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Now this question clarifies why you think too much into simulating reality: http://en.wikipedia.org/wiki/Initial_condition http://en.wikipedia.org/wiki/Initial

Now this question clarifies why you think too much into simulating reality: http://en.wikipedia.org/wiki/Initial_condition http://en.wikipedia.org/wiki/Initial_condition look for nonlinearity EDIT: You can't simulate a brain without considering the quantum effects at atomic levels. You can't simulate quantum effects. QED.

zAy0LfpBZLC8mAC 12y ago
I wasn't asking for a random example of a system that I don't know the initial conditions of, but what specifically you meant when you tried to construct an argument for the impossibility of emulating a brain.
chriswarbo 12y ago
> You can't simulate a brain without considering the quantum effects at atomic levels. That's wild speculation. At the very finest level of detail, we can simulate a brain in this way. At the very coarsest level of detail, we can simulate it as a thermodynamic heat bath. The correct level of detail for the emergence of intelligent behaviour is likely somewhere in-between. > You can't simulate quantum effects. What? Of course you can! Classical computers take an exponential amount of time, but it's still a finite problem. The whole field of Computational Chemistry is based on simulating quantum effects!
- crististm 12y ago
  "The correct level of detail for the emergence of intelligent behaviour is likely somewhere in-between." I think this is your speculation. :) "Classical computers take an exponential amount of time" It is not a matter of time it takes to simulate, but of the details. You don't know which details matter and which don't. You don't know if you need infinite precision or you can stop at Plank's level. Thus, since you don't know a lot of things, you can't be sure that what you simulated was indeed the real thing or something that you imagined/theorized to be the real thing.
  - chriswarbo 12y ago
    > I think this is your speculation. :) True, but I'm hedging my bets ;) > You don't know if you need infinite precision or you can stop at Plank's[sic] level. Objectively: we know that infinite precision computation is no obstacle, since we can just do everything symbolically in proof-space rather than numerically in value-space. Whether we can call that "simulation" is a matter of semantics, but it's "only" an exponential slowdown. Empirically: we know that the Planck-level interactions have no observable effects on macro-scale phenomena. If they did, we wouldn't need to build particle accelerators! Brains do not exploit particle physics for their abilities; there is no point simulating at any scale lower than up/down quarks + electrons + photons. They don't even exploit nuclear physics; there's no point simulating at a scale below the atomic. Brains do exploit chemistry, so an atomically-precise simulation may be justified. Of course, that's only if we want a faithful simulation. There's nothing to say that protein-level simulations won't be perfectly fine, or even cell-level, if the relevant lower-level effects can be approximated. Some current approaches operate at the level of mini-columns, and work well on standard AI tasks like computer vision. These coarser-grained simulations are less precise than the finer-grained ones, but all that matters is that they exhibit intelligent behaviour (however we're defining it). Even if some atomic-level quirk were being exploited by biological brains, we may still be better off without it. Again, it's all a matter of resource usage (intelligence per CPU-second/GB/dollar/etc.). A coarse-grained simulation might not be as intelligent as a fine-grained simulation, but it will run much faster; instead of spending more resources to run the fine-grained simulation, why not spend those same resources running the coarse-grained simulation at faster than real-time, with a larger virtual brain?
  - zAy0LfpBZLC8mAC 12y ago
    "Thus, since you don't know a lot of things, you can't be sure that what you simulated was indeed the real thing or something that you imagined/theorized to be the real thing." That's a useless distinction as there is nothing where you could "know the real thing", you _always_ work with theories, without exceptions. When you take your first step out of bed in the morning, you don't know the _real_ behaviour of the floor (it's made of atoms, after all), you "only" use a relatively high-level theory of solid materials to predict that it will support you before you step onto it. There is no guarantee that that will work out, but there is fundamentally no way to do better than that, all of science works that way, _everything_ we know about the world is "a theory", even the atom theory is a theory, and the quantum theory is a theory, it's all about modeling as best as we can, none of it is "proven to be the real thing", and no scientist ever even tries to prove something to be "the ultimate reality", all that matters to science is to make models more precise, and to figure out what those models seem to be sufficiently precise to use for - and then use them, which we do very successfully indeed.
stephanfroede 12y ago
The conclusion is that you need the quantum "layer" to get a intelligent machine. Not the simulation of quants. Could be much easier than trying to simulate everything. Google tried to use DWave quantum computers for pattern matching in Google Glass. But there is a debate that DWave computers are really quantum computers, some say they are not quantum computers.
- crististm 12y ago
  You might not need the quantum layer, then again, it might be indispensable. The thing is: you don't know. And without considering all the effects you have at atomic and subatomic levels, you can't say that you simulated a brain. All you can say is that you simulated something that looks like a brain. Which is completely different.
mcguire 12y ago
"You can't simulate a brain without considering the quantum effects at atomic levels. You can't simulate quantum effects. QED." One of the neat side effects of using QM to counter determinism is that you go directly from "everything you do is predetermined" to "everything you do is essentially random". Cf. Bell's theorem. https://en.wikipedia.org/wiki/Bell%27s_theorem https://en.wikipedia.org/wiki/Bell%27s_theorem

zAy0LfpBZLC8mAC 12y ago

I wasn't asking for a random example of a system that I don't know the initial conditions of, but what specifically you meant when you tried to construct an argument for the impossibility of emulating a brain.

