Those are good points, thank you very much. I just never connected the dots from Lemmy devs to admins - in my mind they were completely disconnected.
From a cursory check, it seems like piefed is at a good enough place to just switch over - would you say that's a place worth supporting? Or would I just jump from the frying pan into the fire?
Again, I truly appreciate your taking the time to share your experience!
Thank you for taking the time to respond. While I'm aware that there are other paths into the fediverse besides Lemmy, maybe you could walk me through as to why you assert that Lemmy as a software (or probably rather their developers, I guess) can be taken as a bad crowd?
Not sure how to react to your comment, given that I read it through Lemmy. I came here after leaving reddit about a year ago or two, but it seems like we on Lemmy are the bad ones?
I didn't particularly notice it, but have I fallen with a bad crowd, in your opinion? .ml instances and the occasional troll aside, it seems much more constructive and grounded than reddit 😬
I generally hate stuff that tries to claim my attention (through sound, color, light etc) without my say-so. It goes far enough that I cover LEDs on some obnoxious electronics, or switch over to a keyboard with slient switches
My problem with LLMs isn't that they are repetitive. My problem is that we as a society spent literal trillions of dollars in the last few years on the tech bro's promise that pure scaling would improve the outcomes comparably.
That's not what happened however: models that were praised of being capable of "phd-level" reasoning (whatever that is in detail) still make the most basic mistakes and can't be trusted with anything of importance, and most people in the field seem to agree that pure scaling won't change that.
Instead of going back to the drawing board to investigate how "reasoning" can be incorporated, we as a society prepare to double down with another whopping trillion because the next trillion will surely fix the problems.
To put that in perspective: the large hadron collider cost a meager 10 billion, flying to the moon cost around 250 billion dollars (inflation adjusted) over 10 years and ending world hunger comes at around 25 billion per year. So we could feed the world for around 40 years instead. I guess for just twice the cost we could throw in free housing worldwide, so that would end both problems for 20 years.
No idea why OP did it, but for me it demonstrates that the claims of techbros that these LLMs are working on a reasoning level comparable to PhD, is wildly exaggerated. It puts into question if spending literal trillions of dollars for this crap is a good idea, when 250 billion (inflation adjusted) could build the large hadron collider, or a meager 25 billion a year could prevent world hunger.
No, I'm not complaining that chatgpt is shit at reasoning - I'm demonstrating it.
I'm complaining that literal trillions of dollars plus environmental resources are being poured into this fundamentally flawed technology, all while fucking up the job market for entry level applicants.
Only three if I'm being honest, and none of them technically competent, so I'll admit that you have a point here. I'll just add that I assume that Sam Altman had something different in mind when he made that claim.
These models have to analyse and understand the meaning of a prompt rather than what is strictly said
Well, it clearly fails at that, and that's all I'm saying.
I really don't understand what you're arguing here, so I'll assume it must be my poor grasp of the language or the topic.
That said, I salute you and wish you safe travels 👋
The machine thinks that 7 trips are needed to cross the river, because it doesn't understand the question. Readers with actual comprehension understand that only one trip is needed, because the question is not a riddle, even though the it is phrased to resemble one.
Ah thank you, now I see what you mean. And it seems like we're mostly talking about the same thing here 😅
To reiterate: unprecedented amounts of money and resources are being sunk into systems that are fundamentally flawed (among others by semantic drift), because their creators double down on their bad decisions (just scale up more) instead of admitting that LLMs can never achieve what they promise.
So when you're saying that LLMs are just fancy autocorrect, there's absolutely no disagreement from me: it's the point of this post.
And yes, for an informed observed of the field, this isn't news - I just shared the result of an experiment because I was surprised how easy it was to replicate.
I mean, this is just one of half a dozen experiments I conducted (replicating just a few of the thousands that actual scientists do), but the point stands: what PhD (again, that was Sam Qltman'sclaim, not mine) would be thrown off by a web search?
Unless the creators of LLMs admit that their systems won't achieve AGI by just throwing more money at it, shitty claims will prevent the field from actual progress.
I think Data is perfectly capable of love (and many other emotions). It's the tragic twist of his character that he himself believes what he has been told, namely that he couldn't feel.
So he unsuccessfully strives to gain what he unknowingly already has.
Those are good points, thank you very much. I just never connected the dots from Lemmy devs to admins - in my mind they were completely disconnected.
From a cursory check, it seems like piefed is at a good enough place to just switch over - would you say that's a place worth supporting? Or would I just jump from the frying pan into the fire?
