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In this first part we look at the conceptual advantages of Large Language Models (LLMs) in document analysis. The technical implementation and practical code examples of the two contrasting pipelines will follow in detail in an accompanying article.

It wasn't long ago that computers could only repeat speech, forming sentences independently was completely out of the question. It's obvious to everyone that this is no longer the case. The days when computers only spoke like parrots are numbered. When you type a prompt into the input field of one of the countless chatbots, the question of how the input is understood, or whether it is truly understood in the real sense, becomes almost inevitable. How does the model understand the term “tree”, for example, and how does this understanding differ from human understanding?