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This is complete fantasy unfortunately. They make this sound like AI is just a hardware problem, waiting to be solved by the wonder of Moore's Law. It's not.

This is complete fantasy unfortunately. They make this sound like AI is just a hardware problem, waiting to be solved by the wonder of Moore's Law. It's not. The human brain has 100 billion neurons, and 100 trillion synapses (wikipedia) - but it is the connections between them that make it do what it does. The possible connections are just mind boggling. Let's say you build hardware with those numbers (utterly non-trivial) - how does it connect together? How to we get it to structure in a way that those networks do anything? You can't expect it to wire itself into anything useful. We have no idea how the brain does anything of significance (merging of senses into a coherent whole; memory; consciousness etc). We can't even define consciousness let alone understand how it comes about. We can't 'program' a neural network of any complexity. Even things that we take utterly for granted like object recognition is immensely complicated, let alone things that we know are 'difficult' like sentience. We can't expect this stuff to magically appear from a large neural network; nor can we program it (as we don't understand it); nor can we train it as we don't know what intermediate steps to train for. Then, what are the inputs into it (and how are those interpreted by the hardware), and how do we get any output out of it? Let's say you solve both the hardware and the wiring problem - so you have a perfect replica human brain in a jar - how do you tell it what to do? How do you get any sense out of it? We're fumbling in the dark here. To think those fumbles will achieve intelligence in any form in the foreseeable future is unfortunately fantasy.

a-priori 16y ago
This article is fluff, yes, but the subject matter is not. 1) Understanding brain function is, of course, not strictly a hardware problem, but right now hardware is the bottleneck to progress. 2) Of course the brain is complex, but it is not incomprehensibly so. The neural structure has hierarchy: cells wire into microcircuits, which combine into mini-columns, which combine into columns. These neocortical columns are more or less repeated across the surface of the cortex. The brain is not just a jumble of cells. It's Markram's hypothesis that this is a tractable problem: understand each of the bits (ion channels, dendritic arbors, gene expression, etc.), understand how they're put together, run it through a massive supercomputer, and you've simulated a brain. Moreover, if you've done it right, that simulation should behave similarly to a biological brain. I think he's optimistic on the time scale, but I think he's within an order of magnitude and I agree his approach is sound. 3) Pretty much everything about the brain is an emergent property. As an example, the Blue Brain Project's neocortical column simulation shows alpha wave-like oscillations (private corresponence; but I believe Markram mentioned this in his TED lecture). Nowhere is there a cell ticking at 8-12Hz to create the waves. The oscillations emerge because the cells spontaneously synchronize at that frequency. 4) We can't define consciousness because it's an ill-posed question. Common definitions rest on the everyday experience of the 'ghost in the machine', when in reality that experience is an illusion of coherency created by our brains to help make sense of itself and the world. If there's one thing cognitive and neural science has shown over the past several decades, it's how small the domain of the unknowable consciousness is. Take the work of Gazzaniga, 1998, on split brain patients, as described in the book Brain fiction (page 154, starting from the top): http://books.google.ca/books?id=_rkKxbevFZEC&lpg=PP1&ots=9gZT3BFmNq&dq=split%20brain%20confabulation&pg=PA154#v=onepage&q=split%20brain%20confabulation&f=false http://books.google.ca/books?id=_rkKxbevFZEC&lpg=PP1&#38... Et cetera.
Jach 16y ago
Admitting that the problem is hard is important but not very helpful for actually solving the problem. Are you trying to discourage people from trying to solve it? Why, when the benefits should they succeed are astronomical? I agree that a lot of people have rosy-eyed views of an AI future, even ignoring the entire problem of Friendly AI, but why are you attacking them by just stating the difficulty of the problem instead of trying to suggest solutions? Hell, you could even donate some money to the people who do pay attention to the problems: http://www.singinst.org/ http://www.singinst.org/ I don't know how accurate all of your "we" statements are, I'd bet at least one of them is wrong or will be wrong in the near future, considering there's about 7 billion of us and I doubt you've polled us all.
- simonsquiff 16y ago
  >Are you trying to discourage people from trying to solve it? Not at all, the complete opposite. It's a fascinating area but I feel the expectations are completely out of whack with reality. Most of the articles like this have people saying we're only a decade or two away from proper AI, when I'm arguing that that is just not backed up at all - and people are underestimating what work is involved here. When expectations are set wrong, and people eventually realise it, it can damage research in this area as people don't take it seriously any more. Ref the'AI Winter' - the dramatic cut in funding when governments realised most of the experts in the field had massively over-promised and under-delivered. I think we need to break this down into smaller chunks of bounded problems. There is some amazing research around using human like neural networks and similar processes steps for machine vision - e.g. for object recognition, trying to mimic what happens in nature. This is greatly achievable. Trying to model the entire human brain, with talk about how this will lead in the near future to intelligent, reasoning - even sentient AI - is fun but for the reasons I outlined needs an expectation reboot.
gizmo 16y ago
We're fumbling in the dark here, but that doesn't mean that we can't be close to a major breakthrough. > We can't expect this stuff [sentience/consciousness] to magically appear from a large neural network I actually expect those things to magically appear. If you have a functioning brain in a jar it should "come to life" automatically, because it's a reasoning machine. It reasons, therefore it becomes conscious. Just as byproduct of its complexity.

