What is a language model fundamentally trying to do?

A language model’s core function is to predict the most likely next word in a sequence, based on the preceding text. It achieves this by analyzing patterns and relationships within vast amounts of data, rather than relying on a traditional database of facts.

How does an AI like ChatGPT generate responses?

ChatGPT and similar models work by repeatedly predicting the next word in a sentence, one at a time. This process involves converting text into numerical vectors, weighing the relationships between words, and ultimately choosing the most probable sequence of words to form an answer.

What are some limitations of language models?

Language models can sometimes ‘hallucinate’ or invent incorrect information, as they don't possess true understanding or consciousness. Furthermore, their knowledge is limited to the data they were trained on, without the ability to access real-time information or verify facts independently.

How Does an AI Actually “Think”? Language Models Explained Simply

When you talk to ChatGPT, Claude or another AI chatbot, you quickly get the impression that someone is thinking along with you. The answers seem clever, sometimes even empathetic. But what really happens technically when an AI formulates an answer? This article explains how a language model works – and why the term “thinking” should be taken with a grain of salt.

The basic idea: a language model is not a database

A widespread misconception is that an AI works like a huge library in which facts are stored and retrieved when needed. That is wrong. A language model (Large Language Model, LLM for short) has no reference work in its head from which it quotes answers.

Instead, a language model is at its core a highly developed prediction machine. Its only real task is: which word (or more precisely: which piece of text) is most likely to follow what has been written so far? Everything that looks like knowledge, reasoning or creativity arises from this one principle, applied on a gigantic scale.

However, this does not mean that AI is not intelligent: rather, AI works in a manner similar to the human brain and is capable of independently deriving rules from the examples presented to it.