6 ms·

LLMs are just text prediction. I don't see the linear path from LLM to AGI. Was there similar hysteria when the calculator or PC first came out?

api 3y ago
I know there were similar hysterias when automated weaving looms and other extreme labor saving machines came out. These machines did actually put a lot of people out of work, but they grew the economy so much that the net number of jobs increased. In a way it's actually a bit dystopian that the "everyone will be put out of work" predictions never come true, because it means we never get that promised age of leisure. Here we are with something like a hundred thousand times the productivity of a medieval peasant working as much or more than a medieval peasant. The hedonic treadmill and the bullshit job creating effects of commerce and bureaucracy eat all our productivity gains. The economy is actually a red queen's race: https://en.wikipedia.org/wiki/Red_Queen%27s_race https://en.wikipedia.org/wiki/Red_Queen%27s_race
- musicale 3y ago
  Automation has increased income inequality for the past few decades, and is likely to continue to do so as more tech jobs and service jobs are automated in addition to office jobs and manufacturing jobs. > In a way it's actually a bit dystopian that the "everyone will be put out of work" predictions never come true, because it means we never get that promised age of leisure. It's disappointing that the economy seems to be structured in such a way for most people "leisure" is equivalent to "unemployment." It probably doesn't help that increases in housing, health care, and higher education costs have outpaced inflation for decades, or that wages have stagnated (partially due to an increase in benefit costs such as health insurance.)
  - api 3y ago
    Not globally: https://kagi.com/proxy/th?c=lUfv1nYBTMKYtKYO-rQ4Vg_QAA9uQJ07x_miHo4CAuO90QGjluUOcocJ6twN5jAEnkFNmJRVdt88SgP7REH4QrvCUBffjoHbWgXHy5VR5BkueBhkYtH5NYDOnpxufaan https://kagi.com/proxy/th?c=lUfv1nYBTMKYtKYO-rQ4Vg_QAA9uQJ07... Outsourcing has stagnated wages in the developed world, but the cost of manufactured goods has also plummeted. The only reason people aren't better off is that the developed world (especially the anglosphere) has a "cost disease" around things like real estate that prevents people from benefiting from global scale price deflation. It doesn't help you much if gadgets are super cheap but housing is insanely expensive. The high cost of housing is unrelated to automation.
    - musicale 3y ago
      > The high cost of housing is unrelated to automation Housing, health care, higher education... all drastically more expensive. The point about outsourcing is a good one. However, automation still appears to drive income inequality (at least in the US.) "Job-replacing tech has directly driven the income gap since the late 1980s, economists report."[1] [1] https://news.mit.edu/2020/study-inks-automation-inequality-0506 https://news.mit.edu/2020/study-inks-automation-inequality-0...
clnq 3y ago
> similar hysteria when the calculator https://twitter.com/mrgreen/status/1640075654417862657 https://twitter.com/mrgreen/status/1640075654417862657
HDThoreaun 3y ago
We don't need AGI to have an extinction risk. Dumb AI might be even more dangerous
dwaltrip 3y ago
It’s not just random text, they are predicting writings and documents produced by humans. They are “language” models. Language is used to say things about the world. This means that predicting language extremely well is best done through acquiring an understanding of the world. Take a rigorous, well-written textbook. Predicting a textbook is like writing a textbook. To write a good textbook, you need to be an expert in the subject. There’s no way around this. The best language models (eg GPT-4) have some understanding of the world. It isn’t perfect, or even very deep in many ways. It fails in ways that we find quite strange and stupid. It isn’t capable of writing an entire textbook yet. But there is still a model of the world in there. It wouldn’t be able to do everything it is capable of otherwise.
- somewhereoutth 3y ago
  To be more precise, it holds a model of the text that has been fed to it. That will be, at very best, a pale reflection of the underlying model of the world.
- tech_ken 3y ago
  >Predicting a textbook is like writing a textbook HN AGI discourse is full of statements like this (eg. all the stuff about stochastic parrots), but to me this seems massively non-obvious. Mimicking and rephrasing pre-written text is very different from conceiving of and organizing information in new ways. Textbook authors are not simply transcribing their grad school notes down into a book and selling it. They are surveying a field, prioritizing its knowledge content based on an intended audience, organizing said information based on their own experience with and opinions on the learning process, and presenting the knowledge in a way which engages the audience. LLMs are a long way off from this latter behavior, as far as I can tell. > The best language models (eg GPT-4) have some understanding of the world This is another statement that I see variants of a lot, but which seems to way overstate the case. IMO it's like saying that a linear regression "understands" econometrics or a series of coupled ODEs "understands" epidemiology; it's at best an abuse of terminology and at worst a complete misapplication of the term. If I take a picture of a page of a textbook the resulting JPEG is "reproducing" the text, but it doesn't understand the content it's presenting to me in a meaningful way. Sure it has primitives with which it can store the content, but human understanding covers a far richer set of behaviors than merely storing/compressing training inputs. It implies being able to generalize and extrapolate the digested information in novel situations, effectively growing one's own training data. I don't see that behavior in GPT-4
deleted 3y ago
[deleted]
mitthrowaway2 3y ago
The statement isn't about LLMs. It doesn't refer to them even once.
- EamonnMR 3y ago
  But if LLMs hadn't captured the popular imagination I doubt this would have been written this year and gotten the attention of enough prominent signatories to frontpage on HN.
  - mitthrowaway2 3y ago
    Maybe. It's happened before. [1] And several of the signatories have expressed views about AI risk for many years. That said, the renewed anxiety is probably not because these experts think that LLMs per se will become generally intelligent. It's more that each time we find out that the human brain does that we thought were impossible for computers to do turn out to be easy, each time we find that it takes 3~5 years for AI researchers to crack a problem we thought would take centuries[2], people sort of have to adjust their perception of how high the remaining barriers to general intelligence might be. And then when billions of investment dollars pour in at the same time, directing a lot more research into that field, that's another factor that shortens timelines. [1] https://news.ycombinator.com/item?id=14780752 https://news.ycombinator.com/item?id=14780752 [2] https://kotaku.com/humans-triumph-over-machines-in-protein-folding-game-fo-5605576 https://kotaku.com/humans-triumph-over-machines-in-protein-f...

