# What is a transformer? The brain behind modern AI [Skip to content](#lm-inhoud)Network/[NL](/en/wat-is-een-transformer)EN[Hubhub.llmnet.nlCompare models on task, language, cost and license.](https://hub.llmnet.nl/en/)[Communitycommunity.llmnet.nlPrompt techniques, patterns and system prompts.](https://community.llmnet.nl/en/)[APIapi.llmnet.nlLLMs in production: rate limits, routing, structured output.](https://api.llmnet.nl/en/)[Consultancyconsultancy.llmnet.nlRolling out AI in an organization, pilot to production.](https://consultancy.llmnet.nl/en/)[Newsnieuws.llmnet.nlAI developments, explained for the Netherlands.](https://nieuws.llmnet.nl/en/)[Benchmarkbenchmark.llmnet.nlMeasure AI quality yourself, on your own tasks.](https://benchmark.llmnet.nl/en/)[Careersvacatures.llmnet.nlAI roles, salaries and career paths in the Netherlands.](https://vacatures.llmnet.nl/en/)[Learnleren.llmnet.nlAI concepts in plain language, beginner to builder.](https://leren.llmnet.nl/en/)[Guidegids.llmnet.nlRun AI privately on your own Mac, PC, NAS or home server.](https://gids.llmnet.nl/en/)[Directorydirectory.llmnet.nlMapping the AI ecosystem: tools, models, companies.](https://directory.llmnet.nl/en/)[Radarradar.llmnet.nlSignals from X, research and communities for indie developers.](https://radar.llmnet.nl/en/)[Appsapps.llmnet.nlReviews of AI apps and open-source repos, with tips for builders.](https://apps.llmnet.nl/en/)[llmnet.nl — main site](https://llmnet.nl/en/)[](https://x.com/intent/post?url=https%3A%2F%2Fleren.llmnet.nl%2Fen%2Fwat-is-een-transformer&text=What%20is%20a%20transformer%3F%20The%20brain%20behind%20modern%20AI)[](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fleren.llmnet.nl%2Fen%2Fwat-is-een-transformer)[](https://www.reddit.com/submit?url=https%3A%2F%2Fleren.llmnet.nl%2Fen%2Fwat-is-een-transformer&title=What%20is%20a%20transformer%3F%20The%20brain%20behind%20modern%20AI)[](#)[](https://x.com/intent/post?url=https%3A%2F%2Fleren.llmnet.nl%2Fen%2Fwat-is-een-transformer&text=What%20is%20a%20transformer%3F%20The%20brain%20behind%20modern%20AI)[](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Fleren.llmnet.nl%2Fen%2Fwat-is-een-transformer)[](https://www.reddit.com/submit?url=https%3A%2F%2Fleren.llmnet.nl%2Fen%2Fwat-is-een-transformer&title=What%20is%20a%20transformer%3F%20The%20brain%20behind%20modern%20AI)[](#)By Ivo Donker — created with AI assistance (Claude & Gemini) · Last updated: July 27, 2026 [LLMNet](/) > [Learning](https://leren.llmnet.nl/en/) > Module # What is a transformer? The brain behind modern AI, intuitively explained Estimated reading time: 6 minutes | Level: Beginner If you use advanced artificial intelligence today, such as language models, chatbots, or automatic translators, you are using a transformer. Since the introduction of this architecture in 2017, it has sparked a revolution in the tech world. But what exactly does a transformer do under the hood, and why does it work so well? In this module, we explain it without complex formulas or heavy math. ## The problem with old AI Before the transformer existed, computers looked at language like an assembly line in a factory: word by word, from left to right. This had a major drawback: if a sentence became long, the computer 'forgot' the beginning of the sentence. Furthermore, a computer could not properly determine the meaning of a word with multiple meanings (such as the word 'bank') without seeing the context of the entire sentence. A transformer solves this by looking at all words in a sentence simultaneously and analyzing how they relate to each other. ## The analogy: A group of editors Imagine reading a complex book. Instead of one person reading the book word by word, you set up a large table with dozens of editors. Each editorial member is assigned one specific word. As soon as the starting signal sounds, all editors shout across the room which other words in the text are important for their word. This way, the editor assigned to the word "bank" immediately knows whether it refers to money or sitting down, because they look at the relationship with words like "borrow" or "cushion" further down the text. The secret weapon: This interconnected network of relationships is called Self-Attention. It enables the AI to instantly determine which words in a sentence deserve the most 'attention' to understand the true meaning. ## Why does this work so well? Thanks to the attention mechanism, a transformer can: - Understand context: Flawlessly link pronouns (like 'he', 'it', 'they') to the correct object, regardless of the distance in the sentence. - Work in parallel: Because not everything has to be calculated sequentially, modern hardware (like GPUs) can process massive amounts of text at lightning speed. - Scale: The more data and computing power you feed into it, the smarter and more accurate the models become. ### Practical Exercise Look at the following sentence: "The cat claws gave the plant no water because they were too dry." Question: What does 'they' mean in this sentence? Does it refer to the cat claws, the plant, or something else? How would a transformer solve this? Hint: A transformer calculates the 'attention score' between 'they' and all possible nouns in the sentence to see which score is the highest. Share your findings with other creators in our [community](https://community.llmnet.nl/en/)! 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