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I can't access the wired article but in one interview he had an angle that I thought was interesting. It was new to me, which was weird because I saw so many do

by ftxbro 3y ago

I can't access the wired article but in one interview he had an angle that I thought was interesting. It was new to me, which was weird because I saw so many doomer angles. His bold angle was that the automatic differentiability makes artificial optimization (training) so much more effective than any algorithm that biological neural systems might be using. According to wikipedia neural systems can do some backpropagation (https://en.wikipedia.org/wiki/Neural_backpropagation https://en.wikipedia.org/wiki/Neural_backpropagation) but Hinton was suggesting that the artificial optimization methods can be so much more powerful. This was funny to me because usually people allow biology the benefit of the doubt for the sake of argument, meekly begging to assume that artificial training might approach the biological abilities to within some order of magnitude, and submissively suggesting that one artificial neural parameter might be worth like 1/100 of a synapse or so if it would please the biologists. Then the AI researchers would say something like even if Moore's law diminishes we will still reach human power by 2050 or whatever. But not Hinton. He's like yeah the artificial training uses math power that goes beyond what our squishy neurotransmitters can muster, and if I were allowed to say AGI already exists then I'd say it, but I'm not allowed so instead I'll say AGI within five years.

TechnicolorByte 3y ago
Having a tenuous grasp of how modern AI/DL networks work and an even more tenuous grasp of neuroscience, can I ask for a ELI5 of the above and a source? Are you saying that Hinton is not a doomer and believes that AGI is inevitable very soon?
- ALittleLight 3y ago
  How does the parent comment imply Hinton is not a doomer? AI Doom is the idea that AI will be very bad for humanity (e.g. extinction) and the idea that AGI is near is compatible with that. To my knowledge Hinton thinks Doom is a significant possibility and that AGI is plausibly near.
  - svnt 3y ago
    Using the term doomer generally implies the doom is unwarranted/an overreaction. Parent is asking whether GP thinks Hinton is justified in predicting actual doom.
- ftxbro 3y ago
  > Having a tenuous grasp of how modern AI/DL networks work and an even more tenuous grasp of neuroscience, can I ask for a ELI5 of the above and a source? I guess you know more than you let on but the tldr of modern AI is: massive GPGPU datacenters, automatic differentiation libraries, artificial neural architectures that scale by just stacking layers, and tera sized digital corpuses. Here's a Hinton quote, as transcribed in https://www.computerworld.com/article/3695568/qa-googles-geoffrey-hinton-humanity-just-a-passing-phase-in-the-evolution-of-intelligence.html https://www.computerworld.com/article/3695568/qa-googles-geo... which is presumably from his interview in https://www.youtube.com/watch?v=sitHS6UDMJc https://www.youtube.com/watch?v=sitHS6UDMJc -- "very recently, I’ve changed my mind a lot about the relationship between the brain and the kind of digital intelligence we’re developing. I used to think that the computer models we were developing weren’t as good as the brain. The aim was to see if you could understand more about the brain by seeing what it takes to improve the computer models. Over the last few months, I’ve changed my mind completely, and I think probably the computer models are working in a completely different way than the brain. They’re using back propagation and I think the brain’s probably not. And a couple things have led me to that conclusion and one of them is the performance of GPT-4." -- My understanding of the pre-joke-explaining "normie" interpretation of the tldr of AI was something like: 'the massive GPGPU datacenters are trying to substitute for the hardware of the brain but badly, inefficiently, and expensively. The automatic differentiation libraries and layer-stacking architectures are trying to substitute the amazing learning abilities of the neurons and synapses in the brain. The tera sized digital corpuses are used by AI in a statistically inefficient way compared to how much humans can learn from such little information.' To me it seems that Hinton is now saying he's changed his mind about some of this interpretation, and that in particular it seems like he thinks the automatic differentiation libraries and layer stacking architectures are fundamentally more effective than what brains are doing with neurons and synapses, in a way that isn't just about clock cycles. This is funny to me because I don't think it's a common opinion on any side of the ai debates. > Are you saying that Hinton is not a doomer It depends what you mean by doomer, but I could speculate. I think he could be described as a dignified doomer with a stiff upper lip. He's 75 years old and I doubt he's holding out hope for a lot of life extension for himself. I don't think he expects to personally witness the real consequences of AGI even if AGI appears in his lifetime. I think he's pretty sure that AGI will eventually replace humanity as we know it. > and believes that AGI is inevitable very soon? maybe 'inevitable' is too strong but yes.
derbOac 3y ago
We actually know so little about human cognition that that assumption seems wildly naive to me. Having said that, I assume that at some point in the future AI's problem-solving abilities will surpass those of humans. But there's still other issues to reckon with even then. I think we should all be much more worried about what humans will do in response to AI than AI itself. Framing this all in terms of AI rather than AI-related policy distracts from the real issues in my opinion. I'm not worried about AI, I'm worried about people: what people will do with it and what rationalizations they will have for how they treat other people as a consequence.

