---
title: "What Is Natural Language Processing (NLP)? A Sourced Explainer"
slug: what-is-natural-language-processing
category: ai
category_label: "AI"
author: "BrainWavePost Staff"
date: 2026-06-07
tags: ["nlp", "ai", "language", "basics"]
read_time_minutes: 6
canonical_url: https://brainwavepost.com/article/what-is-natural-language-processing
source: BrainWavePost
---

# What Is Natural Language Processing (NLP)? A Sourced Explainer

*AI · 2026-06-07 · BrainWavePost Staff · 6 min read*

> A short, fully sourced introduction to natural language processing using official definitions from IBM and educational material from Google.

> **How this article is sourced** _(info)_
>
> Definitions here come from IBM's official 'What is NLP?' page and Google's Machine Learning Crash Course. [1][2]

IBM defines natural language processing (NLP) as 'a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language.' The goal is to enable computers to read, understand and derive meaning from human language in a useful way. [1]

## How NLP works at a high level

Google's Machine Learning Crash Course explains that NLP tasks typically involve converting raw text into a structured representation that a model can process. Common steps include tokenisation (splitting text into words or subwords), parsing (analysing grammatical structure), and embedding (converting tokens into numerical vectors). [2]

## Common real-world applications

- Machine translation (e.g. translating between languages). [1]
- Sentiment analysis (determining whether text expresses a positive, negative, or neutral opinion). [1]
- Speech recognition (converting spoken language into text). [1]
- Question answering and chatbots. [1]
- Spam detection and content moderation. [2]

## NLP and large language models

IBM notes that modern large language models (LLMs) such as GPT-4 and Gemini are built on transformer architectures, a specific type of neural network designed for NLP tasks. These models are pre-trained on vast amounts of text and then fine-tuned for specific applications. [1]

> **Key idea** _(tip)_
>
> NLP bridges the gap between human language (messy, ambiguous, context-dependent) and computer processing (structured, literal, mathematical). [1][2]

## References (clickable)

- [1] IBM — What is natural language processing?: https://www.ibm.com/topics/natural-language-processing
- [2] Google — Machine Learning Crash Course, Text Classification: https://developers.google.com/machine-learning/crash-course/embeddings/video-lecture

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