11 ms·

Geoff Hinton Wants Computers to Think More Like Brains

126 points by Osiris30 8y ago

thrwthrw93223 8y ago
Side comment: hacker news is known for having the ‘author here’ moments in threads. Has Professor Hinton ever made a known appearance on HN?
- visarga 8y ago
  I know Hinton participated in a few AMA sessions on reddit.
criddell 8y ago
> The brain is solving a very different problem from most of our neural nets. You’ve got roughly 100 trillion synapses. Hinton doesn't mention microtubules at all. Do any of the neural net or other connected neuron models incorporate the quantum vibration effects inside the neuron's microtubules?
- daveguy 8y ago
  Not a neurophysiologist. Can you point me to any controlled studies verifying this microtubule quantum effects? If not, a principle based description of the theory and hypothesized effects would be helpful too. Microtubule physiology characterization would also be good. Completely not up to date on neurophysiology so pretty much any references would help. Thanks in advance! Edit: Nevermind on microtubule resources. Plenty on the physiology references for those.
  - criddell 8y ago
    The quantum vibrations might be crackpottery, but the microtubules might still be information carriers[1]. I'm still curious if any neural net models incorporate these paths. [1]: https://onlinelibrary.wiley.com/doi/pdf/10.1111/jnc.12621 https://onlinelibrary.wiley.com/doi/pdf/10.1111/jnc.12621
    - etiam 8y ago
      Nets used for practical machine learning today are too abstract to incorporate them in any meaningful way. When you reduce the whole "neuron" to a weighted sum wrapped by some nonlinear function, in discrete timesteps, you've killed so much structure in the modelling it doesn't matter if the original information transfer path was supposed to be by membrane depolarization or by modifying cytoskeleton strands. Arguably if there is a cytoskeleton mechanism for signalling or storage it's captured in some ways in changing the weights and evaluating the net, but not if it had any unique function beyond the abstraction which was already in place from the conventional view. Studying other structures than the synapses and membranes is prudent, but Hameroff must be somewhere on the line between crackpot and intellectual poseur. Use your time on some real science instead. Here's one option: http://www.gatsby.ucl.ac.uk/~lmate/biblio/dayanabbott.pdf http://www.gatsby.ucl.ac.uk/~lmate/biblio/dayanabbott.pdf
- aaaaaaaaaab 8y ago
  I thought quantum microtubules are still considered crackpottery.
  - criddell 8y ago
    That could be. I'm the furthest thing from an expert in this.
  - jostmey 8y ago
    They are
  - codekilla 8y ago
    Stuart Hammeroff gave a talk here at Caltech about them last year.....which surprised me a bit. It is still considered far afield from mainstream neuroscience, however, quantum biology is something many are seriously thinking about.
  - lenticular 8y ago
    There are definitely a few non-crackpots interested in quantum microtubules, but it seems very far from mainstream. It's conceivable that quantum effects could matter in some way on very small scales, and that doesn't really have anything to do with quantum mysticism.
xpuente 8y ago
The big question here is: How brains think?
- paraschopra 8y ago
  Active Inference is one possible hypothesis unifying different ideas on how brains think.
AndrewKemendo 8y ago
There's a logical inconsistency here: Statement 1:I’ve always been worried about potential misuses in lethal autonomous weapons. I think there should be something like a Geneva Convention banning them, like there is for chemical weapons. Statement 2: You should regulate them (AI) based on how they perform. You run the experiments to see if the thing’s biased, or if it is likely to kill fewer people than a person. The intention of utilizing AI in weapons systems is to reduce human error in their application. So is it unethical to implement an "AI" in a weapons system that kills fewer people than a person would? Seperately, I am curious why Hinton is not talking more about state representation and prediction, as almost uniformly across DL/RL researchers this is agreed upon as the next step forward. Hinton certainly is working with Richard Sutton on his RL programs at U Alberta. Sutton believes that the next step in AI systems is state representation and prediction and gave a quick talk on it recently [1]. [1] https://www.youtube.com/watch?v=6-Uiq8-wKrg https://www.youtube.com/watch?v=6-Uiq8-wKrg
- b_tterc_p 8y ago
  That feels like a question of decision making vs execution. I think most people would prefer we don’t let machines choose who to kill. We are probably ok with AI guided projectiles towards selected targets.
- chongli 8y ago
  The intention of utilizing AI in weapons systems is to reduce human error in their application. So is it unethical Reducing human error is one possible benefit of AI weapon systems but there are numerous drawbacks. AI weapons could be programmed to violate laws and commit atrocities on an incomprehensible scale. They could conceivably cause the extinction of human beings or even all life on the planet. They don't even need to be sentient, let alone super intelligent, to accomplish this. If they can be mass produced and armoured well enough to resist most small arms fire, they could easily overwhelm any human armies. The scariest part of the Terminator films is not Skynet, it's the terminators themselves and they're far more plausible than a godlike super-AI.
- articwombat 8y ago
  Statement 2 is not in regards to weapons systems. It is referencing things like self-driving cars. You can see that if you include the next sentence. "ou should regulate them based on how they perform. You run the experiments to see if the thing’s biased, or if it is likely to kill fewer people than a person. With self-driving cars, I think people kind of accept that now."
gambler 8y ago
>With self-driving cars, I think people kind of accept that now. That even if you don’t quite know how a self-driving car does it all, if it has a lot fewer accidents than a person-driven car then it’s a good thing. Unless there is a condition in the environment that causes a systemic failure involving large number of self-driving cars at the same time. This happens all the time with other types of software. People shouldn't assume that machine-learned models are magically different and ignore all common-sense rules we apply to safety-critical applications. In your daily job, would you be willing to bet your entire car on a black box piece of code that seems reliable, because it worked most of the time in the past? Also, recall that flash crash of the stock market. Imagine something like that, but with lots of cars on a highway. If you don't understand "how a self-driving car does it", you are unlikely to install appropriate safeguards. PS: Please don't insult your intelligence by replying that we don't understand how people drive either, so it makes any opaque self-driving software okay.
