I know plenty of people who are shittier in writing code than Claude. People with real jobs who are expensive like 50-100k/year.
People whom you have to always handhold and were code review is fundamental.
You can write tests, pr gates etc.
It's still a scale in what you can let them do unsupervised vs controlling them more closely but already better than real people I know. Because they are also a lot faster.
If you have racing thoughts and some magic system responds to you and it's abstract enough (even people on hn do not know how LLMs work, plenty of them) then going for a walk is not enough...
You clearly underestimate the quality of people I have seen and worked with.
And yes guard rails can be added easily.
Security is my only concern and for that we have a team doing only this but that's also just a question of time.
Whatever LLMs ca do today doesn't matter. It matters how fast it progresses and we will see if we still use LLMs in 5 years or agi or some kind of world models.
Debatable I would argue. It's definitely not 'just a statistical model's and I would argue that the compression into this space fixes potential issues differently than just statistics.
But I'm not a mathematics expert if this is the real official definition I'm fine with it. But are you though?
I'm disappointed that you had to add the 'metamagical' to your question tbh
It doesn't matter if ai is in a hype cycle or not it doesn't change how a technology works.
Check out the yt videos from 1blue3brown he explains LLMs quite well.
.your first step is the word embedding this vector space represents the relationship between words. Father - grandfather. The vector which makes a father a grandfather is the same vector as mother to grandmother.
You the use these word vectors in the attention layer to create a n dimensional space aka latent space which basically reflects a 'world' the LLM walks through. This makes the 'magic' of LLMs.
Basically a form of compression by having higher dimensions reflecting kind a meaning.
Your brain does the same thing. It can't store pixels so when you go back to some childhood environment like your old room, you remember it in some efficient (brain efficient) way. Like the 'feeling' of it.
That's also the reason why an LLM is not just some statistical parrot.
It shows that a 'llm' can now work on issues like this today and tomorrow it can do even more.
Don't be so ignorant. A few years ago NO ONE could have come up with something so generic as an LLM which will help you to solve this kind of problems and also create text adventures and java code.