Deep learning
Dated sources are over 18 months old; other dates are unknown.
Publication dates and source age
Sources counted: 2
Newest dated source: 2016
Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.
Some publication dates are unknown; the newest dated source may not be the newest source overall.
Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.
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In plain language
Machine learning that builds several layers of learned calculations on top of one another. [1]
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Limits & distinctions
Deep refers to layers of computation or representation. It is not a measure of wisdom, and there is no universally agreed minimum depth. [1]
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A fuller explanation
In a deep neural network, intermediate layers transform the numbers passed between input and output. Training adjusts settings across the network. These layers can build increasingly complex representations. [2] [1]
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How it relates to the map
Use this term to distinguish a model family from a claim about how quickly AI should advance. [1]
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https://theaiatlas.org/ideas/deep-learning/
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Sources and what we read
1. Deep Learning
Source is over 18 months old.
Publication dates and source age
Sources counted: 1
Newest dated source: 2016
Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.
Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.
Read layered representations and computational depth in Chapter 1. The book’s citation page supplies the publication year. No agreed layer threshold or intelligence measure is inferred.
2. Neural networks: Nodes and hidden layers
Publication dates and source age
Sources counted: 1
Publication dates are unavailable.
Assessed at this edition's evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.
Some publication dates are unknown; the newest dated source may not be the newest source overall.
Publication age does not tell us whether a claim is still valid. Reading an old source again does not make its publication date newer. An update date does not establish that the passage we used was updated.
Read the explanations of connected layers, numerical weights and biases, and calculations. Did not run the embedded exercises. Used for the mathematical structure, not a claim that an artificial network reproduces a human brain.
Edition and machine-readable evidence
Content version 0.20.0. Evidence cutoff 2026-09-15; this does not mean every source was read on that day.
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