- donaldknuth123 8y ago
  Just look at the airline industry, planes are flown by software 90% of the time. Do you also worry about a global blackout of autopilot software? Seems like a silly thing to get stuck on. Our banking and electrical grid systems are far more prone to failure than anything built in SV.
- AndrewKemendo 8y ago
  This is a common conflation of intelligence evaluation criteria which is discussed in detail in Jose Hernandez-Orallo's 2017 book Measure of all minds. It can be simultaneously true that we cannot describe in a causally deterministic way how a system works while also determining with some confidence that the system is performing as desired. This is true of all human systems. So if you don't know how people drive, but have enough confidence to let them drive based on performance in evaluation scenarios, then similarly we should be able to let machines drive assuming they perform equally as well as humans over the same contexts without knowing how they drive either.
  - ddingus 8y ago
laythea 8y ago
"You should regulate them based on how they perform. You run the experiments to see if the thing’s biased, or if it is likely to kill fewer people than a person. With self-driving cars, I think people kind of accept that now" I don't. In my opinion, we are all getting carried away with ourselves. Google or not, I challenge anyone who makes a statement including the phrase "...more like brains", to define that statement accurately. In response, you will likely hear all sorts of things that sound like we know what we are doing and are very clever, but. If we can't even ask the questions properly, I doubt we will get deliberately valuable answers. Sure, we may luck out, with AI researchers stumbling across random combinations (layered AI) that do produce useful results hap-hazardly, but I would never rely on it. Eg. I rely on software running in an aircraft, because: a) it works, by design, not trial and error. b) it is verified. c) we know how it works. unless you have (c) you cannot achieve (b), with any degree of certainty. Experimenting until confident is not good enough for me for anything important. Brains fail at times. Computers should not make mistakes. Even if you knew how a brain works, and even if its possible to replicate it, please don't make computers like this. Software fails enough on its own without any help, even when we supposedly understand it. With this AI stuff, even if we knew where we are going, we don't know how to get there. And even if we did get there (wherever that is), in the long run, AI is not going to be used for the good. As always with humanity, we will find ways to use AI to extract value out of other people. This is what drives business. No thanks, but it is interesting for fluff. A bit too voodoo for me.
- modeless 8y ago
  > Brains fail at times. Computers should not make mistakes. I don't think this is a reasonable position to take. We are going to have to accept that if we want computers to do the things brains can do, they will also make mistakes like brains do sometimes. It's not reasonable to insist that the error rate is exactly zero. Besides, if you consider the computer as a complete system including the hardware and human-computer interface, it's clear that no complete system can ever be error-free, even if the CPU executes its instructions faultlessly. As long as it's as good or better than a human, it's good enough to be useful. Even with "fallible" AI techniques, we should be able to make systems that are much more reliable than humans.
0xdeadbeefbabe 8y ago
> GH: No, there's not going to be an AI winter, because it drives your cellphone. In the old AI winters, AI wasn't actually part of your everyday life. Now it is. Oh good; although, that predicament about publishing AI papers seems pretty bad.
- thanatropism 8y ago
  There's something interesting about AI winters: they begin with researchers claiming incremental science (say, heuristic tree search) as Whoa Artificial Intelligence and end up with some pretty complex technology totally taken for granted (car routing apps). In this cycle, we're in love with Computer Vision -- at the other end of the tunnel we might be stuck with omnipresent facial recognition and nada-de-nada of Jeff Hawkins and Ray Kurzweil's dreams.
KasianFranks 8y ago
One symbol: computational neuroscience
FigmentEngine 8y ago
brains don't think, minds do.
- thanatropism 8y ago
  Heck, brains might think but computers certainly do nothing of the sort.
- anonytrary 8y ago
  What does this even mean?
  - darkpuma 8y ago
    Presumably he's a dualist.
rdlecler1 8y ago
We place too much emphasis on learning and not enough on designing AI network topology. No matter how hard you try you’re not going to get a chimpanzee to write novels. They have different brain architectures.
sifoobar 8y ago
We do have some kind of shared understanding when it comes to humans though, especially within a culture and even more so within a limited context like driving a car. We don't generally expect someone to freak out and start treating a car in sunlight as a house because they've seen a lot of houses in sunlight lately. The difference between a human and ML is that a human has a clue, demanding perfect introspection is missing the point. This borders on dishonesty if you ask me, he should know better.
guicho271828 8y ago
So .. like human brains that chose a particular president?
YeGoblynQueenne 8y ago
>> People can’t explain how they work, for most of the things they do. When you hire somebody, the decision is based on all sorts of things you can quantify, and then all sorts of gut feelings. People have no idea how they do that. If you ask them to explain their decision, you are forcing them to make up a story. Manager: Why did you delete the production database in the middle of a work-day, no less? DBA: My decision was based on all sorts of things you can quantify, and then all sorts of gut feeling. I have no idea how I do that. Do not ask me to explain my decision, or you are forcing me to make up a story. Manager: But, you crashed our client's entire business for a whole day! DBA: I can't explain how I work. (Somehow, I don't see that flying.)
- smallnamespace 8y ago
  Nobody has perfect self knowledge, and yet in society we demand people explain and justify themselves, so some level of confabulation is unavoidable. I guess pointing that out while explaining yourself is a bad idea though.
mistrial9 8y ago
As a programmer, I find you faith in computers amusing

