Sustainability & AI
Neural network
A computing model of connected layers of units, loosely inspired by the brain; the basis of deep learning.
Definition
A computational model composed of layers of simple interconnected units whose connection strengths are adjusted during training, loosely inspired by biological neurons.
Quick reference
At a glance
- Subject
- Sustainability & AI
- Editorial status
- Editorial draft
- Definition status
- Established
- Last updated
- 21 August 2026
References
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Overview
What it means
Networks learn by propagating errors backward through their layers to update weights — the backpropagation algorithm. Depth (many layers) enables the hierarchical feature learning reviewed in LeCun, Bengio and Hinton's 2015 Nature paper; scale is what links capability to energy use.
How it is used
Neural networks underlie essentially all modern AI applications in sustainability, from image interpretation to language analysis to control systems. Their behaviour is statistical and data-dependent, which shapes both their power and their failure modes.
Why it matters
As the substrate of contemporary AI, neural networks define what the technology can and cannot do: they interpolate brilliantly within their training distribution and extrapolate unreliably beyond it — a crucial caveat for environmental decisions under novel conditions.
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