a-priori 16y ago

This article is fluff, yes, but the subject matter is not. 1) Understanding brain function is, of course, not strictly a hardware problem, but right now hardware is the bottleneck to progress. 2) Of course the brain is complex, but it is not incomprehensibly so. The neural structure has hierarchy: cells wire into microcircuits, which combine into mini-columns, which combine into columns. These neocortical columns are more or less repeated across the surface of the cortex. The brain is not just a jumble of cells. It's Markram's hypothesis that this is a tractable problem: understand each of the bits (ion channels, dendritic arbors, gene expression, etc.), understand how they're put together, run it through a massive supercomputer, and you've simulated a brain. Moreover, if you've done it right, that simulation should behave similarly to a biological brain. I think he's optimistic on the time scale, but I think he's within an order of magnitude and I agree his approach is sound. 3) Pretty much everything about the brain is an emergent property. As an example, the Blue Brain Project's neocortical column simulation shows alpha wave-like oscillations (private corresponence; but I believe Markram mentioned this in his TED lecture). Nowhere is there a cell ticking at 8-12Hz to create the waves. The oscillations emerge because the cells spontaneously synchronize at that frequency. 4) We can't define consciousness because it's an ill-posed question. Common definitions rest on the everyday experience of the 'ghost in the machine', when in reality that experience is an illusion of coherency created by our brains to help make sense of itself and the world. If there's one thing cognitive and neural science has shown over the past several decades, it's how small the domain of the unknowable consciousness is. Take the work of Gazzaniga, 1998, on split brain patients, as described in the book Brain fiction (page 154, starting from the top): http://books.google.ca/books?id=_rkKxbevFZEC&lpg=PP1&ots=9gZT3BFmNq&dq=split%20brain%20confabulation&pg=PA154#v=onepage&q=split%20brain%20confabulation&f=false http://books.google.ca/books?id=_rkKxbevFZEC&lpg=PP1&#38... Et cetera.

Jach 16y ago

Admitting that the problem is hard is important but not very helpful for actually solving the problem. Are you trying to discourage people from trying to solve it? Why, when the benefits should they succeed are astronomical? I agree that a lot of people have rosy-eyed views of an AI future, even ignoring the entire problem of Friendly AI, but why are you attacking them by just stating the difficulty of the problem instead of trying to suggest solutions? Hell, you could even donate some money to the people who do pay attention to the problems: http://www.singinst.org/ http://www.singinst.org/ I don't know how accurate all of your "we" statements are, I'd bet at least one of them is wrong or will be wrong in the near future, considering there's about 7 billion of us and I doubt you've polled us all.

simonsquiff 16y ago
>Are you trying to discourage people from trying to solve it? Not at all, the complete opposite. It's a fascinating area but I feel the expectations are completely out of whack with reality. Most of the articles like this have people saying we're only a decade or two away from proper AI, when I'm arguing that that is just not backed up at all - and people are underestimating what work is involved here. When expectations are set wrong, and people eventually realise it, it can damage research in this area as people don't take it seriously any more. Ref the'AI Winter' - the dramatic cut in funding when governments realised most of the experts in the field had massively over-promised and under-delivered. I think we need to break this down into smaller chunks of bounded problems. There is some amazing research around using human like neural networks and similar processes steps for machine vision - e.g. for object recognition, trying to mimic what happens in nature. This is greatly achievable. Trying to model the entire human brain, with talk about how this will lead in the near future to intelligent, reasoning - even sentient AI - is fun but for the reasons I outlined needs an expectation reboot.

gizmo 16y ago

We're fumbling in the dark here, but that doesn't mean that we can't be close to a major breakthrough. > We can't expect this stuff [sentience/consciousness] to magically appear from a large neural network I actually expect those things to magically appear. If you have a functioning brain in a jar it should "come to life" automatically, because it's a reasoning machine. It reasons, therefore it becomes conscious. Just as byproduct of its complexity.