I've been saying "if AI is making you so productive then where is all this great new software" and I guess the answer is the software is out there it's just not great, it's terrible, and nobody is using it
-
@troed @ZanaGB @eniko and what hardware was used to train those models? Whose data was in the training set? Was it properly licensed or was it obtained without consent, compensation or attribution? And what did it cost to gather that training data? Externalities matter, these things don't appear out of thin air
-
@troed @ZanaGB @eniko and what hardware was used to train those models? Whose data was in the training set? Was it properly licensed or was it obtained without consent, compensation or attribution? And what did it cost to gather that training data? Externalities matter, these things don't appear out of thin air
If you want to make completely different points to the one answered - sure!
Has any artist ever compensated another from having looked at their paintings while learning to draw?
Has any budding coder ever compensated others when having studied their code to learn how to do things?
I'm all for lambasting shitty tech bro AI companies, but that's not the same as claiming that any and all LLM usage is bad. I suggest looking at Mistral AI as a european company that's building datacenters using fully renewable energy and ethically sourced data.
-
@troed Alright, now lets look at the statement:
> "if AI is making you so productive then where is all this great new software" and I guess the answer is the software is out there it's just not great, it's terrible, and nobody is using it
and look at the chart where usage is lowering and app reviews are also lowering but more app releases are occurring.... Which is drawing a conclusion that, yeah given the data.. these things aren't being used.
Now to quote you and what you are asserting as the claim.
> The claim was that LLMs don't help in creating programs that people actually use.
That statement is different from the original one. Cute that you tried to change it though!
There is a weighing on the software quality and the usage of it, along with the graph indicating that there is less usage overall given more application releases.
Fwiw, if I wanted to fully clarify what the claim is, I would have asked the original poster to clarify rather than just guessing, which is what you did.
I can't state what their full claim is but I can see semblance of truth in what is being stated given:
* Statement
* Chart
* Journals
* Social consensus (Not reliable but hey, I'll throw it in there)> I gave three examples of apps that people use
I guess you did, dang! I guess if I was to at least track some accounts on there it would be roughly 7 people out of those 3 repos? acknowledging the 5 followers on one and 2 comments left on two of them.
However, that is being generous that those people are using them.
> and that wouldn't have existed without LLM
Maybe for you but I could see someone else making these things or possibly they may already exist. I'm not finding these things special or requiring an LLM for them to exist.
> I'm going to make a wild guess: There's nothing anyone can show you, ever, that will make you change your mind.
If you want to come to that conclusion, that's fine. I understand how you could feel here and it is okay to also be wrong.
@ahto So you're _guessing_ that if I hadn't created those programs someone else would've and that means that the argument that LLMs indeed produce apps that people use is wrong?
I'm sure you believe that you're great at debating.
-
If you want to make completely different points to the one answered - sure!
Has any artist ever compensated another from having looked at their paintings while learning to draw?
Has any budding coder ever compensated others when having studied their code to learn how to do things?
I'm all for lambasting shitty tech bro AI companies, but that's not the same as claiming that any and all LLM usage is bad. I suggest looking at Mistral AI as a european company that's building datacenters using fully renewable energy and ethically sourced data.
@troed not the same thing and you know it. People looking at things and storing copies of someone else's potentially copyrighted data for training are two completely different things. Is it so hard to admit that there are externalities and they are bad no matter how you slice it?
Mistral AI is your run-of-the-mill AI company that does not disclose what's in their training sets, just like everybody else: https://help.mistral.ai/en/articles/347390-does-mistral-disclose-its-training-datasets
-
@troed not the same thing and you know it. People looking at things and storing copies of someone else's potentially copyrighted data for training are two completely different things. Is it so hard to admit that there are externalities and they are bad no matter how you slice it?
Mistral AI is your run-of-the-mill AI company that does not disclose what's in their training sets, just like everybody else: https://help.mistral.ai/en/articles/347390-does-mistral-disclose-its-training-datasets
@gabrielesvelto LLMs don't "store copies" when they train. What happens in their neural networks is very similar to what happens in a human brain when learning.
"run of the mill": https://mistral.ai/news/our-contribution-to-a-global-environmental-standard-for-ai/
-
@ahto So you're _guessing_ that if I hadn't created those programs someone else would've and that means that the argument that LLMs indeed produce apps that people use is wrong?
I'm sure you believe that you're great at debating.
> So you're _guessing_ that if I hadn't created those programs someone else would've and that means that the argument that LLMs indeed produce apps that people use is wrong?
I'm suggesting that it would be incorrect to claim that they (or something like it) wouldn't exist without you and an LLM.
> I'm sure you believe that you're great at debating.
Look at you go! Feeling so sure about my beliefs!
-
@gabrielesvelto LLMs don't "store copies" when they train. What happens in their neural networks is very similar to what happens in a human brain when learning.
"run of the mill": https://mistral.ai/news/our-contribution-to-a-global-environmental-standard-for-ai/
"Alignment Whack-a-Mole : Finetuning Activates Verbatim Recall of Copyrighted Books in Large Language Models"
> "We show that finetuning bypasses these protections: by training models to expand plot summaries into full text, a task naturally suited for commercial writing assistants, we cause GPT-4o, Gemini-2.5-Pro, and DeepSeek-V3.1 to reproduce up to 85-90% of held-out copyrighted books, with single verbatim spans exceeding 460 words, using only semantic descriptions as prompts and no actual book text"
-
"Alignment Whack-a-Mole : Finetuning Activates Verbatim Recall of Copyrighted Books in Large Language Models"
> "We show that finetuning bypasses these protections: by training models to expand plot summaries into full text, a task naturally suited for commercial writing assistants, we cause GPT-4o, Gemini-2.5-Pro, and DeepSeek-V3.1 to reproduce up to 85-90% of held-out copyrighted books, with single verbatim spans exceeding 460 words, using only semantic descriptions as prompts and no actual book text"
Are you asking for a lesson in how LLMs work or did you just want to show off ignorance?
