What is Tokenization? A Simple Explanation
Learn how computers and AI understand human language through tokenization - breaking down the process from words to numbers and back
Introduction
What is Tokenization? In this article, I will explain what tokenization is in simple words. Have you ever thought about how a computer or AI understands human language? The truth is, computers don't actually understand words they only understand numbers. This has been true from the first computer ever made till today. Tokenization is the process that changes our words into a form the computer can work with, so it can read, understand, and reply to us.
What is Tokenization?
Tokenization is a method of breaking something into smaller parts. These smaller parts are called tokens. In AI tokens can be whole words, chunks of words, or even a single letter it all depends on the algorithm.
For example, if you type "Hey how are you" the Tokenizer first split it into tokens like "Hey", "ho", "w", "are yo", "u". If you want to see how different model Tokenization work you can visit this site: Tokenization
Their algorithms are very smart they know how to split words in a smart way. For example words like "Hey", "Hi", **"**How", "are", etc., are used very often in everyday sentences because they appear so frequently the algorithm will tokenize the entire word as a single token.
Now take an example of my name amaan. The algorithm might split it into "am", "a", and "an". Why? Because "am" and "an" are common parts of many words and sentences that we use daily. so the algorithm already has them stored in its "dictionary" of tokens. This makes processing faster and more efficient.
Encode and Decode
Then, the encoder comes into picture. Each token is turned into numbers, like:
"Hey", "How", "are", "you" → [012, 235, 45, 520, 78]
Once the words are turned into numbers they're sent to the AI (like ChatGPT) which process them and sends back a response as numbers, for example: [890, 456, 401]
And then finally the algorithm decode those numbers back into text, such as "Hi, I am fine", and that's the reply you see.
Sounds a bit confusing right? That's why it all happens behind the scenes so we can chat naturally in our own language.
I built an app that lets you visualize how a tokenizer works from breaking text into tokens to encoding and decoding them. You can check it out here on GitHub: https://github.com/amaanpatell/Tokenizer
Why Tokenization Matters
- Improves communication between humans and computers
- Makes information easier to process
Conclusion
Now you've got a basic idea of what tokenization is and how it works behind the scenes. The next time you type something into an AI model you can picture the process your words get broken into tokens those tokens are turned into numbers the AI processes them and then the numbers are decoded back into words for your answer.
Isn't it Sounds like a lot of work for a single question right? And it is lot of work tokenizing, encoding, processing, and decoding all take lot of computing power. That's why these AI models run on crazy powerful CPUs and GPUs. that's the reason why companies like Nvidia, which make the chips powering AI, have seen their stock prices shoot up during the AI boom.