126 points by Osiris30 8y ago

Side comment: hacker news is known for having the ‘author here’ moments in threads. Has Professor Hinton ever made a known appearance on HN?

visarga 8y ago
I know Hinton participated in a few AMA sessions on reddit.

criddell 8y ago

> The brain is solving a very different problem from most of our neural nets. You’ve got roughly 100 trillion synapses. Hinton doesn't mention microtubules at all. Do any of the neural net or other connected neuron models incorporate the quantum vibration effects inside the neuron's microtubules?

daveguy 8y ago
Not a neurophysiologist. Can you point me to any controlled studies verifying this microtubule quantum effects? If not, a principle based description of the theory and hypothesized effects would be helpful too. Microtubule physiology characterization would also be good. Completely not up to date on neurophysiology so pretty much any references would help. Thanks in advance! Edit: Nevermind on microtubule resources. Plenty on the physiology references for those.
- criddell 8y ago
  The quantum vibrations might be crackpottery, but the microtubules might still be information carriers[1]. I'm still curious if any neural net models incorporate these paths. [1]: https://onlinelibrary.wiley.com/doi/pdf/10.1111/jnc.12621 https://onlinelibrary.wiley.com/doi/pdf/10.1111/jnc.12621
  - etiam 8y ago
    Nets used for practical machine learning today are too abstract to incorporate them in any meaningful way. When you reduce the whole "neuron" to a weighted sum wrapped by some nonlinear function, in discrete timesteps, you've killed so much structure in the modelling it doesn't matter if the original information transfer path was supposed to be by membrane depolarization or by modifying cytoskeleton strands. Arguably if there is a cytoskeleton mechanism for signalling or storage it's captured in some ways in changing the weights and evaluating the net, but not if it had any unique function beyond the abstraction which was already in place from the conventional view. Studying other structures than the synapses and membranes is prudent, but Hameroff must be somewhere on the line between crackpot and intellectual poseur. Use your time on some real science instead. Here's one option: http://www.gatsby.ucl.ac.uk/~lmate/biblio/dayanabbott.pdf http://www.gatsby.ucl.ac.uk/~lmate/biblio/dayanabbott.pdf
aaaaaaaaaab 8y ago
I thought quantum microtubules are still considered crackpottery.
- criddell 8y ago
  That could be. I'm the furthest thing from an expert in this.
- jostmey 8y ago
  They are
- codekilla 8y ago
  Stuart Hammeroff gave a talk here at Caltech about them last year.....which surprised me a bit. It is still considered far afield from mainstream neuroscience, however, quantum biology is something many are seriously thinking about.
- lenticular 8y ago
  There are definitely a few non-crackpots interested in quantum microtubules, but it seems very far from mainstream. It's conceivable that quantum effects could matter in some way on very small scales, and that doesn't really have anything to do with quantum mysticism.