api 3y ago

I know there were similar hysterias when automated weaving looms and other extreme labor saving machines came out. These machines did actually put a lot of people out of work, but they grew the economy so much that the net number of jobs increased. In a way it's actually a bit dystopian that the "everyone will be put out of work" predictions never come true, because it means we never get that promised age of leisure. Here we are with something like a hundred thousand times the productivity of a medieval peasant working as much or more than a medieval peasant. The hedonic treadmill and the bullshit job creating effects of commerce and bureaucracy eat all our productivity gains. The economy is actually a red queen's race: https://en.wikipedia.org/wiki/Red_Queen%27s_race https://en.wikipedia.org/wiki/Red_Queen%27s_race

musicale 3y ago
Automation has increased income inequality for the past few decades, and is likely to continue to do so as more tech jobs and service jobs are automated in addition to office jobs and manufacturing jobs. > In a way it's actually a bit dystopian that the "everyone will be put out of work" predictions never come true, because it means we never get that promised age of leisure. It's disappointing that the economy seems to be structured in such a way for most people "leisure" is equivalent to "unemployment." It probably doesn't help that increases in housing, health care, and higher education costs have outpaced inflation for decades, or that wages have stagnated (partially due to an increase in benefit costs such as health insurance.)
- api 3y ago
  Not globally: https://kagi.com/proxy/th?c=lUfv1nYBTMKYtKYO-rQ4Vg_QAA9uQJ07x_miHo4CAuO90QGjluUOcocJ6twN5jAEnkFNmJRVdt88SgP7REH4QrvCUBffjoHbWgXHy5VR5BkueBhkYtH5NYDOnpxufaan https://kagi.com/proxy/th?c=lUfv1nYBTMKYtKYO-rQ4Vg_QAA9uQJ07... Outsourcing has stagnated wages in the developed world, but the cost of manufactured goods has also plummeted. The only reason people aren't better off is that the developed world (especially the anglosphere) has a "cost disease" around things like real estate that prevents people from benefiting from global scale price deflation. It doesn't help you much if gadgets are super cheap but housing is insanely expensive. The high cost of housing is unrelated to automation.
  - musicale 3y ago
    > The high cost of housing is unrelated to automation Housing, health care, higher education... all drastically more expensive. The point about outsourcing is a good one. However, automation still appears to drive income inequality (at least in the US.) "Job-replacing tech has directly driven the income gap since the late 1980s, economists report."[1] [1] https://news.mit.edu/2020/study-inks-automation-inequality-0506 https://news.mit.edu/2020/study-inks-automation-inequality-0...

