# Algorithm

Record: term-algorithm · Type: term · Edition: 0.20.0 · Evidence cutoff: 2026-09-15

[Read in the atlas](https://theaiatlas.org/ideas/algorithm/) · [Complete evidence](https://theaiatlas.org/evidence.html#idea-algorithm) · [JSON](https://theaiatlas.org/records/term-algorithm.json) · [Pinned complete dataset](https://theaiatlas.org/editions/e74392d479c0e7da8636a7d6a0454d03510df86ffca9931eb86babd952665ca5/data.json)

Dataset pointer: `/glossary/83`. Reviewed: 2026-09-15.

> This is a curated, AI-assisted editorial atlas, not a census, affiliation classifier or independently fact-checked authority.

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## Publication dates and source age

Publication dates are unavailable.

Newest dated source: unavailable. Assessed at this edition’s evidence cutoff: 2026-09-15. 18-month boundary: 2025-03-15.

Publication age does not establish validity or a new source-reading date. Unknown dates and month/year precision remain explicit in the JSON record.

## /summary

A set of steps a computer can carry out to produce a result.

Claim: claim-term-algorithm-1a5192ba3d7825ca26b24a72. Annotation: synthesis.

[glossary-model-algorithm](https://www.nist.gov/dads/HTML/algorithm.html)

## /definition

For example, a sorting algorithm puts a list of numbers in order. Training a language model uses algorithms to adjust its numerical settings.

Claim: claim-term-algorithm-1e4c26398ee834b2e16dc7b8. Annotation: synthesis.

[glossary-model-algorithm](https://www.nist.gov/dads/HTML/algorithm.html) · [google-gradient-descent](https://developers.google.com/machine-learning/crash-course/linear-regression/gradient-descent) · [hf-models](https://huggingface.co/learn/llm-course/en/chapter2/3)

## /placement

Start here when separating the program’s procedure from the model it trains or runs.

Claim: claim-term-algorithm-25f52a21ad9f2e54a62ed1b2. Annotation: editorial.

[glossary-model-algorithm](https://www.nist.gov/dads/HTML/algorithm.html) · [hf-models](https://huggingface.co/learn/llm-course/en/chapter2/3)

## /distinction

An algorithm can include random choices. Calling something an algorithm does not establish that every run gives the same result.

Claim: claim-term-algorithm-09422ce4d5c74cb753a9bb98. Annotation: synthesis.

[glossary-model-algorithm](https://www.nist.gov/dads/HTML/algorithm.html)

## Source provenance

### glossary-model-algorithm

[algorithm](https://www.nist.gov/dads/HTML/algorithm.html)

Paul E. Black / NIST Dictionary of Algorithms and Data Structures · First-hand source (primary) · Published: undated · Updated: 2020-11-09 · Material last read: 2026-09-15 · Verification: read

Read scope is described in the source note.

Read the definition and listed algorithm types. The entry was modified on 9 November 2020; the later HTML formatting date is not a content revision.

No archive check recorded.

### google-gradient-descent

[Linear regression: Gradient descent](https://developers.google.com/machine-learning/crash-course/linear-regression/gradient-descent)

Google for Developers · First-hand source (primary) · Published: undated · Updated: 2026-02-03 · Material last read: 2026-09-15 · Verification: read

Read scope is described in the source note.

Read the iterative prediction, loss and parameter-update explanation. The page's guarantees for convex linear regression are not extended here to neural-network training. Updated date follows the page; initial publication is unspecified.

No archive check recorded.

### hf-models

[Models](https://huggingface.co/learn/llm-course/en/chapter2/3)

Hugging Face LLM Course · First-hand source (primary) · Published: undated · Material last read: 2026-09-15 · Verification: read

Read scope is described in the source note.

Read architecture, weights, checkpoints, loading and saving. Used to distinguish a model's structure and learned values from the application around it. Example code was read, not executed; live page publication date unspecified.

No archive check recorded.