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This is a bad title, it should be "Where will advances in AI come from now?", In the first paragraph, the author states that AI is here, but asks where new AI a

by Balgair 10y ago

This is a bad title, it should be "Where will advances in AI come from now?", In the first paragraph, the author states that AI is here, but asks where new AI advances will be from. On that, in 2, the author talks about Brain Simulations and states that it'll take up to 500 years. I think that is a good upper estimate actually. Though optogenetics is a great tool, we need more. Mammalian brains can be up to 50% (at the low estimate, some say 90%) made out of astrocytes and glia. We know pretty much nothing about how they affect neuro processes, outside that they do, sometimes. We do know that is a huge problem with our understanding though, which is something I guess. Optogenetics should help tease out some of those glia methods, but as usual, it will raise more questions than answers. Another issue is potentation and its molecular mechanisms in more than just the hippocampus. That work is incredibly tough, but we really only focus on the anatomically 'easy' areas for memory. We have to do more to understand. In short, we don't even know the correct questions to ask when it comes to the brain and understanding it. A full simulation, or a '80%' approximation even, is a few paradigm shifts away still (maybe, we cant know yet). It will likely have to be a 'full world' simulation too, where you have to control all the inputs to the brain and therefore have to model a world first. The brain's best feature is that it is all connected and a giant spaghetti mess. This is, obviously, a long ways away.

