Probably in large part because you can't verify when its wrong since that isn't your area of expertise, so those advice looks better to you.
You should assume your org will be the same quality as a program written by a non-technical person using an LLM if you do it that way.
She reports that he is really nice, but some times he is insisting that he knows the working of some part of the system and is giving advice based on his understanding. Only thing is that he is wrong.
The software engineer needs to "de-hallucinate" him in order to get a proper answer.
I think we are at a time where we need not to categorically be critical about these things. Yes, preciseness is an issue. But there is a good chance that the LLM advice is on par with a random dude from a local accelerator.
This is not how modern training pipelines work. The models are trained on proprietary alignments that ensure factuality.
Regardless, that random dude from a local accelerator probably regurgitates those blog articles himself.
Just like reviews "ensure" correctness on Wikipedia - which is actually a good case. In my childhood teachers would make us avoid Wikipedia. Now they advice students to use it.
Most of the wrong thing it says is just invented by the model, not things it has seen, cleaning up the input doesn't add much there since it writes the same kind of bullshit as bullshitting humans do.
> The software engineer needs to "de-hallucinate" him in order to get a proper answer.
The question is not whether a model is sound and complete. The question how LLMs perform in comparison to the existing solutions.
Don't let perfect get in the way of good.
Let's take an example. I studied physics and can likely answer most questions on nuclear physics. However, as it is a while back, my answers will not sound as smooth, and I may have to correct myself a few times.
If you ask ChatGPT the same questions, it will come up with elegant, convincing answers. As a layman, you will likely prefer what ChatGPT comes up with, as it is answers are eloquent. Of course, until you build a nuclear reactor using ChatGPT knowledge. Once the fuel rods become critical and start making its way through the earth's crust, you may realise you should have relied on my stumbling answers instead.
At very least, ChatGPT doesn't intentionally try to mislead me to sell me something (yet).
I have a friend who has business experience and has been getting verifiably helpful marketing advice from LLMs.
Sales are up. That’s all that matters for any set of instructions: does it lead to the expected end result.
These “do LLMs always hallucinate” questions are in the category of “do humans have a soul”. This is fine and dandy but the conversation doesn’t always need to go there as there is practical utility to discuss as well.
Which is a kind of Gell-Mann Amnesia. Which, I just noticed, has “LLM” in the name.
https://www.goodreads.com/quotes/65213-briefly-stated-the-ge...
Talking to people in other fields, e.g., history and literature, they say it’s the same for them.
LLMs are only useful if you know the topic you’re asking questions about. Otherwise, they generate so much nonsense that you cannot verify, that trusting it becomes a liability.
IME it hallucines rarely when asked practical programming questions but basically constantly when asked math questions beyond basic calculus.
As a business owner with both applied experience and formal education on both the tech and the business sides, I wouldn’t trust random LLM-generated advice on business. There are nuances and a certain humanity in good business that an LLM is unlikely to pick up. And the Internet is filled with horrible advice and useless insight on running a business that it can’t distinguish from good advice and valuable insight.
My advice to anyone seriously considering a business is that a course or reading a good survey text on business will pay off in ways that ChatGPT can’t (yet?) give you.
People are falling into the same trap of accepting authoritative sounding advice as true in an area they are not experts in.
Not true, and you're missing a key point for the topic at hand. LLMs are useful if you know the topic OR if you have measurable outcomes. If you want to increase sales, and you ask an LLM how to increase sales, you will know if its ideas work if they result in increased sales.
Think of it like AlphaGo - it learned to play Go by playing with an AI despite having no knowledge of Go strategy, because it could determine what was effective based on outcomes.
Only if OP is themself not somewhat business savvy
“ because you can't verify when its wrong since that isn't your area of expertise, so those advice looks better to you.”