5 ms·

All of this "throwing GPUs at problems" approach has brought us an online casino, domination over transparent games (chess, go) and trivia spitting chatbots (Wa

All of this "throwing GPUs at problems" approach has brought us an online casino, domination over transparent games (chess, go) and trivia spitting chatbots (Watson, ChatGPT) and not much more. It's brisk business for hardware makers, operators and engineers in general. Society keeps getting promised freedom, amazing new tech. And people keep using datacenters-as-a-service to drain speculative VC funds and government subsidies (depending on which side of the Atlantic they are located). The core promise of silver bullet tech that can defeat real world limitations is such an obvious ploy. Well guess what they are just hiding the entropy exhaust somehow. And we keep falling for it.

karmasimida 4y ago
ChatGPT is the silver bullet, you can't convince me otherwise. If the end of deep learning is to achieve artificial intelligence, we had almost achieved it at this stage.
- kabes 4y ago
  Define silver bullet. Because it doesn't really bring us closer to stuff like self driving cars.
  - mdp2021 4y ago
    There is an ironic possibility that the poster confused the expression "silver bullet" for something different from "fake solution placing hopes on shiny idols". (Probably - sorry, just analytically - by negating the expression "it is no silver bullet". Process that does not work, since it is the actual silver bullet that does nothing special.) Edit: although, reading better, the later poster reprised the expression, probably ironically, from the original poster. Sorry, I missed that in the original.
    - losvedir 4y ago
      I don't quite understand your comment, but I think you have your definition of "silver bullet" backwards. It means a solution that works incredibly, almost magically, well.
      - mdp2021 4y ago
        No, it's just a bit complex, but it depends on use - and today it is for a number of reasons more common to see "silver bullet" for "ineffective but seducing". It is a (non-)"solution" that /is believed/ to «work incredibly, almost magically, well». It works in a fable and not outside. One of the first occurrences of the idea was the response of the Oracle of Delphi to Philip II of Macedon (father of Alexander), "With silver arms you may conquer the world". In this case the idea made sense on all planes: Philip understood that he could use bribery to achieve victory, and it worked. But then the idea went on in folklore as a miraculous solution: you "could" use them against spells, then witches, then werewolves, vampires etc. Many reasons may conflate in the whole idea. What happens next is the capillary reach of the scientific mindset, placing silver and the said "evils it cures" in a different place, farther from "dreamlike" perspectives. So, today it is often said a "silver bullet" something that is said to be a "miraculous solution" - but that in reality is just a piece of shiny, alluring metal working well as an excuse to seduce a public in search of hopes, however ill-placed. Populists e.g. are said to have "silver bullets" ready against any sociopolitical illness - they have "solutions" presented as a miracle cure, but they just do not stand scientifically, effectively - though they may be effective in prolonging a career as an elected representative.
        losvedir 4y ago
        > No, it's just a bit complex, but it depends on use - and today it is for a number of reasons more common to see "silver bullet" for "ineffective but seducing". It is a (non-)"solution" that /is believed/ to «work incredibly, almost magically, well». It works in a fable and not outside. Yes, you're re-asserting that, but I still disagree, at least in my dialect of General American English. Maybe you're in the UK and it's different there? In my experience, you almost always hear it as part of the negative: "X is not a silver bullet". That phrase has your meaning of "ineffective but seducing". The implication then is that the silver bullet is effective. Magically so. Everyone associates it with the only thing that can kill a werewolf. The thing that began this whole inane conversation was the mildly interesting use of "silver bullet" in the positive: > ChatGPT is the silver bullet, you can't convince me otherwise. The poster is taking the "no silver bullet" idiom and flipping it on its head. The "standard" usage would say "ChatGPT is no silver bullet", meaning it's not a magical solution to all problems. By negating it (and using the idiom unusually in the positive), they're saying that it is magically effective and can work on all problems.
  - SanderNL 4y ago
    It doesn’t? Given all data of surroundings, isn’t “driving” completing the next “token” (action)?
  - karmasimida 4y ago
    ChatGPT is AN answer as how to create AI. Simple as that. It works as a natural language parser that works the same as human. It is the holy grail that NLP community trying to find, one mechanism that can be commanded by plain English. If it can program, then it can drive cars. Driving is inherently a low level task comparing to programming, hundreds of millions Americans can drive, far fewer can program. But ChatGPT is just blind at the moment. Next step is to make it see, and walk and use its fingers. Won't be too far away in the future.
    - mdp2021 4y ago
      > works the same as human Very certainly not, until you show that it has reflection - critical thinking -, which has many times shown not to have. > Simple as that As already expressed, you cannot just dump personal positions "porque [t]e sale de l'alma" (Borges).
      - chaxor 4y ago
        Reflexion*
        mdp2021 4y ago
        Thanks! It brings us to some checks. But I read > Spelling with -ct- recorded from late 14c., established 18c., by influence of the verb. OED considers the version with -x- to be "the etymological spelling", but Fowler (1926 - «A clear differentiation being out of the question, and the variation of form being without essential significance...») points out that -ct- is usual in the general senses and even technical ones Actually, I would say that 'reflection' is the more proper. 'Reflexion' reflects the French spelling, so it is "«etymological»" in the sense of "post-Hastings 1066" (i.e. tracing the history), but in Latin it is 'flectere' (hence 're-flectere'). "Flectere" is already an action, so "reflection" is proper for the faculty.
