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ChatGPT and large language models, explained

ChatGPT, Gemini and Claude are chat assistants built on large language models (LLMs) — neural networks trained on huge amounts of text to read and write language.

An LLM does one thing extremely well: given some text, it predicts what text should come next. Trained on a large part of the internet, that single ability turns out to cover translation, summarising, answering questions, writing code and holding conversations.

What they are good at

Drafting and rewriting text, explaining concepts, translating between major languages, summarising long documents, and helping with routine writing at work or study. For many office tasks they are a genuine time-saver.

What to watch out for

LLMs sometimes hallucinate — state false things fluently and confidently. They reflect their training data, which is mostly English, Chinese and Russian: quality drops sharply for small languages. Never paste personal or secret data into a public chatbot, and always verify facts, laws, dates and medical or financial claims independently.

LLMs and Karakalpak

Today’s global models handle Karakalpak poorly — there is simply too little Karakalpak text on the internet for them to learn from. This is changing as more Karakalpak content goes online; every published page, including this site’s four-language content, becomes future training data. Building that digital foundation for the language is part of the AI Center’s mission.

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