who the fuck is scraeming ‘RTFM’ at my house. show yourself, coward. i will never r any fm
I beg someone to help me. There is this new guy at my workplace, officially as a developer who can’t write code at all. He has pasted an entire project I did into ChatGPT with “optimize this” and pull requested it. I swear.
Reminder that all these Chat-formatted LLMs are just text-completion engines trained on text formatted like a chat. You’re not having a conversation with it, it’s “completing” the chat history you’re providing it. By randomly(!) choosing the next text tokens that seems like they best fit the text provided.
If you don’t directly provide, in the chat history and/or the text completion prompt, the information you’re trying to retrieve, you’re essentially fishing for text in a sea of random text tokens that seems like it fits the question.
It will always complete the text, even if the tokens it chooses minimally fit the context, it chooses the best text it can but it will always complete the text.
This is how they work, and anything else is usually the company putting in a bunch of guide bumpers to reformat prompts into coaxing the models to respond in a “smarter” way (see GPT-4o and “chain of reasoning”)
They were trained on reddit. How much would you trust a chatbot whose brain consists of the entirety of reddit put in a blender?
I am amazed it works as well as it does. Gemini only occasionally tells people to kill themselves.
The only reason i use ChatGPT for some quick stuff is just that search engines suck so bad.
Perplexity (or open source equivalents) are much better for this.
Depending on the task, it’s quicker to verify the AI response than work through the blank page phase.
They don’t give you the answer, they give you a rough idea of where to look for the answer.
I’ve used them to generate chunks of boilerplate code that was 80% of what I needed, because I knew what I needed and wanted to save time.
Probably because they’re not checking them
sigh people do talk about this, they complain about it non-stop. These same people probably aren’t using it as intended, or are deliberately trying to farm a “gotcha” response. AI is a very neat tool which can do a lot of things well, but it’s important to recognize its limitations. I don’t use it for things I don’t understand because I won’t recognize if it’s spitting out nonsense, but for topics I do understand it’s hard to overstate how efficient and time saving it is.
“Give me a vegan recipe using <ingredient>” has been flawless. The recipes are decent, although they tend to use the same spices over and over.
I sometimes use it to “convert” preexisting bulletpoints or informal notes into a professional sounding business email. I already know all the information so proofreading the final product doesn’t take a lot of time.
I think a lot of people who shit on AI forget that some people struggle with putting their thoughts into words. Especially if they aren’t writing in their native language.
Efficiency depends on the cost doesnt it?
The cost to me, the user, is nothing
Sorry to hear that you consider your time worthless. Have you tried therapy for that?
There’s something so uniquely funny about being too stupid to insult someone properly. Thanks for the chuckle
It depends upon what you use ChatGPT for and if you know how to use it productively. For example if I ask ChatGPT coding questions it is often very helpful. If I ask it history questions it constantly makes things up. You also again need to know how to use it, like people who claim ChatGPT is not helpful for coding you ask them how they use it and they basically just ask ChatGPT to do their whole project for them and when it fails they claim it is useless. But that’s not the productive way to use it, the productive way to use it is like a replacement for StackOverflow or to provide you examples of how to use some library, or things like that, not doing your whole project for you. Of course, people often use it incorrectly so it’s probably not a good idea to allow its use in the workplace, but for individual use it can be very helpful.
And thank god it doesn’t get them all the way there, because if it were able to completely do everything accurately with the level of ambiguous prompts the layperson gives it, anyone technical would essentially be out of a job.
And honestly, the world would be better off not making people complacent just being end users of everything, and instead have to have a modicum of understanding what they are doing.
I used to think its just neophobia having all these kids using smart phones and touch screens for everything at increasingly earlier ages, but its like they only know how to use/consume things, never an inkling of trying to tinker with things and understand how to repurpose the mechanisms , figure out how things work (tbf everything now is super integrated, much harder to repair).
It just doesn’t bode well to me when it seems like the future labor force is so disconnected from the underlying systems they use.
For coding it heavily depends on the language. For example, it’s quite decent at writing C#, but whenever I try to ask it any question about rust, it’s either flat out wrong or doesn’t even fucking compile.
Also found it most useful when I know exactly what I want, just don’t know the syntax. Like when I was writing C# code generation for the first time. Also unsurprisingly sucks at working with libraries.
chatgpt has been really good for teaching me code. As long as I write the code myself and just ask for clarity or best practices i haven’t had any bad hallucinations.
For example I wanted to change a character in an array with another one but it would give some error about data types that were way out of my league. Anyways apparently I needed to run list(string) first even though string[5] will return the character.
However that’s in python which I assume is well understood due to the ton of stackoverflow questions and alternative docs. I did ask it to do something in Google docs scripting something once and it had no idea what was going on and just hoped it worked. Fair enough, I also had no idea what was going on.