JoeAltmaier 10y ago
A hard problem to be sure. But much of a human brain is a uniform matrix that self-programs. If we duplicate that blindly, we won't have to figure out how that works or have to program it. Still a lot to do before that I guess. But 500 years? What else in human history has taken that long to figure out? The age of technology is shorter than that.
- dmd 10y ago
  > But much of a human brain is a uniform matrix that self-programs. Speaking as a neuroscience PhD ... no. Not remotely close, sorry.
  - JoeAltmaier 10y ago
    The cortex? How would you describe it then? There are not enough genes in our genome to wire every connection, so self-organizing.
    - tormeh 10y ago
      The visual system is basically a deep neural net of the type we are already building, but it's self-contained. Generally it seems like our brain is composed of a lot of fixed-function neural nets (and other algorithms) which are then integrated by less specialized units. That's my impression anyway. I think maybe our artificial visual nets are too general, actually, in comparison to natural ones. It not only describes what it sees, but tries to analyze it too. Showing a picture of a dog results in "dog", rather than "big four-legged furry thing". Expecting a visual system to know that a chihuahua and a German shepherd is the same thing is maybe a case of grouping tasks that shouldn't be grouped.
      - sounds 10y ago
        In order to build an artificial visual system, humans must grasp what their own visual system does. In order to describe what the human visual system does we use words like "dog" -- and I would agree with you, "big four-legged furry mammal" might be better, but artificial visual systems work more at the level of "80% probability of dog," "2% probability of brick," "90% probability of chihuahua," and they don't really know that chihuahua must always imply dog. In order to describe the function of the visual system, a fundamental change really must happen in the way the system's output is described. Using plain written words as output may work as a system but it is not an exact replica of a human visual system. It is more of a trained animal act: when you see dog-like images, press the button labelled "dog" (does the animal even comprehend what a dog is?) In order to rethink the way we describe output, we will have to come up with a very precise description of the inside potentials and activations in mammalian brains. We are just barely creating tools to describe what an artificial neural net "is thinking." So I guess we're starting to look in that direction.
    - LeifCarrotson 10y ago
- damptowel 10y ago
  > If we duplicate that blindly, we won't have to figure out how that works or have to program it. ...said every failed AI researcher ever.
  - sgt101 10y ago
    Well, and probably all the ones that are still working (I won't say succeeded). It's part of the journey I guess!
- JackFr 10y ago
  What typically happens is that after a few hundred years, people realize that the questions that prior generations were asking were laughably wrong.
- sangnoir 10y ago
  > But 500 years? What else in human history has taken that long to figure out? Powered, heavier than air flight falls into that ball park. da Vinci was making doodles in the (late) 15th century, but this was only accomplished by the Wright brothers in the (early) 20th century. Edit: After additional research, I discovered that recorded attempts at manned flight can be found as far back as the 11th[1] century! So it took roughly 700 years to figure out, if not longer as earlier attempts were likely not recorded. 1. https://en.wikipedia.org/wiki/Ornithopter https://en.wikipedia.org/wiki/Ornithopter
  - sounds 10y ago
    Interestingly the challenge was finding a power source with enough thrust-to-weight for power flight. Heavier-than-air flight can be decomposed into "power source," "stability of design," and maybe "scale". So for instance, Da Vinci came up with pretty good designs for heavier-than-air unpowered flight. Our current decomposition of mammalian intelligence seems somewhat weak in comparison: we've divided the mammal brain into regions, yes, but we still haven't made an accurate simulation at the electrochemical level of a functioning mammalian brain. That's not to say nobody has or is trying, only that our simulations are more like approximations at present. They also don't have good simulations of astrocytes and glia.
- the_af 10y ago
  > If we duplicate that blindly, we won't have to figure out how that works or have to program it. Genuine question: what would be the value of blindly duplicating a brain without figuring out how it works (and as a consequence, without knowing how to change/improve how it works)? After all, we already know how to create human brains, and it doesn't involve tech at all :)
  - sgt101 10y ago
    Also that process can be a great deal of fun!
  - roywiggins 10y ago
    You can take that artificial brain and run it at twice the speed, hook it up to the internet, reset it when it goes insane, etc. A lot of mad scientist options that aren't possible with human brains.
    - the_af 10y ago
      Maybe, but I'm not entirely convinced. If it's blind duplication, what have you learned from it? How would you know how to reset it or speed it up, if you don't understand how it works? We don't know how to reset human brains. Also, blindly duplicating a human brain would raise serious ethical implications, especially if you intend to perform experiments on it. If it's clearly an appliance which only superficially resembles a human brain, I don't see the problem. If it was created blindly, and you're unsure how much it differs from a child's brain, would you cut it open, hook it to the internet or reset it at will?
      - kamaal 10y ago
        Any duplicated human brain to which you can provide even the most basic sensory inputs like pain, is equivalent to torturing a real human.. I don't think these sort of experiments should be allowed.
- elorant 10y ago
  The Antikythera mechanism was invented somewhere between 205 BC and 100 BC. And yet it took us more than one and a half millennia to get to the first mechanical astronomical clocks.
- freyir 10y ago
  > But 500 years? What else in human history has taken that long to figure out? Calculus took a few thousand years to figure out.
- tajen 10y ago
