| LLMs would be better nomenclature than AI in this context. LLMs are not factual databases. They are not trained to retrieve or produce factual statements. LLMs give you the most likely word after some prior words. They are incredibly accurate at estimating the probabilities of the next word. It is a weird accident that you can use auto-regressive next word prediction to make a chat bot. It's even weirder that you can ask the chatbot questions and give it requests and it appears to produce coherent answers and responses. LLMs are best thought of as language generators (or "writers") not as repositories of knowledge and facts. LLM chatbots were a happy and fascinating (and for some, very helpful) accident. But they were not designed to be "factually correct" they were designed to predict words. People don't care about (or are willing to accept) the "wrong answers" because there are enough use cases for "writing" that don't require factual accuracy. (see for instance, the entire genre of fiction writing) I would argue that it is precisely LLMs ability to escape the strict accuracy requirements of the rest of CS and just write/hallucinate some fiction that is actually what makes this tech fascinating and uniquely novel. |
For this question, what LLMs were designed for is I think less relevent than what they are advertised for, e.g.
"Get answers. Find inspiration. Be more productive. Free to use. Easy to try. Just ask and ChatGPT can help with writing, learning, brainstorming, and more." https://openai.com/chatgpt/
No mention of predicting words.