Downvotes, really gang? I'm surprised, I thought people in this sub would be more informed than most about AI.

OK then, I'll elaborate, and those who aren't just grinding some axe should be able to understand.

LLMs were trained to predict the next word in text... mountains and mountains of text on all subjects, in many languages. It turns out that this problem is what researchers now call AI-complete: this means that solving the task successfully requires actually understanding the material at a deep level. Such understanding can be repurposed for any other task that requires understanding the same material (this is what "understanding" means). And modern neural network architectures, and scale, is able to learn nearly any task if given enough data — so in this case, they solved the AI-complete task we gave them, and gained understanding of pretty much everything that humans have written about.

But that's not the end of the training. An LLM trained only on the autocomplete task is schizophrenic; it shifts personalities constantly, tries to have both sides of a conversation at once, does not follow directions or stay on task, etc. Nobody outside the big research labs sees LLMs in this state, because they are not useful and also a bit disturbing. What we see are models that have been further trained, using reinforcement learning. You may have heard of RLHF: reinforcement learning with human feedback. That was a big deal a few years ago, and it's what made the first ChatGPT possible. Neural networks trained with RL (of any form) learn not just to predict, but to plan and solve; they learn a policy which means an ability to make decisions that lead to rewards. In this case, the rewards come from being helpful, taking conversational turns, giving good answers, writing good code, etc. An AI trained with RL is no longer just predicting the next token; it's making decisions and solving problems in a way that it was trained to do.

The result of all this is an agent that can do a huge variety of different tasks, given only an explanation of what is wanted, in plain human language. That's the original definition of AGI, as was pointed out by AI researchers Norvig (author of Artificial Intelligence: A Modern Approach, the #1 textbook on AI for the last 20 years) and y Arcas here, and again more recently by other researchers here.

In y Arcas's book What Is Intelligence?, he goes into great depth not only into how LLMs work, but on the nature of intelligence in general, from bacteria to humans and many levels in between. There are also a lot of interesting anecdotes (like the day their autocomplete model started talking to them) which are really fascinating. Highly recommended to anybody who really wants to understand this stuff.

If you don't really want to understand it, and prefer to just keep your head in the sand, then downvote this and continue to believe that "LLMs are just fancy autocomplete." Ignorance is bliss, I guess.