Again, I truly appreciate your taking the time to share your experience!
Thank you for taking the time to respond. While I'm aware that there are other paths into the fediverse besides Lemmy, maybe you could walk me through as to why you assert that Lemmy as a software (or probably rather their developers, I guess) can be taken as a bad crowd?
Smol keyboards. Each one was my endgame, but I still like them 🤗
That's true, although I thought you're talking about including the dots into the path, which is absolutely not what anyone wants 😄
I'm a little late to the party, but
PATHshould only consist of the directories, so it should look like this:export PATH=$PATH:/usr/sbin/Not sure how to react to your comment, given that I read it through Lemmy. I came here after leaving reddit about a year ago or two, but it seems like we on Lemmy are the bad ones?
I didn't particularly notice it, but have I fallen with a bad crowd, in your opinion? .ml instances and the occasional troll aside, it seems much more constructive and grounded than reddit 😬
Oof, nicht cool.
I generally hate stuff that tries to claim my attention (through sound, color, light etc) without my say-so. It goes far enough that I cover LEDs on some obnoxious electronics, or switch over to a keyboard with slient switches
My problem with LLMs isn't that they are repetitive. My problem is that we as a society spent literal trillions of dollars in the last few years on the tech bro's promise that pure scaling would improve the outcomes comparably.
That's not what happened however: models that were praised of being capable of "phd-level" reasoning (whatever that is in detail) still make the most basic mistakes and can't be trusted with anything of importance, and most people in the field seem to agree that pure scaling won't change that.
Instead of going back to the drawing board to investigate how "reasoning" can be incorporated, we as a society prepare to double down with another whopping trillion because the next trillion will surely fix the problems.
To put that in perspective: the large hadron collider cost a meager 10 billion, flying to the moon cost around 250 billion dollars (inflation adjusted) over 10 years and ending world hunger comes at around 25 billion per year. So we could feed the world for around 40 years instead. I guess for just twice the cost we could throw in free housing worldwide, so that would end both problems for 20 years.
So I'm fine with LLMs being repetitive, frankly don't care at all, because a trillion dollars are a terrible thing to waste
Hey good news, I just found out how to block users \o/
No idea why OP did it, but for me it demonstrates that the claims of techbros that these LLMs are working on a reasoning level comparable to PhD, is wildly exaggerated. It puts into question if spending literal trillions of dollars for this crap is a good idea, when 250 billion (inflation adjusted) could build the large hadron collider, or a meager 25 billion a year could prevent world hunger.
No, I'm not complaining that chatgpt is shit at reasoning - I'm demonstrating it.
I'm complaining that literal trillions of dollars plus environmental resources are being poured into this fundamentally flawed technology, all while fucking up the job market for entry level applicants.
Only three if I'm being honest, and none of them technically competent, so I'll admit that you have a point here. I'll just add that I assume that Sam Altman had something different in mind when he made that claim.
Marvelous 👌
🤣
I love it!
What were the steps? We might need them in the future 👀
Well, it clearly fails at that, and that's all I'm saying. I really don't understand what you're arguing here, so I'll assume it must be my poor grasp of the language or the topic.
That said, I salute you and wish you safe travels 👋
The machine thinks that 7 trips are needed to cross the river, because it doesn't understand the question. Readers with actual comprehension understand that only one trip is needed, because the question is not a riddle, even though the it is phrased to resemble one.
Ah thank you, now I see what you mean. And it seems like we're mostly talking about the same thing here 😅
To reiterate: unprecedented amounts of money and resources are being sunk into systems that are fundamentally flawed (among others by semantic drift), because their creators double down on their bad decisions (just scale up more) instead of admitting that LLMs can never achieve what they promise. So when you're saying that LLMs are just fancy autocorrect, there's absolutely no disagreement from me: it's the point of this post.
And yes, for an informed observed of the field, this isn't news - I just shared the result of an experiment because I was surprised how easy it was to replicate.
I mean, this is just one of half a dozen experiments I conducted (replicating just a few of the thousands that actual scientists do), but the point stands: what PhD (again, that was Sam Qltman'sclaim, not mine) would be thrown off by a web search?
Unless the creators of LLMs admit that their systems won't achieve AGI by just throwing more money at it, shitty claims will prevent the field from actual progress.
I think Data is perfectly capable of love (and many other emotions). It's the tragic twist of his character that he himself believes what he has been told, namely that he couldn't feel. So he unsuccessfully strives to gain what he unknowingly already has.