        chaxor 4y ago
        Sorry, this was meant to be a semi-sarcastic reference to the paper by Northeastern. They use "Reflexion" in the title. It's a paper about how these systems improve their responses by simply allowing their outputs to be 'reflected upon' by the system. For instance, they are able to improve something like ~60% to ~87% by simply allowing the 'reflection' upon what was just output.
- jackblemming 4y ago
  It boggles my mind how people can think this when Alexnet stepped on the scene over a decade ago and not much has fundamentally improved since then. OpenAI just said they’re not planning on training GPT-5 for awhile because the scaling trick has hit diminishing returns. This isn’t “AGI is 2 years away”, it’s we’ve milked this advancement as best we can and bigger advancements are going to need a fundamental paradigm shift which usually doesn’t happen overnight. Not to say GPT-4 or vision models aren’t amazingly useful, but they’re no silver bullet. I’ve been using GPT-3 for awhile now and it makes a lot of fundamentally stupid mistakes.
  - est31 4y ago
    What about Transformers? And GPT-3 is fundamental improvement to earlier LLMs. Same goes for speech recognition which went from highly parametric to end to end in the last decade. Many other things like stable diffusion, TTS, etc. It's like github's UI. If you use it daily, you maybe notice a little change here or there, but it doesn't disrupt you much. But now if one checks github screenshots from 10 years ago they look so different. Say for example Youtube's auto transcription feature. I remember when it launched, it wasn't that bad but got many things wrong. Now it's really good, still making mistakes but gotten much better.
  - dave_sullivan 4y ago
    "Not much" has fundamentally improved since Alexnet??? Honestly half the comments in this thread boggle my mind. What is even the word for someone that is shown something amazing that they don't understand and then dismisses it on completely superficial grounds? Like if I go back in time and show someone a computer and they think it's just a typewriter and who ever needed one of those anyway? It's like ignorance but in the most willfull, dismissive way possible. Gross.
    - flangola7 4y ago
      The straight denialism around what transformer models can do has been very disappointing, though maybe not unsurprising. Acknowledging what that means acknowledging that your world is about to soon change in massive and unpredictable ways and the future you had planned and expected is not going to happen.
- mdp2021 4y ago
  > you can't convince me otherwise So? Are you trying to make this a poll? > deep learning is to achieve artificial intelligence, we had almost achieved DL has already """achieved""" AI, which was there before the perceptron. In fact, "Artificial Intelligence" is there to solve problems without direct human work, and it has worked pretty well in the past decades in many different domains. This is to say, that our goal has been to have automated problem solvers - that of producing general intelligence (and, before that, general problem solvers) is kind of a different goal.
mxwsn 4y ago
Maybe for general consumers. But deep learning is really a fundamental advance that has impacted science in important ways, e.g. AlphaFold. In general, deep learning learns function approximators that scale smoothly with data and resources, a fundamental advance from prior ML methods like SVMs, with extraordinarily general use.
- mdp2021 4y ago
  A perspective illusion is given by the fact that the area is still importantly in development. See for example the matter of "temporal quality degradation" - a commentary appeared yesterday ( https://news.ycombinator.com/item?id=35566145 https://news.ycombinator.com/item?id=35566145 )
mdp2021 4y ago
> has brought us Also heavy privacy issues ("Throw everything we know about everyone in the computation - and more of it please").
SanderNL 4y ago
All this science nonsense just got us all this mechanical horses that were unnecessary anyway and bigger explosions, who needs all that shit anyway. We keep believing this all leads to something, I’d say drop it all and go back to the woods. Man, I don’t even know where to begin to counter all your unreasonable framing. Watson and ChatGPT in the same list, just dismissing chess and go as “transparent” (whatever that means) games.. just, wow.
- mdp2021 4y ago
  > All this science "Throwing experimentation and modelling at problems" is really not on the same plane as "throwing GPUs at problems". Also because "trying" is part of the preliminary phase.
  - SanderNL 4y ago
    The dismissive (and ignorant) part of this is that throwing GPU’s is all they are doing.
    - mdp2021 4y ago
      I think the poster tried to denounce the hype as a detrimental effect on the AI industry as search for actual solutions. Which may come from the confusion between the phases and outcomes of "Research" and "Development", where the "exciting" results of the "R" have created a fever on the "D" - also, since funding remains critical.
    - namaria 4y ago
      Please all this hard sell on complicated boondogles that will save us from the complexities of life. The concept of AI is as old of computers. Maybe older. People have been claiming we are just some form of AI since writing began. The turn of phrase may have been cast in anger and it clearly displeased people since it got downvoted to oblivion. You can call it dismissive, but calling it ignorant is uncalled for. Producing the first half decent chatbot is not a good outcome given the time and effort put into this.
NovaDudely 4y ago
> It's brisk business for hardware makers, operators and engineers in general. Gold Rush, sell shovels... you get it.
senko 4y ago
Wow, what an incredibly dismissive and jaded take.
- namaria 4y ago
  And you feel like you've added something worthwhile to this conversation?