xpuente 8y ago

The big question here is: How brains think?

paraschopra 8y ago
Active Inference is one possible hypothesis unifying different ideas on how brains think.

AndrewKemendo 8y ago

There's a logical inconsistency here: Statement 1:I’ve always been worried about potential misuses in lethal autonomous weapons. I think there should be something like a Geneva Convention banning them, like there is for chemical weapons. Statement 2: You should regulate them (AI) based on how they perform. You run the experiments to see if the thing’s biased, or if it is likely to kill fewer people than a person. The intention of utilizing AI in weapons systems is to reduce human error in their application. So is it unethical to implement an "AI" in a weapons system that kills fewer people than a person would? Seperately, I am curious why Hinton is not talking more about state representation and prediction, as almost uniformly across DL/RL researchers this is agreed upon as the next step forward. Hinton certainly is working with Richard Sutton on his RL programs at U Alberta. Sutton believes that the next step in AI systems is state representation and prediction and gave a quick talk on it recently [1]. [1] https://www.youtube.com/watch?v=6-Uiq8-wKrg https://www.youtube.com/watch?v=6-Uiq8-wKrg

b_tterc_p 8y ago
That feels like a question of decision making vs execution. I think most people would prefer we don’t let machines choose who to kill. We are probably ok with AI guided projectiles towards selected targets.
chongli 8y ago
The intention of utilizing AI in weapons systems is to reduce human error in their application. So is it unethical Reducing human error is one possible benefit of AI weapon systems but there are numerous drawbacks. AI weapons could be programmed to violate laws and commit atrocities on an incomprehensible scale. They could conceivably cause the extinction of human beings or even all life on the planet. They don't even need to be sentient, let alone super intelligent, to accomplish this. If they can be mass produced and armoured well enough to resist most small arms fire, they could easily overwhelm any human armies. The scariest part of the Terminator films is not Skynet, it's the terminators themselves and they're far more plausible than a godlike super-AI.
articwombat 8y ago
Statement 2 is not in regards to weapons systems. It is referencing things like self-driving cars. You can see that if you include the next sentence. "ou should regulate them based on how they perform. You run the experiments to see if the thing’s biased, or if it is likely to kill fewer people than a person. With self-driving cars, I think people kind of accept that now."

gambler 8y ago

>With self-driving cars, I think people kind of accept that now. That even if you don’t quite know how a self-driving car does it all, if it has a lot fewer accidents than a person-driven car then it’s a good thing. Unless there is a condition in the environment that causes a systemic failure involving large number of self-driving cars at the same time. This happens all the time with other types of software. People shouldn't assume that machine-learned models are magically different and ignore all common-sense rules we apply to safety-critical applications. In your daily job, would you be willing to bet your entire car on a black box piece of code that seems reliable, because it worked most of the time in the past? Also, recall that flash crash of the stock market. Imagine something like that, but with lots of cars on a highway. If you don't understand "how a self-driving car does it", you are unlikely to install appropriate safeguards. PS: Please don't insult your intelligence by replying that we don't understand how people drive either, so it makes any opaque self-driving software okay.

donaldknuth123 8y ago
Just look at the airline industry, planes are flown by software 90% of the time. Do you also worry about a global blackout of autopilot software? Seems like a silly thing to get stuck on. Our banking and electrical grid systems are far more prone to failure than anything built in SV.
AndrewKemendo 8y ago
This is a common conflation of intelligence evaluation criteria which is discussed in detail in Jose Hernandez-Orallo's 2017 book Measure of all minds. It can be simultaneously true that we cannot describe in a causally deterministic way how a system works while also determining with some confidence that the system is performing as desired. This is true of all human systems. So if you don't know how people drive, but have enough confidence to let them drive based on performance in evaluation scenarios, then similarly we should be able to let machines drive assuming they perform equally as well as humans over the same contexts without knowing how they drive either.
- ddingus 8y ago

