No, its much, much more primitive than an LLM.

It scans your last message for keywords, potentially multiple keywords, keywords in some order, etc, fairly simple patterns you can use something like regex to parse.

Then, based on what it detects, it picks from something like a tree of responses, maybe reinserting the specific keyword you used.

Basically, imagine plotting out the entire dialogue tree from some video game.

… It really is not too much more complex than that.

An LLM, on the other hand, has been trained on something like trillions of pages of text, which then gets processed through multiple billions of layers of per word/character comparative analysis, producing a very complex set of relationships between characters and words, that it then uses to evaluate responses.

And when I say ‘very complex’ I mean that the results of parsing all the training data are not human readable, even by experts, its a gibberish mass of relationships between billions of matrices, something like that… its not even really code that you could read and then say ‘oh! that part is causing this problem!’

So tldr:

I could probably teach you how to write a simple oldschool chatbot that works in a terminal or on IRC, in like, a week or two, even if you have literally 0 prior coding experience. You could easily make a simple chatbot fit in under a megabyte of code, even under a tenth or hundredth of a megabyte, for the actual chat parts of it.

… I absolutely could not teach you how to make an LLM from scratch, and even if I could, we’d have to rent some server clusters to process even a tiny training data set, for a very primitive version of al LLM. And it would take up gigabytes of local space, and thats with the finished, condensed, ‘trained’ model. Could easily be thousands of times more data that would go into the training.