karmasimida 4y ago

ChatGPT is the silver bullet, you can't convince me otherwise. If the end of deep learning is to achieve artificial intelligence, we had almost achieved it at this stage.

kabes 4y ago
Define silver bullet. Because it doesn't really bring us closer to stuff like self driving cars.
- mdp2021 4y ago
  There is an ironic possibility that the poster confused the expression "silver bullet" for something different from "fake solution placing hopes on shiny idols". (Probably - sorry, just analytically - by negating the expression "it is no silver bullet". Process that does not work, since it is the actual silver bullet that does nothing special.) Edit: although, reading better, the later poster reprised the expression, probably ironically, from the original poster. Sorry, I missed that in the original.
  - losvedir 4y ago
    I don't quite understand your comment, but I think you have your definition of "silver bullet" backwards. It means a solution that works incredibly, almost magically, well.
    - mdp2021 4y ago
      No, it's just a bit complex, but it depends on use - and today it is for a number of reasons more common to see "silver bullet" for "ineffective but seducing". It is a (non-)"solution" that /is believed/ to «work incredibly, almost magically, well». It works in a fable and not outside. One of the first occurrences of the idea was the response of the Oracle of Delphi to Philip II of Macedon (father of Alexander), "With silver arms you may conquer the world". In this case the idea made sense on all planes: Philip understood that he could use bribery to achieve victory, and it worked. But then the idea went on in folklore as a miraculous solution: you "could" use them against spells, then witches, then werewolves, vampires etc. Many reasons may conflate in the whole idea. What happens next is the capillary reach of the scientific mindset, placing silver and the said "evils it cures" in a different place, farther from "dreamlike" perspectives. So, today it is often said a "silver bullet" something that is said to be a "miraculous solution" - but that in reality is just a piece of shiny, alluring metal working well as an excuse to seduce a public in search of hopes, however ill-placed. Populists e.g. are said to have "silver bullets" ready against any sociopolitical illness - they have "solutions" presented as a miracle cure, but they just do not stand scientifically, effectively - though they may be effective in prolonging a career as an elected representative.
      - losvedir 4y ago
        > No, it's just a bit complex, but it depends on use - and today it is for a number of reasons more common to see "silver bullet" for "ineffective but seducing". It is a (non-)"solution" that /is believed/ to «work incredibly, almost magically, well». It works in a fable and not outside. Yes, you're re-asserting that, but I still disagree, at least in my dialect of General American English. Maybe you're in the UK and it's different there? In my experience, you almost always hear it as part of the negative: "X is not a silver bullet". That phrase has your meaning of "ineffective but seducing". The implication then is that the silver bullet is effective. Magically so. Everyone associates it with the only thing that can kill a werewolf. The thing that began this whole inane conversation was the mildly interesting use of "silver bullet" in the positive: > ChatGPT is the silver bullet, you can't convince me otherwise. The poster is taking the "no silver bullet" idiom and flipping it on its head. The "standard" usage would say "ChatGPT is no silver bullet", meaning it's not a magical solution to all problems. By negating it (and using the idiom unusually in the positive), they're saying that it is magically effective and can work on all problems.
- SanderNL 4y ago
  It doesn’t? Given all data of surroundings, isn’t “driving” completing the next “token” (action)?
- karmasimida 4y ago
  ChatGPT is AN answer as how to create AI. Simple as that. It works as a natural language parser that works the same as human. It is the holy grail that NLP community trying to find, one mechanism that can be commanded by plain English. If it can program, then it can drive cars. Driving is inherently a low level task comparing to programming, hundreds of millions Americans can drive, far fewer can program. But ChatGPT is just blind at the moment. Next step is to make it see, and walk and use its fingers. Won't be too far away in the future.