-
Are you asking for a lesson in how LLMs work or did you just want to show off ignorance?
Oh, those are the only choices? I was just adding a link that was relevant and that you might want to read
-
Oh, those are the only choices? I was just adding a link that was relevant and that you might want to read
Let's do it like this: Are there limits to how much you can compress data?
(This is a Computer Science 101 question so don't spend too long on it)
-
Let's do it like this: Are there limits to how much you can compress data?
(This is a Computer Science 101 question so don't spend too long on it)
I'm not here to answer a measure theory question.
I'm just pointing out an article that goes againsts yours.
-
I'm not here to answer a measure theory question.
I'm just pointing out an article that goes againsts yours.
Oh this isn't theory. Let's try again: Is there a limit to how much you can compress data?
I get why you don't _want_ to answer, since the answer proves that with the laws of physics in this universe LLMs don't store copies of their training data.
-
Oh this isn't theory. Let's try again: Is there a limit to how much you can compress data?
I get why you don't _want_ to answer, since the answer proves that with the laws of physics in this universe LLMs don't store copies of their training data.
> Oh this isn't theory. Let's try again: Is there a limit to how much you can compress data?
Well, I'm going to say that it depends on the domain here but you are probably after something specific here.
> I get why you don't _want_ to answer, since the answer proves that with the laws of physics in this universe LLMs don't store copies of their training data.
Oh, please do tell!
-
> Oh this isn't theory. Let's try again: Is there a limit to how much you can compress data?
Well, I'm going to say that it depends on the domain here but you are probably after something specific here.
> I get why you don't _want_ to answer, since the answer proves that with the laws of physics in this universe LLMs don't store copies of their training data.
Oh, please do tell!
No, it doesn't "depends".
https://en.wikipedia.org/wiki/Shannon%27s_source_coding_theorem
If LLMs stored their training data we would apparently be able to compress all of human knowledge into files easily downloadable onto regular computers, since that's the size of LLM models.
They don't. They do however learn and have better memories than human brains so they can indeed regurgitate 460 words in a row (that's from the paper you linked) from a source in some cases.
If you want to play debate, try learning the subject matter first.
-
No, it doesn't "depends".
https://en.wikipedia.org/wiki/Shannon%27s_source_coding_theorem
If LLMs stored their training data we would apparently be able to compress all of human knowledge into files easily downloadable onto regular computers, since that's the size of LLM models.
They don't. They do however learn and have better memories than human brains so they can indeed regurgitate 460 words in a row (that's from the paper you linked) from a source in some cases.
If you want to play debate, try learning the subject matter first.
> No, it doesn't "depends".
Oh okay! I guess, it was silly of myself to assume some constraints. However, I guess you win this one!
> If LLMs stored their training data we would apparently be able to compress all of human knowledge into files easily downloadable onto regular computers, since that's the size of LLM models.
Oh okay! So... LLMs don't store them at all?
> They don't. They do however learn and have better memories than human brains so they can indeed regurgitate 460 words in a row (that's from the paper you linked) from a source in some cases.
But now you are saying they do? If they could regurgitate 460 words in a row, sounds like they stored it or have some kind of memory of it right?
Like, that article was stating "reproduce up to 85-90% of held-out copyrighted books"
So... there is some representation in which one could consider it looking like compression in which HEY, look at that:
"A review of state-of-the-art techniques for large language model compression"https://link.springer.com/article/10.1007/s40747-025-02019-z
-
No, it doesn't "depends".
https://en.wikipedia.org/wiki/Shannon%27s_source_coding_theorem
If LLMs stored their training data we would apparently be able to compress all of human knowledge into files easily downloadable onto regular computers, since that's the size of LLM models.
They don't. They do however learn and have better memories than human brains so they can indeed regurgitate 460 words in a row (that's from the paper you linked) from a source in some cases.
If you want to play debate, try learning the subject matter first.
@troed good, what do you know about modern neuroscience? Because you know what they say: extraordinary claims require extraordinary proof. And you claimed that LLMs memorize things like the human brain, can you prove it? Because @ahto provided one of several.peer reviewed articles that prove without question that LLMs store high-probability training data essentially verbatim. But you didn't provide proof that the human brain store sparse matrixes and multiplies them.
-
@dome @0x0961h @jargoggles @eniko Did you just post text an LLM gave you? Pull your head out of your ass and type your own response.
-
@eniko AI enjoyers always react very emotional to criticism
-
-
@troed not the same thing and you know it. People looking at things and storing copies of someone else's potentially copyrighted data for training are two completely different things. Is it so hard to admit that there are externalities and they are bad no matter how you slice it?
Mistral AI is your run-of-the-mill AI company that does not disclose what's in their training sets, just like everybody else: https://help.mistral.ai/en/articles/347390-does-mistral-disclose-its-training-datasets
AI is being treated like that movie "Blood Diamond". I believe many are unaware, due to the loss of transparency, the costs involved to pull off that simple free prompt generation, which creators were stolen from, which towns had their houses demolished, or what resources were extracted for AI infrastructure.
Quili.ai made an ethical point sitting in as a team of human AI prompt responders to save their town of water scarcity; revealing the community we have forgotten.
← where I wish sloperators were put