chriswarbo 12y ago

> You can't simulate a brain without considering the quantum effects at atomic levels. That's wild speculation. At the very finest level of detail, we can simulate a brain in this way. At the very coarsest level of detail, we can simulate it as a thermodynamic heat bath. The correct level of detail for the emergence of intelligent behaviour is likely somewhere in-between. > You can't simulate quantum effects. What? Of course you can! Classical computers take an exponential amount of time, but it's still a finite problem. The whole field of Computational Chemistry is based on simulating quantum effects!

crististm 12y ago
"The correct level of detail for the emergence of intelligent behaviour is likely somewhere in-between." I think this is your speculation. :) "Classical computers take an exponential amount of time" It is not a matter of time it takes to simulate, but of the details. You don't know which details matter and which don't. You don't know if you need infinite precision or you can stop at Plank's level. Thus, since you don't know a lot of things, you can't be sure that what you simulated was indeed the real thing or something that you imagined/theorized to be the real thing.
- chriswarbo 12y ago
  > I think this is your speculation. :) True, but I'm hedging my bets ;) > You don't know if you need infinite precision or you can stop at Plank's[sic] level. Objectively: we know that infinite precision computation is no obstacle, since we can just do everything symbolically in proof-space rather than numerically in value-space. Whether we can call that "simulation" is a matter of semantics, but it's "only" an exponential slowdown. Empirically: we know that the Planck-level interactions have no observable effects on macro-scale phenomena. If they did, we wouldn't need to build particle accelerators! Brains do not exploit particle physics for their abilities; there is no point simulating at any scale lower than up/down quarks + electrons + photons. They don't even exploit nuclear physics; there's no point simulating at a scale below the atomic. Brains do exploit chemistry, so an atomically-precise simulation may be justified. Of course, that's only if we want a faithful simulation. There's nothing to say that protein-level simulations won't be perfectly fine, or even cell-level, if the relevant lower-level effects can be approximated. Some current approaches operate at the level of mini-columns, and work well on standard AI tasks like computer vision. These coarser-grained simulations are less precise than the finer-grained ones, but all that matters is that they exhibit intelligent behaviour (however we're defining it). Even if some atomic-level quirk were being exploited by biological brains, we may still be better off without it. Again, it's all a matter of resource usage (intelligence per CPU-second/GB/dollar/etc.). A coarse-grained simulation might not be as intelligent as a fine-grained simulation, but it will run much faster; instead of spending more resources to run the fine-grained simulation, why not spend those same resources running the coarse-grained simulation at faster than real-time, with a larger virtual brain?
- zAy0LfpBZLC8mAC 12y ago
  "Thus, since you don't know a lot of things, you can't be sure that what you simulated was indeed the real thing or something that you imagined/theorized to be the real thing." That's a useless distinction as there is nothing where you could "know the real thing", you _always_ work with theories, without exceptions. When you take your first step out of bed in the morning, you don't know the _real_ behaviour of the floor (it's made of atoms, after all), you "only" use a relatively high-level theory of solid materials to predict that it will support you before you step onto it. There is no guarantee that that will work out, but there is fundamentally no way to do better than that, all of science works that way, _everything_ we know about the world is "a theory", even the atom theory is a theory, and the quantum theory is a theory, it's all about modeling as best as we can, none of it is "proven to be the real thing", and no scientist ever even tries to prove something to be "the ultimate reality", all that matters to science is to make models more precise, and to figure out what those models seem to be sufficiently precise to use for - and then use them, which we do very successfully indeed.

stephanfroede 12y ago

The conclusion is that you need the quantum "layer" to get a intelligent machine. Not the simulation of quants. Could be much easier than trying to simulate everything. Google tried to use DWave quantum computers for pattern matching in Google Glass. But there is a debate that DWave computers are really quantum computers, some say they are not quantum computers.

crististm 12y ago
You might not need the quantum layer, then again, it might be indispensable. The thing is: you don't know. And without considering all the effects you have at atomic and subatomic levels, you can't say that you simulated a brain. All you can say is that you simulated something that looks like a brain. Which is completely different.

mcguire 12y ago

"You can't simulate a brain without considering the quantum effects at atomic levels. You can't simulate quantum effects. QED." One of the neat side effects of using QM to counter determinism is that you go directly from "everything you do is predetermined" to "everything you do is essentially random". Cf. Bell's theorem. https://en.wikipedia.org/wiki/Bell%27s_theorem https://en.wikipedia.org/wiki/Bell%27s_theorem