by ftxbro 3y ago

TechnicolorByte 3y ago

Having a tenuous grasp of how modern AI/DL networks work and an even more tenuous grasp of neuroscience, can I ask for a ELI5 of the above and a source? Are you saying that Hinton is not a doomer and believes that AGI is inevitable very soon?

ALittleLight 3y ago
How does the parent comment imply Hinton is not a doomer? AI Doom is the idea that AI will be very bad for humanity (e.g. extinction) and the idea that AGI is near is compatible with that. To my knowledge Hinton thinks Doom is a significant possibility and that AGI is plausibly near.
- svnt 3y ago
  Using the term doomer generally implies the doom is unwarranted/an overreaction. Parent is asking whether GP thinks Hinton is justified in predicting actual doom.
ftxbro 3y ago
> Having a tenuous grasp of how modern AI/DL networks work and an even more tenuous grasp of neuroscience, can I ask for a ELI5 of the above and a source? I guess you know more than you let on but the tldr of modern AI is: massive GPGPU datacenters, automatic differentiation libraries, artificial neural architectures that scale by just stacking layers, and tera sized digital corpuses. Here's a Hinton quote, as transcribed in https://www.computerworld.com/article/3695568/qa-googles-geoffrey-hinton-humanity-just-a-passing-phase-in-the-evolution-of-intelligence.html https://www.computerworld.com/article/3695568/qa-googles-geo... which is presumably from his interview in https://www.youtube.com/watch?v=sitHS6UDMJc https://www.youtube.com/watch?v=sitHS6UDMJc -- "very recently, I’ve changed my mind a lot about the relationship between the brain and the kind of digital intelligence we’re developing. I used to think that the computer models we were developing weren’t as good as the brain. The aim was to see if you could understand more about the brain by seeing what it takes to improve the computer models. Over the last few months, I’ve changed my mind completely, and I think probably the computer models are working in a completely different way than the brain. They’re using back propagation and I think the brain’s probably not. And a couple things have led me to that conclusion and one of them is the performance of GPT-4." -- My understanding of the pre-joke-explaining "normie" interpretation of the tldr of AI was something like: 'the massive GPGPU datacenters are trying to substitute for the hardware of the brain but badly, inefficiently, and expensively. The automatic differentiation libraries and layer-stacking architectures are trying to substitute the amazing learning abilities of the neurons and synapses in the brain. The tera sized digital corpuses are used by AI in a statistically inefficient way compared to how much humans can learn from such little information.' To me it seems that Hinton is now saying he's changed his mind about some of this interpretation, and that in particular it seems like he thinks the automatic differentiation libraries and layer stacking architectures are fundamentally more effective than what brains are doing with neurons and synapses, in a way that isn't just about clock cycles. This is funny to me because I don't think it's a common opinion on any side of the ai debates. > Are you saying that Hinton is not a doomer It depends what you mean by doomer, but I could speculate. I think he could be described as a dignified doomer with a stiff upper lip. He's 75 years old and I doubt he's holding out hope for a lot of life extension for himself. I don't think he expects to personally witness the real consequences of AGI even if AGI appears in his lifetime. I think he's pretty sure that AGI will eventually replace humanity as we know it. > and believes that AGI is inevitable very soon? maybe 'inevitable' is too strong but yes.

derbOac 3y ago

We actually know so little about human cognition that that assumption seems wildly naive to me. Having said that, I assume that at some point in the future AI's problem-solving abilities will surpass those of humans. But there's still other issues to reckon with even then. I think we should all be much more worried about what humans will do in response to AI than AI itself. Framing this all in terms of AI rather than AI-related policy distracts from the real issues in my opinion. I'm not worried about AI, I'm worried about people: what people will do with it and what rationalizations they will have for how they treat other people as a consequence.