Comment by OJFord | Hacker News Reader

Comment by OJFord | Hacker News Reader

Parent Full thread

'in 2011' is weirdly recent though isn't it, not even to mention specific? Was there some particular advancement in Prolog based NLP around then that those of us with only a basic introduction to it (and not using it in an NLP course) wouldn't be aware of how capable it is in that regard?

Because I agree with you that sounds ridiculous to me, but also my level of Prolog is like

  parent(a, b).
  parent(c, b).
  couple(x, y) :-
    parent(x, z),
    parent(y, z).

and dimly recalling what a 'cut' is. (I'm exaggerating a bit but I've barely used it since university, not even 100% sure about that syntax)

So I'm prepared to believe the state of the art for ChatGPT-like thing done in Prolog is a lot more impressive than I might have expected if someone asked me yesterday.

In fact, when I compared it to Prolog, it was exactly with the view that, back in 2011, it was already possible to define a sentence/text as grammatical or ungrammatical with just a few lines of code. What LLM models like ChatGPT do is generate text based on corpora distributed across the web, grouped, tokenized and trained with a general purpose, but, in the end, they still need the same rules as Prolog to determine whether or not they can regurgitate the text to the user.

The problem is that most people can't see that rabbit r1 is a deceptive product, at least. chatGPT (and Gemini, Claude and many others) doesn't do this (it doesn't trick its users into thinking that the product does one thing, but it actually does another).

I think you have a misconception of how these transformer models work.

I know how they work, and I think it's a really good job. But in the end, they still have to perform a gramatical check (like Prolog sentences) to be sure the text should be sent.

As I say, I know i pushed the limits, that's on me.

Reply on news.ycombinator.com