Depends on the context, there is a lot of work in the scientific methods community trying to use NLP to augment traditionally fully human processes such as thematic analysis and systematic literature reviews and you can have protocols for validation there without 100% human review

that is such a ridiculous idea. Just because you see hate for it in the media doesn't mean it originated there. I'll have you know that i have embarrassed myself by screaming at robot phone receptionists for years now. stupid fuckers pretending to be people but not knowing shit. I was born ready to hate LLMs and I'm not gonna have you claim that CNN made me do it.

harder to notice incorrect information in review, than making sure it is correct when writing it.

That depends entirely on your writing method and attention span for review.

Most people make stuff up off the cuff and skim anything longer than 75 words when reviewing, so the bar for AI improving over that is really low.

it specifies the tasks in the article

Do you use an IDE for writing your code or do you use a notepad like a "real" programmer?
An IDE like Intellij has fancy shit like generating getters, setters, constructors, equals hashscode, you should never use those, real programmers write those by hand.

Your attention detail is very good btw, which I am ofc being sarcastic about because if you had any you'd have noticed I have never said I write my code with chat gpt, I said Unit tests, sql for unit tests.

Ofc attention to detail is not a requirement of software engineering so you should be good. (This was also sarcasm I feel like you need this to be pointed out for you).

Also by your implied logic that the code being not written by you = bad, no company should ever hire Junior engineers, I mean what are you gonna do? Fucking read the code they wrote?

Got it, changing your gender to female. Is there anything else I can assist you with?

It’s usually vastly easier to verify an answer than posit one, if you have the patience to do so.

I'm envisioning a world where multiple AI engines create and check each others' work... the first thing they need to make work to support that scenario is probably fusion power.

As useless as a cubicle farm full of unsupervised workers.

I have actually been doing this lately: iteratively prompting AI to write software and fix its errors until something useful comes out. It's a lot like machine translation. I speak fluent C++, but I don't speak Rust, but I can hammer away on the AI (with English language prompts) until it produces passable Rust for something I could write for myself in C++ in half the time and effort.

I also don't speak Finnish, but Google Translate can take what I say in English and put it into at least somewhat comprehensible Finnish without egregious translation errors most of the time.

Is this useful? When C++ is getting banned for "security concerns" and Rust is the required language, it's at least a little helpful.

Tjose are people who could be living their li:es, pursuing their ambitions, whatever. That could get some shit done. Comparison not valid.

It’s usually vastly easier to verify an answer than posit one, if you have the patience to do so.

I usually write 3x the code to test the code itself. Verification is often harder than implementation.

A junior developer actually learns from doing the job, an LLM only learns when they update the training corpus and develop an updated model.

Yes, but the test code "writes itself" - the path is clear, you just have to fill in the blanks.

Writing the proper product code in the first place, that's the valuable challenge.

I'm in a workplace that has tried not to be overbearing about AI, but has encouraged us to use them for coding.

I've tried to give mine some very simple tasks like writing a unit test just for the constructor of a class to verify current behavior, and it generates output that's both wrong and doesn't verify anything.

I'm aware it sometimes gets better with more intricate, specific instructions, and that I can offer it further corrections, but at that point it's not even saving time. I would do this with a human in the hopes that they would continue to retain the knowledge, but I don't even have hopes for AI to apply those lessons in new contexts. In a way, it's been a sigh of relief to realize just like Dotcom, just like 3D TVs, just like home smart assistants, it is a bubble.

DocumentDB is not for one drive documents (PDFs and such). It's for "documents" as in serialized objects (json or bson).

Were you prone to this weird leaps of logic before your brain was fried by talking to LLMs, or did you start being a fan of talking to LLMs because your ability to logic was...well...that?

Neither can we...

Whoa that's like how many colors there are

Emotion > Facts. Most people have been trained to blindly accept things and cheer on what fits with their agenda. Like technbro's exaggerating LLMs, or people like you misrepresenting LLMs as mere statistical word generators without intelligence. That's like saying a computer is just wires and switches, or missing the forest for the trees. Both is equally false.

Yet if it fits with the emotional needs or with dogma, then other will agree. It's a convenient and comforting "A vs B" worldview we've been trained to accept. And so the satisfying notion and misinformation keeps spreading.

LLMs tell us more about human intelligence and the human slop we've been generating. It tells us that most people are not that much more than statistical word generators.

There's a certain amount of: "if this isn't going to take over the world, I'm going to just take my money and put it in something that will" mentality out there. It's not 100% of all investors, but it's pervasive enough that the "potential world beaters" are seriously over-funded as compared to their more modest reliable inflation+10% YoY return alternatives.