Large language models are like super-smart text detectives who read and write stories all day long.
Imagine you have a big box full of puzzle pieces, each piece has a word on it. These models use these puzzle pieces to figure out what comes next in a sentence or story. They look at the words already used, think about how they fit together, and then pick the best puzzle piece to add next.
How They Read
When the model reads something, it looks at each word one by one, like reading a book from left to right. It tries to understand what each word means based on the ones before it. This helps it guess what might come next.
How They Write
When the model writes something, it starts with a few words and keeps adding more. It's like playing a game where you say a sentence out loud and keep going, "I went to the park because..." Then you think about what makes sense after that and say the next part.
These models don’t use magic, they just have lots of practice and a big box of puzzle pieces to help them read and write stories like pros!
Examples
- A language model breaks down a sentence into individual words, then predicts the next word based on what it has learned.
- It's like having a friend who reads lots of books and can guess the next word in a story just by remembering patterns from those books.
- When you type 'The cat sat on the', the model might predict 'mat' because that’s a common ending to that sentence.
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See also
- How are large language models like ChatGPT actually trained?
- How are deepfakes created, and what are their implications?
- How do AI hallucinations happen in large language models?
- How Do Computers Actually Understand What You Type?
- How do AI hallucinations occur in large language models?