  Other inventions that have taken 500 years are not comparable: We're now 7bn people whereas the total number of people since the beginning of Earth is ~100bn. That means research can advance as much in 1 generation as it advanced in a thousand years, and it's accelerated by 1/a much greater proportion of people who can do research full time compared to <1% at the time of Da Vinci, and 2/greater access to better tools.
- tajen 10y ago
  Other inventions that have taken 500 years are not comparable: We're now 7bn people whereas the total number of people since the beginning of Earth is ~100bn. That means research can advance as much in 1 generation as it advanced in a thousand years, and it's accelerated by 1/a much greater proportion of people who can do research full time compared to <1% at the time of Da Vinci, and 2/greater access to better tools.
ThomPete 10y ago
But isn't that the wrong premise? Our brains emerged without a designer or an undertanding of how the brain works (I assume you don't believe in god) from simple principles and through the evolutionary process. Why do we need to understand the brain for brain simulation to happen? I don't know how long it will take but I don't understand any claims about how long it will take. It can be forever or it can be in a couple of years depending on what we uncover. For all we know our giant network of computers and sensor are already kind of a brain simulation.
- akiselev 10y ago
  The evolutionary process took billions of years (hundreds of millions for the mammalian brain to be specific) so even though we're intelligent designers we don't quite have a precise concept of what intelligence is let alone know how to implement it. We don't know what data structures or processes make true human intelligence so while it's possible we stumble on our own version, working with what we already have as a baseline seems far more practical.
  - ThomPete 10y ago
    Only if what you set it as criteria to understand the brain you are simulating, it might be that the brain can be simulated without us knowing how. The evolutionary process can be simulated or replicated in digital space and go through iterations much faster no?
    - unabst 10y ago
      To engineer anything, we need to understand it. The options you are weighing are between understanding the brain so we can write programs that run on robots that would exhibit human-like behavior, and understanding the nature of organic evolution to the point where we could simulate every organism's survival and death that lead to the autonomous design and formation of the human brain. To estimate engineer-ability requires understanding also, but I think we understand enough to know simulating the whole of evolution is not an easier problem.
3pt14159 10y ago
If what you are saying is true, then sentient AI will almost certainly come out of cellular automation far far sooner than from accurate simulation of organic matter. Though I can't pin down exactly why, this makes me much more certain that we live in a simulation. Perhaps it's the automata-like nature of quantum physics.
- zardo 10y ago
  If there is life in cellular automata, is it brought to life by symbolically representing it with voltage differences in a computer, or is it alive whether we run the simulation or not? I think the second makes more sense, the implication is that a simulation world need not be simulated at all. It's just as real inside if it isn't symbolically represented somewhere else as if it is, and ending the calculation of state transitions doesn't change what the next state is.
  - 3pt14159 10y ago
    Especially with things like Hash Life. It really bleeds across into philosophy. This concept is explored in a book I recently recommended on HN. Permutation City. You'd probably get a kick out of it.
  - jjoonathan 10y ago
    If I can't interact with it, whether I think it is alive or not is moot, and it might make sense to capture that fact in the definition.
    - zardo 10y ago
      In the definition of life? I'm not sure... It seems like a very anthropocentric definition. Isn't it enough to observe it interacting with the things it can interact with, and base the level of aliveness on that?
      - jjoonathan 10y ago
        Definitions exist to serve us, not the other way around, so anthropocentricity isn't exactly a sin. If we base our definition of life on observed interactions, we reacquire the same problems we had before, where we have difficulty deciding whether or not deceased ancestors / fictional characters / miscellaneous accidental Turing machines are alive. To be sure, a restricted subset of observed interactions are good proxies for determining life: if I see a bird interacting with a worm outside the window, it's a good bet that I could get up and scare it off / put out birdseed / etc, but I'd argue that if you tease out the restrictions required to define the subset of observed interactions that constitute life you're liable to find yourself right back at the interaction definition.
erikpukinskis 10y ago
Simulating a brain doesn't give you general purpose AI. Brains are useless. You can get one pretty easily, but what would you do with it? A brain without a body wouldn't be intelligent at all. So, ok, shift the goalposts to simulating a brain and a body. But that's not particularly intelligent either. If you dropped an adult human in the vacuum of space (with life support) nothing particularly intelligent would happen either. Ok, well shift the goalposts to simulating a brain and a body and an environment for it to live in. Still won't be intelligent. Humans raised without any socialization have serious cognitive defects. Not really "intelligent" for our purposes. Well, so simulate a brain in a body and a social environment. No we've introduced a chicken and egg problem. Maybe you give the AI a robot body and allow it to live amongst humans. That would work, and also removes the need to simulate the environment. A huge win. But is that any different than a human human? Ok, you want this virtual brain to be way bigger... 100x the neurons of a human. But still with the human body and socialization. How is that different than a human with a cloud-connected smartphone? Right, bandwidth. Elon musk says a smartphone doesn't have enough bandwidth and we need a BCI. But raw UI bandwidth doesn't seem tk have increased for a couple decades now. Smartphones actually have less bandwidth than laptops. But we keep being able to do more and more with better software. Is bandwidth really the limitation? And if bandwidth isn't the limitation, does an AI really have an advantage over a cloud-augmented human brain?