  - mdp2021 4y ago
    > works the same as human Very certainly not, until you show that it has reflection - critical thinking -, which has many times shown not to have. > Simple as that As already expressed, you cannot just dump personal positions "porque [t]e sale de l'alma" (Borges).
    - chaxor 4y ago
      Reflexion*
      - mdp2021 4y ago
        Thanks! It brings us to some checks. But I read > Spelling with -ct- recorded from late 14c., established 18c., by influence of the verb. OED considers the version with -x- to be "the etymological spelling", but Fowler (1926 - «A clear differentiation being out of the question, and the variation of form being without essential significance...») points out that -ct- is usual in the general senses and even technical ones Actually, I would say that 'reflection' is the more proper. 'Reflexion' reflects the French spelling, so it is "«etymological»" in the sense of "post-Hastings 1066" (i.e. tracing the history), but in Latin it is 'flectere' (hence 're-flectere'). "Flectere" is already an action, so "reflection" is proper for the faculty.
        chaxor 4y ago
        Sorry, this was meant to be a semi-sarcastic reference to the paper by Northeastern. They use "Reflexion" in the title. It's a paper about how these systems improve their responses by simply allowing their outputs to be 'reflected upon' by the system. For instance, they are able to improve something like ~60% to ~87% by simply allowing the 'reflection' upon what was just output.
jackblemming 4y ago
It boggles my mind how people can think this when Alexnet stepped on the scene over a decade ago and not much has fundamentally improved since then. OpenAI just said they’re not planning on training GPT-5 for awhile because the scaling trick has hit diminishing returns. This isn’t “AGI is 2 years away”, it’s we’ve milked this advancement as best we can and bigger advancements are going to need a fundamental paradigm shift which usually doesn’t happen overnight. Not to say GPT-4 or vision models aren’t amazingly useful, but they’re no silver bullet. I’ve been using GPT-3 for awhile now and it makes a lot of fundamentally stupid mistakes.
- est31 4y ago
  What about Transformers? And GPT-3 is fundamental improvement to earlier LLMs. Same goes for speech recognition which went from highly parametric to end to end in the last decade. Many other things like stable diffusion, TTS, etc. It's like github's UI. If you use it daily, you maybe notice a little change here or there, but it doesn't disrupt you much. But now if one checks github screenshots from 10 years ago they look so different. Say for example Youtube's auto transcription feature. I remember when it launched, it wasn't that bad but got many things wrong. Now it's really good, still making mistakes but gotten much better.
- dave_sullivan 4y ago
  "Not much" has fundamentally improved since Alexnet??? Honestly half the comments in this thread boggle my mind. What is even the word for someone that is shown something amazing that they don't understand and then dismisses it on completely superficial grounds? Like if I go back in time and show someone a computer and they think it's just a typewriter and who ever needed one of those anyway? It's like ignorance but in the most willfull, dismissive way possible. Gross.
  - flangola7 4y ago
    The straight denialism around what transformer models can do has been very disappointing, though maybe not unsurprising. Acknowledging what that means acknowledging that your world is about to soon change in massive and unpredictable ways and the future you had planned and expected is not going to happen.
mdp2021 4y ago
> you can't convince me otherwise So? Are you trying to make this a poll? > deep learning is to achieve artificial intelligence, we had almost achieved DL has already """achieved""" AI, which was there before the perceptron. In fact, "Artificial Intelligence" is there to solve problems without direct human work, and it has worked pretty well in the past decades in many different domains. This is to say, that our goal has been to have automated problem solvers - that of producing general intelligence (and, before that, general problem solvers) is kind of a different goal.

