
TechnologyE13
ComputationE11
TechnologyE10
TechnologyE5
TechnologyThe application of biological knowledge to engineering.
The science and engineering of the universe beyond Earth.
The capacity to do work, and the central organising challenge of modern civilisation.
Systems defined by their connections rather than their components.
The science and practice of making things at scale.