by Balgair 10y ago

JoeAltmaier 10y ago

A hard problem to be sure. But much of a human brain is a uniform matrix that self-programs. If we duplicate that blindly, we won't have to figure out how that works or have to program it. Still a lot to do before that I guess. But 500 years? What else in human history has taken that long to figure out? The age of technology is shorter than that.

dmd 10y ago
> But much of a human brain is a uniform matrix that self-programs. Speaking as a neuroscience PhD ... no. Not remotely close, sorry.
- JoeAltmaier 10y ago
  The cortex? How would you describe it then? There are not enough genes in our genome to wire every connection, so self-organizing.
  - tormeh 10y ago
    The visual system is basically a deep neural net of the type we are already building, but it's self-contained. Generally it seems like our brain is composed of a lot of fixed-function neural nets (and other algorithms) which are then integrated by less specialized units. That's my impression anyway. I think maybe our artificial visual nets are too general, actually, in comparison to natural ones. It not only describes what it sees, but tries to analyze it too. Showing a picture of a dog results in "dog", rather than "big four-legged furry thing". Expecting a visual system to know that a chihuahua and a German shepherd is the same thing is maybe a case of grouping tasks that shouldn't be grouped.
    - sounds 10y ago
      In order to build an artificial visual system, humans must grasp what their own visual system does. In order to describe what the human visual system does we use words like "dog" -- and I would agree with you, "big four-legged furry mammal" might be better, but artificial visual systems work more at the level of "80% probability of dog," "2% probability of brick," "90% probability of chihuahua," and they don't really know that chihuahua must always imply dog. In order to describe the function of the visual system, a fundamental change really must happen in the way the system's output is described. Using plain written words as output may work as a system but it is not an exact replica of a human visual system. It is more of a trained animal act: when you see dog-like images, press the button labelled "dog" (does the animal even comprehend what a dog is?) In order to rethink the way we describe output, we will have to come up with a very precise description of the inside potentials and activations in mammalian brains. We are just barely creating tools to describe what an artificial neural net "is thinking." So I guess we're starting to look in that direction.
  - LeifCarrotson 10y ago
damptowel 10y ago
> If we duplicate that blindly, we won't have to figure out how that works or have to program it. ...said every failed AI researcher ever.
- sgt101 10y ago
  Well, and probably all the ones that are still working (I won't say succeeded). It's part of the journey I guess!
JackFr 10y ago
What typically happens is that after a few hundred years, people realize that the questions that prior generations were asking were laughably wrong.
sangnoir 10y ago
> But 500 years? What else in human history has taken that long to figure out? Powered, heavier than air flight falls into that ball park. da Vinci was making doodles in the (late) 15th century, but this was only accomplished by the Wright brothers in the (early) 20th century. Edit: After additional research, I discovered that recorded attempts at manned flight can be found as far back as the 11th[1] century! So it took roughly 700 years to figure out, if not longer as earlier attempts were likely not recorded. 1. https://en.wikipedia.org/wiki/Ornithopter https://en.wikipedia.org/wiki/Ornithopter
- sounds 10y ago
  Interestingly the challenge was finding a power source with enough thrust-to-weight for power flight. Heavier-than-air flight can be decomposed into "power source," "stability of design," and maybe "scale". So for instance, Da Vinci came up with pretty good designs for heavier-than-air unpowered flight. Our current decomposition of mammalian intelligence seems somewhat weak in comparison: we've divided the mammal brain into regions, yes, but we still haven't made an accurate simulation at the electrochemical level of a functioning mammalian brain. That's not to say nobody has or is trying, only that our simulations are more like approximations at present. They also don't have good simulations of astrocytes and glia.
the_af 10y ago
> If we duplicate that blindly, we won't have to figure out how that works or have to program it. Genuine question: what would be the value of blindly duplicating a brain without figuring out how it works (and as a consequence, without knowing how to change/improve how it works)? After all, we already know how to create human brains, and it doesn't involve tech at all :)
- sgt101 10y ago
  Also that process can be a great deal of fun!
- roywiggins 10y ago
  You can take that artificial brain and run it at twice the speed, hook it up to the internet, reset it when it goes insane, etc. A lot of mad scientist options that aren't possible with human brains.
  - the_af 10y ago
    Maybe, but I'm not entirely convinced. If it's blind duplication, what have you learned from it? How would you know how to reset it or speed it up, if you don't understand how it works? We don't know how to reset human brains. Also, blindly duplicating a human brain would raise serious ethical implications, especially if you intend to perform experiments on it. If it's clearly an appliance which only superficially resembles a human brain, I don't see the problem. If it was created blindly, and you're unsure how much it differs from a child's brain, would you cut it open, hook it to the internet or reset it at will?
    - kamaal 10y ago
      Any duplicated human brain to which you can provide even the most basic sensory inputs like pain, is equivalent to torturing a real human.. I don't think these sort of experiments should be allowed.
elorant 10y ago
The Antikythera mechanism was invented somewhere between 205 BC and 100 BC. And yet it took us more than one and a half millennia to get to the first mechanical astronomical clocks.
freyir 10y ago
> But 500 years? What else in human history has taken that long to figure out? Calculus took a few thousand years to figure out.
tajen 10y ago
Other inventions that have taken 500 years are not comparable: We're now 7bn people whereas the total number of people since the beginning of Earth is ~100bn. That means research can advance as much in 1 generation as it advanced in a thousand years, and it's accelerated by 1/a much greater proportion of people who can do research full time compared to <1% at the time of Da Vinci, and 2/greater access to better tools.
tajen 10y ago
Other inventions that have taken 500 years are not comparable: We're now 7bn people whereas the total number of people since the beginning of Earth is ~100bn. That means research can advance as much in 1 generation as it advanced in a thousand years, and it's accelerated by 1/a much greater proportion of people who can do research full time compared to <1% at the time of Da Vinci, and 2/greater access to better tools.