clnq 3y ago

> similar hysteria when the calculator https://twitter.com/mrgreen/status/1640075654417862657 https://twitter.com/mrgreen/status/1640075654417862657

HDThoreaun 3y ago

We don't need AGI to have an extinction risk. Dumb AI might be even more dangerous

dwaltrip 3y ago

It’s not just random text, they are predicting writings and documents produced by humans. They are “language” models. Language is used to say things about the world. This means that predicting language extremely well is best done through acquiring an understanding of the world. Take a rigorous, well-written textbook. Predicting a textbook is like writing a textbook. To write a good textbook, you need to be an expert in the subject. There’s no way around this. The best language models (eg GPT-4) have some understanding of the world. It isn’t perfect, or even very deep in many ways. It fails in ways that we find quite strange and stupid. It isn’t capable of writing an entire textbook yet. But there is still a model of the world in there. It wouldn’t be able to do everything it is capable of otherwise.

somewhereoutth 3y ago
To be more precise, it holds a model of the text that has been fed to it. That will be, at very best, a pale reflection of the underlying model of the world.
tech_ken 3y ago
>Predicting a textbook is like writing a textbook HN AGI discourse is full of statements like this (eg. all the stuff about stochastic parrots), but to me this seems massively non-obvious. Mimicking and rephrasing pre-written text is very different from conceiving of and organizing information in new ways. Textbook authors are not simply transcribing their grad school notes down into a book and selling it. They are surveying a field, prioritizing its knowledge content based on an intended audience, organizing said information based on their own experience with and opinions on the learning process, and presenting the knowledge in a way which engages the audience. LLMs are a long way off from this latter behavior, as far as I can tell. > The best language models (eg GPT-4) have some understanding of the world This is another statement that I see variants of a lot, but which seems to way overstate the case. IMO it's like saying that a linear regression "understands" econometrics or a series of coupled ODEs "understands" epidemiology; it's at best an abuse of terminology and at worst a complete misapplication of the term. If I take a picture of a page of a textbook the resulting JPEG is "reproducing" the text, but it doesn't understand the content it's presenting to me in a meaningful way. Sure it has primitives with which it can store the content, but human understanding covers a far richer set of behaviors than merely storing/compressing training inputs. It implies being able to generalize and extrapolate the digested information in novel situations, effectively growing one's own training data. I don't see that behavior in GPT-4

deleted 3y ago

[deleted]

mitthrowaway2 3y ago

The statement isn't about LLMs. It doesn't refer to them even once.

EamonnMR 3y ago
But if LLMs hadn't captured the popular imagination I doubt this would have been written this year and gotten the attention of enough prominent signatories to frontpage on HN.
- mitthrowaway2 3y ago
  Maybe. It's happened before. [1] And several of the signatories have expressed views about AI risk for many years. That said, the renewed anxiety is probably not because these experts think that LLMs per se will become generally intelligent. It's more that each time we find out that the human brain does that we thought were impossible for computers to do turn out to be easy, each time we find that it takes 3~5 years for AI researchers to crack a problem we thought would take centuries[2], people sort of have to adjust their perception of how high the remaining barriers to general intelligence might be. And then when billions of investment dollars pour in at the same time, directing a lot more research into that field, that's another factor that shortens timelines. [1] https://news.ycombinator.com/item?id=14780752 https://news.ycombinator.com/item?id=14780752 [2] https://kotaku.com/humans-triumph-over-machines-in-protein-folding-game-fo-5605576 https://kotaku.com/humans-triumph-over-machines-in-protein-f...