mxwsn 4y ago

Maybe for general consumers. But deep learning is really a fundamental advance that has impacted science in important ways, e.g. AlphaFold. In general, deep learning learns function approximators that scale smoothly with data and resources, a fundamental advance from prior ML methods like SVMs, with extraordinarily general use.

mdp2021 4y ago
A perspective illusion is given by the fact that the area is still importantly in development. See for example the matter of "temporal quality degradation" - a commentary appeared yesterday ( https://news.ycombinator.com/item?id=35566145 https://news.ycombinator.com/item?id=35566145 )

mdp2021 4y ago

> has brought us Also heavy privacy issues ("Throw everything we know about everyone in the computation - and more of it please").

SanderNL 4y ago

All this science nonsense just got us all this mechanical horses that were unnecessary anyway and bigger explosions, who needs all that shit anyway. We keep believing this all leads to something, I’d say drop it all and go back to the woods. Man, I don’t even know where to begin to counter all your unreasonable framing. Watson and ChatGPT in the same list, just dismissing chess and go as “transparent” (whatever that means) games.. just, wow.

mdp2021 4y ago
> All this science "Throwing experimentation and modelling at problems" is really not on the same plane as "throwing GPUs at problems". Also because "trying" is part of the preliminary phase.
- SanderNL 4y ago
  The dismissive (and ignorant) part of this is that throwing GPU’s is all they are doing.
  - mdp2021 4y ago
    I think the poster tried to denounce the hype as a detrimental effect on the AI industry as search for actual solutions. Which may come from the confusion between the phases and outcomes of "Research" and "Development", where the "exciting" results of the "R" have created a fever on the "D" - also, since funding remains critical.
  - namaria 4y ago
    Please all this hard sell on complicated boondogles that will save us from the complexities of life. The concept of AI is as old of computers. Maybe older. People have been claiming we are just some form of AI since writing began. The turn of phrase may have been cast in anger and it clearly displeased people since it got downvoted to oblivion. You can call it dismissive, but calling it ignorant is uncalled for. Producing the first half decent chatbot is not a good outcome given the time and effort put into this.

NovaDudely 4y ago

> It's brisk business for hardware makers, operators and engineers in general. Gold Rush, sell shovels... you get it.

senko 4y ago

Wow, what an incredibly dismissive and jaded take.

namaria 4y ago
And you feel like you've added something worthwhile to this conversation?