ThomPete 10y ago

But isn't that the wrong premise? Our brains emerged without a designer or an undertanding of how the brain works (I assume you don't believe in god) from simple principles and through the evolutionary process. Why do we need to understand the brain for brain simulation to happen? I don't know how long it will take but I don't understand any claims about how long it will take. It can be forever or it can be in a couple of years depending on what we uncover. For all we know our giant network of computers and sensor are already kind of a brain simulation.

akiselev 10y ago
The evolutionary process took billions of years (hundreds of millions for the mammalian brain to be specific) so even though we're intelligent designers we don't quite have a precise concept of what intelligence is let alone know how to implement it. We don't know what data structures or processes make true human intelligence so while it's possible we stumble on our own version, working with what we already have as a baseline seems far more practical.
- ThomPete 10y ago
  Only if what you set it as criteria to understand the brain you are simulating, it might be that the brain can be simulated without us knowing how. The evolutionary process can be simulated or replicated in digital space and go through iterations much faster no?
  - unabst 10y ago
    To engineer anything, we need to understand it. The options you are weighing are between understanding the brain so we can write programs that run on robots that would exhibit human-like behavior, and understanding the nature of organic evolution to the point where we could simulate every organism's survival and death that lead to the autonomous design and formation of the human brain. To estimate engineer-ability requires understanding also, but I think we understand enough to know simulating the whole of evolution is not an easier problem.

3pt14159 10y ago

If what you are saying is true, then sentient AI will almost certainly come out of cellular automation far far sooner than from accurate simulation of organic matter. Though I can't pin down exactly why, this makes me much more certain that we live in a simulation. Perhaps it's the automata-like nature of quantum physics.

zardo 10y ago
If there is life in cellular automata, is it brought to life by symbolically representing it with voltage differences in a computer, or is it alive whether we run the simulation or not? I think the second makes more sense, the implication is that a simulation world need not be simulated at all. It's just as real inside if it isn't symbolically represented somewhere else as if it is, and ending the calculation of state transitions doesn't change what the next state is.
- 3pt14159 10y ago
  Especially with things like Hash Life. It really bleeds across into philosophy. This concept is explored in a book I recently recommended on HN. Permutation City. You'd probably get a kick out of it.
- jjoonathan 10y ago
  If I can't interact with it, whether I think it is alive or not is moot, and it might make sense to capture that fact in the definition.
  - zardo 10y ago
    In the definition of life? I'm not sure... It seems like a very anthropocentric definition. Isn't it enough to observe it interacting with the things it can interact with, and base the level of aliveness on that?
    - jjoonathan 10y ago
      Definitions exist to serve us, not the other way around, so anthropocentricity isn't exactly a sin. If we base our definition of life on observed interactions, we reacquire the same problems we had before, where we have difficulty deciding whether or not deceased ancestors / fictional characters / miscellaneous accidental Turing machines are alive. To be sure, a restricted subset of observed interactions are good proxies for determining life: if I see a bird interacting with a worm outside the window, it's a good bet that I could get up and scare it off / put out birdseed / etc, but I'd argue that if you tease out the restrictions required to define the subset of observed interactions that constitute life you're liable to find yourself right back at the interaction definition.

erikpukinskis 10y ago

Simulating a brain doesn't give you general purpose AI. Brains are useless. You can get one pretty easily, but what would you do with it? A brain without a body wouldn't be intelligent at all. So, ok, shift the goalposts to simulating a brain and a body. But that's not particularly intelligent either. If you dropped an adult human in the vacuum of space (with life support) nothing particularly intelligent would happen either. Ok, well shift the goalposts to simulating a brain and a body and an environment for it to live in. Still won't be intelligent. Humans raised without any socialization have serious cognitive defects. Not really "intelligent" for our purposes. Well, so simulate a brain in a body and a social environment. No we've introduced a chicken and egg problem. Maybe you give the AI a robot body and allow it to live amongst humans. That would work, and also removes the need to simulate the environment. A huge win. But is that any different than a human human? Ok, you want this virtual brain to be way bigger... 100x the neurons of a human. But still with the human body and socialization. How is that different than a human with a cloud-connected smartphone? Right, bandwidth. Elon musk says a smartphone doesn't have enough bandwidth and we need a BCI. But raw UI bandwidth doesn't seem tk have increased for a couple decades now. Smartphones actually have less bandwidth than laptops. But we keep being able to do more and more with better software. Is bandwidth really the limitation? And if bandwidth isn't the limitation, does an AI really have an advantage over a cloud-augmented human brain?