Natural language processing (NLP)
The field of getting computers to work with human language.
A person writes the rules: “If the email mentions ‘lottery’, mark it as spam.”
Show the program ten thousand emails marked spam or not. It works out the patterns itself.
Most of what is called AI today is the second kind. It is powerful because nobody had to write the rules, and hard to explain for exactly the same reason.
The fuller definition
Natural language processing is the field of computing concerned with analysing, understanding, and generating human language. Large language models are one approach within it.
Go deeper
Lines represent computational connections with learned values. This tiny diagram illustrates a neural network; a transformer or mixture-of-experts model has additional structures not shown here.
A concrete example
Classifying emails, extracting names and dates, and summarizing a letter are all NLP tasks.
The distinction that matters
NLP predates generative AI. Many legal-technology tools use older NLP methods that do not generate text at all.
Related terms
Large language model (LLM)
A program trained on enormous amounts of text so it can read and write language. ChatGPT and Claude are built on large language models.
Documents & retrievalEntity extraction
Pulling out names, dates, amounts, and places from text.
FoundationsClassification
Sorting items into groups. For example, put each email in a group based on its topic.
Where it is taught
What actually happens when you ask AI a question?Source and further reading
Google · Machine Learning GlossaryThe definition and example are written for this library. The link gives background, official documentation or legal authority as labelled. Legal scope depends on the jurisdiction and current text; product features depend on release and settings.