Because in a lot of applications you can bypass hallucinations.
- getting sources for something
- as a jump off point for a topic
- to get a second opinion
- to help argue for r against your position on a topic
- get information in a specific format
In all these applications you can bypass hallucinations because either it’s task is non-factual, or it’s verifiable while promoting, or because you will be able to verify in any of the superseding tasks.
Just because it makes shit up sometimes doesn’t mean it’s useless. Like an idiot friend, you can still ask it for opinions or something and it will definitely start you off somewhere helpful.
All LLMs are text completion engines, no matter what fancy bells they tack on.
If your task is some kind of text completion or repetition of text provided in the prompt context LLMs perform wonderfully.
For everything else you are wading through territory you could probably do easier using other methods.
Also just searching the web in general.
Google is useless for searching the web today.
Not if you want that thing that everyone is on about. Don’t you want to be in with the crowd?! /s
so, basically, even a broken clock is right twice a day?
Yes, but for some tasks mistakes don’t really matter, like “come up with names for my project that does X”. No wrong answers here really, so an LLM is useful.
great value for all that energy it expends, indeed!
Can’t agree
How is that faster than just picking a random name? Noone picks software based on name.
And yet virtually all of software has names that took some thought, creativity, and/or have some interesting history. Like the domain name of your Lemmy instance. Or Lemmy.
And people working on something generally want to be proud of their project and not name it the first thing that comes to mind, but take some time to decide on a name.
Wouldnt they also not want to take a random name off an AI generated list? How is that something to be proud of? The thought, creativity, and history behind it is just that you put a query into chatgpt and picked one out of 500 names?
Maybe its just a difference of perspective but thats not only not a special origin story for a name, its taking from others in a way you won’t be able to properly credit them, which is essential to me.
I would rather avoid the trouble and spend the time with a coworker or friend throwing ideas back and forth and building an identity intentionally.
I suppose AI could be nice if I was alone nearly all the time.
The process of throwing ideas back and forth usually doesn’t include just choosing one, but generating ideas as jumping off points, usually with some existing concept in mind. Talking with friends, looking at other projects, searching for inspiration online and in the real world, and now also generating some more ideas with an LLM to add to the mix. Using one source and just picking a suggestion probably won’t get you a good result.
No, maybe more like, even a functional clock is wrong every 0.8 days.
https://superuser.com/questions/759730/how-much-clock-drift-is-considered-normal-for-a-non-networked-windows-7-pcThe frequency is probably way higher for most LLMs though lol
Because most people are too lazy to bother with making sure the results are accurate when they sound plausible. They want to believe the hype, and lack critical thinking.
I don’t want to believe any hype! I just want to be able to ask “hey Chatgtp, I’m looking for a YouTube video by technology connections where he discusses dryer heat pumps.” And not have it spit out "it’s called “the neat ways your dryer heat pumps save energy!”
And it is not, that video doesn’t exist. And it’s even harder to disprove it on first glance because the LLM is mimicing what Alex would have called the video. So you look and look with your sisters very inefficient PS4 controller-to-youtube interface… And finally ask it again and it shy flowers you…
But I swear he talked about it ?!?! Anyone?!?
This sound awfully familiar, like almost exactly what people were saying about Wikipedia 20 years ago…
Pretty weak analogy. Wikipedia was technologically trivial and did a really good job of avoiding vested interests. Also the hype is orders of magnitude different, noone ever claimed Wikipedia was going to lead to superhuman intelligences or to replacement of swathes of human creative/service workers.
Actually since you mention it, my hot take is that Wikipedia might have been a more significant step forward in AI than openAI/latest generation LLMs. The creation of that corpus is hugely valuable in training and benchmarking models of natural language. Also it actually disrupted an industry (conventional encyclopedias) in a way that I’m struggling to think of anything that LLMs has replaced in the same way thus far.
Those people were wrong because wikipedia requires actual citations from credible sources, not comedic subreddits and infowars. Wikipedia is also completely open about the information being summarized, both in who is presenting it and where someone can confirm it is accurate.
AI is a presented to the user as a black box and tries to be portray it as equivalent to human with terms like ‘hallucinations’ which really mean ‘is wrong a bunch, lol’.
I only use it for complex searches with results I can usually parse myself like ‘‘list 30 typical household items without descriptions or explainations with no repeating items’’ kind of thing.
great value for all that energy it expends, indeed!
it’s because everyone stopped using it, right?
at least months ago?
They’re trying not to lose money on the developments
It’s usually good for ecosystems with good and loads of docs. Whenever docs are scarce the results become shitty. To me it’s mostly a more targeted search engine without the crap (for now)
