August 2026
Beginner
272 pages
7h 45m
English
In this chapter
The seemingly magical text generation capacity of LLMs is impressive. But if you think about it, that’s all they do. They take in text. They apply some reasoning to that text. They output text. That’s it.
Their action is confined to strings of text, and in many cases, that’s enough. For example, this would work if we wanted to build an app to summarize a document, translate a message, or answer questions based on a given knowledge base. For many applications, the text-in, text-out ...
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