Language models & large language models (LLMs)
Dated sources are over 18 months old; other dates are unknown.
Publication dates and source age
Sources counted: 6
Newest dated source: 2024-07
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.
Open in the glossary Reading notes · Structured record
In plain language
An LLM is a model trained to process language. Computer software runs it and, for text generation, produces an answer one piece at a time. [1] [2] [3]
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Limits & distinctions
A model can produce a convincing sentence without checking it against an external source. Search or other tools must be supplied by the surrounding application. [5] [6]
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A fuller explanation
Software runs a large neural network using numerical settings learned from training data. During ordinary text generation, it calculates scores for possible next tokens, selects one, and repeats. Tokens are the pieces of text the model processes. [1] [3] [2] [4]
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How it relates to the map
This is the starting point for the atlas's explanation of how chatbots produce answers. [2]
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https://theaiatlas.org/ideas/llm/
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Image previews are summaries. Keep the page link so readers can check the evidence.
Sources and what we read
1. Models
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 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.
2. Text generation
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 next-token generation, generation settings, temperature, sampling and prompt-format sections. Library options illustrate the process; defaults and suggested temperatures are not treated as universal chatbot behavior. Live page publication date unspecified.
3. LLMs: What's a large language model?
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 token prediction, encoder-only and decoder-only variants, and self-attention. Used for architecture and terminology; broad performance comparisons and claims about all LLMs on the teaching page are not adopted.
4. Tokenizers
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 word, character and subword tokenization, encoding to numerical IDs and decoding. Used for the fact that token boundaries depend on the tokenizer; no fixed words-to-tokens conversion is assumed. Live page publication date unspecified.
5. Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile
Source is over 18 months old.
Publication dates and source age
Sources counted: 1
Newest dated source: 2024-07
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 introduction, section 2.2 on confabulation, and selected MEASURE actions 2.3, 2.5, 2.6, 2.7 and 2.9 concerning evaluation evidence, generalization, citations, generated-code review and safeguards. A voluntary risk-management profile; no claim that all 64 pages or every referenced study was reviewed.
6. Tool use
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 tool descriptions, model-generated call requests, application execution and returning results to the chat. Example functions were not run. Used for the separation between requesting and executing an action; live page publication date unspecified.
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.
Pinned complete dataset · Complete evidence page · Agent consumption guide