Honestly this impresses me most. The fact that we have word prediction and it can still be very useful (in my experience). You're right people don't understand it; hell i don't either, fully. Nevertheless it is shockingly useful for being nothing more than an autocomplete over existing information.. in my view.
Even if all we could add to the service is the ability to cite sources of information - ie to validate for ourselves statements more easily - then i think it would be a huge leap in interfaces.
Being able to put a chat interface over content seems wholly unique to me. I'd love to explore the depth of complex inputs like the entire LOTR series as a chat. To discuss, learn, and grow on existing content. I don't care about intelligence; i just want the ability to mitigate confidently-incorrect. If that's even possible.
Their job is 100 percent to predict the next word, but saying that hides what you have to do in order to predict the next word
In a factual database? You have to repeat facts.
In a logical database? You have to learn logic.
In a database containing only good chess moves? You have to learn to make good chess moves.
Train any AI model in a strong enough way and it will pick up donation knowledge along the way. Yes, it's predicting words, but it's using that knowledge to do it.
It's by no means perfect, but do not underestimate the potential here, and remember that reductive definitions (it's just x) can make most great things seem bad or mundane.
If the approximation works, and the training data is coherent, it will produce coherent responses.
The surprising thing to me is that this does work so much of the time.
LLMs are not supposed to answer knowledge questions. They are not knowledge bases. The fact that everybody, including their developers insist on using them that way is just absurd. Are we in a Kafka novel?
That's the equivalent to complaining that the self driving cars you rented didn't deploy your marketing message effectively, so their AI must be bonkers.
I googled for a knowledge question and wasn't able to find an answer.
Then I used ChatGPT and it produced a surprisingly satisfying (opinionated and correct) response.
I was able to successfully extract value by treating LLM as knowledge base, what exactly is absurd about it?
(to be fair, I asked ChatGPT the same question today and this time it returned a bland "it depends" non-answer).
Barely anyone is calling them LLM, its always AI.
It correctly predict, you need intelligence. This model encodes human knowledge in its huge neural net.