laythea 8y ago

"You should regulate them based on how they perform. You run the experiments to see if the thing’s biased, or if it is likely to kill fewer people than a person. With self-driving cars, I think people kind of accept that now" I don't. In my opinion, we are all getting carried away with ourselves. Google or not, I challenge anyone who makes a statement including the phrase "...more like brains", to define that statement accurately. In response, you will likely hear all sorts of things that sound like we know what we are doing and are very clever, but. If we can't even ask the questions properly, I doubt we will get deliberately valuable answers. Sure, we may luck out, with AI researchers stumbling across random combinations (layered AI) that do produce useful results hap-hazardly, but I would never rely on it. Eg. I rely on software running in an aircraft, because: a) it works, by design, not trial and error. b) it is verified. c) we know how it works. unless you have (c) you cannot achieve (b), with any degree of certainty. Experimenting until confident is not good enough for me for anything important. Brains fail at times. Computers should not make mistakes. Even if you knew how a brain works, and even if its possible to replicate it, please don't make computers like this. Software fails enough on its own without any help, even when we supposedly understand it. With this AI stuff, even if we knew where we are going, we don't know how to get there. And even if we did get there (wherever that is), in the long run, AI is not going to be used for the good. As always with humanity, we will find ways to use AI to extract value out of other people. This is what drives business. No thanks, but it is interesting for fluff. A bit too voodoo for me.

modeless 8y ago
> Brains fail at times. Computers should not make mistakes. I don't think this is a reasonable position to take. We are going to have to accept that if we want computers to do the things brains can do, they will also make mistakes like brains do sometimes. It's not reasonable to insist that the error rate is exactly zero. Besides, if you consider the computer as a complete system including the hardware and human-computer interface, it's clear that no complete system can ever be error-free, even if the CPU executes its instructions faultlessly. As long as it's as good or better than a human, it's good enough to be useful. Even with "fallible" AI techniques, we should be able to make systems that are much more reliable than humans.

0xdeadbeefbabe 8y ago

> GH: No, there's not going to be an AI winter, because it drives your cellphone. In the old AI winters, AI wasn't actually part of your everyday life. Now it is. Oh good; although, that predicament about publishing AI papers seems pretty bad.

thanatropism 8y ago
There's something interesting about AI winters: they begin with researchers claiming incremental science (say, heuristic tree search) as Whoa Artificial Intelligence and end up with some pretty complex technology totally taken for granted (car routing apps). In this cycle, we're in love with Computer Vision -- at the other end of the tunnel we might be stuck with omnipresent facial recognition and nada-de-nada of Jeff Hawkins and Ray Kurzweil's dreams.

KasianFranks 8y ago

One symbol: computational neuroscience

FigmentEngine 8y ago

brains don't think, minds do.

thanatropism 8y ago
Heck, brains might think but computers certainly do nothing of the sort.
anonytrary 8y ago
What does this even mean?
- darkpuma 8y ago
  Presumably he's a dualist.

rdlecler1 8y ago

We place too much emphasis on learning and not enough on designing AI network topology. No matter how hard you try you’re not going to get a chimpanzee to write novels. They have different brain architectures.

sifoobar 8y ago

We do have some kind of shared understanding when it comes to humans though, especially within a culture and even more so within a limited context like driving a car. We don't generally expect someone to freak out and start treating a car in sunlight as a house because they've seen a lot of houses in sunlight lately. The difference between a human and ML is that a human has a clue, demanding perfect introspection is missing the point. This borders on dishonesty if you ask me, he should know better.

guicho271828 8y ago

So .. like human brains that chose a particular president?

YeGoblynQueenne 8y ago

>> People can’t explain how they work, for most of the things they do. When you hire somebody, the decision is based on all sorts of things you can quantify, and then all sorts of gut feelings. People have no idea how they do that. If you ask them to explain their decision, you are forcing them to make up a story. Manager: Why did you delete the production database in the middle of a work-day, no less? DBA: My decision was based on all sorts of things you can quantify, and then all sorts of gut feeling. I have no idea how I do that. Do not ask me to explain my decision, or you are forcing me to make up a story. Manager: But, you crashed our client's entire business for a whole day! DBA: I can't explain how I work. (Somehow, I don't see that flying.)

smallnamespace 8y ago
Nobody has perfect self knowledge, and yet in society we demand people explain and justify themselves, so some level of confabulation is unavoidable. I guess pointing that out while explaining yourself is a bad idea though.

mistrial9 8y ago

As a programmer, I find you faith in computers amusing