Review Natural Language Processing

Natural language processing is the field of computing concerned with analyzing, understanding, transforming, and generating human language.

NLP includes tasks such as translation, search, classification, transcription, summarization, and text generation. Large language models are one family of methods used within this broader field.

The broader term helps teams avoid treating every language feature as a chatbot or LLM. Different language tasks can require different methods, evidence, and controls.

An email system uses NLP to classify incoming messages by topic and route them to the correct team.

NLP does not imply that a system understands language in the full human sense, and not every NLP system generates text.

NLP is the toolbox for working with human language.

* [[large-language-model|Large Language Model]] * [[generative-ai|Generative AI]] * [[embedding|Embedding]] * [[chatbot|Chatbot]]

* [NIST AI 100-2 E2025, Adversarial Machine Learning](https://doi.org/10.6028/NIST.AI.100-2e2025) — NIST terminology for natural-language processing and language models. * [Google for Developers, Machine Learning Glossary](https://developers.google.com/machine-learning/glossary) — technical definitions for natural-language and machine-learning concepts.

* Explore language generation through [[large-language-model|Large Language Model]] and meaning-based comparison through [[embedding|Embedding]].