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Why AI language models choke on too much text

Large language models represent text using tokens, each of which is a few characters. Short words are represented by a single token (like "the" or "it"), whereas larger words may be represented by several tokens (GPT-4o represents "indivisible" with "ind," "iv," and "isible").

When OpenAI released ChatGPT two years ago, it had a memoryβ€”known as a context windowβ€”of just 8,192 tokens. That works out to roughly 6,000 words of text. This meant that if you fed it more than about 15 pages of text, it would β€œforget” information from the beginning of its context. This limited the size and complexity of tasks ChatGPT could handle.

Today’s LLMs are far more capable:

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