If you read too much into supercomputing and think that they can simulate atoms, then go tell CERN to stop searching for sub-particles and simulate them instead.
Otherwise, I think you know what I mean. Besides, a real system depends on initial conditions. You can't simulate those.
1. We form a hypothesis about how something works.
2. We do experiments to try to falsify said hypothesis.
3. If a certain amount of experimentation fails to falsify the hypothesis, we conclude tentatively that the hypothesis is a correct model of reality, namely, we promote it to a theory.
4. We use that theory to simulate the real thing computationally.
(4) is the whole point of doing steps (1) to (3) - and all VMG is saying is that there is no reason to assume that (1) to (3) couldn't lead to (4) with regards to the brain, just as there is no reason to do so with regards to atoms, which in turn is why we do operate CERN instead of just asserting that atoms cannot be understood.
You don't know the initial conditions which are a _huge_ part in determining the outcome of the simulation. Maybe you will limit your precision to Plank constant. Can you measure with that precision?
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.
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!
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.
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.
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?
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.
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.
They can't run simulations instead of their experiments, since they're looking for new fundamental Physics; in other words, they're trying to find out which of their simulations describes the world best.
AI research isn't looking for fundamental results; we have a good theory of computation, and a good-enough theory of Physics to describe our brains. We know which simulation to run. The remaining problems are 'only' to do with resource usage: which computations/arrangements-of-atoms can give us good-enough results in short-enough time?
If we could efficiently run O(2^n) algorithms, AI would be unnecessary; we could just brute-force everything (including brain emulation).
The reason CERN has built a 27km, 14TeV, super-cooled, superconducting magnetic particle collider is because we know so much about fundamental Physics that it takes something really crazy, like the LHC, running billions of collisions, in order to find something which we might find surprising. So far, it's not surprised us; although it has confirmed the ideas Peter Higgs developed 50 years ago.
Of course, there is still debate and surprise to be had in other, non-fundamental areas; yet these are studying the consequences of the fundamental laws (they're debating the output of a simulation, not its code).
You can stop higher than atoms anytime you think the result satisfies your experimental measurements.
It seemed to me that your argument was "There are details of how an atom works that we currently don't know how to simulate. A brain's behaviour is a result of the behaviour of the atoms it consists of. Therefore, it's impossible to simulate a brain to any degree of accuracy at all."
Using the same logic, and given that most everything we interact with is made of atoms, one could deduce that it's impossible to simulate anything at all, except for electron beams, maybe. That seems to me to be obviously in contradiction to how well we can navigate and manipulate the world in our day-to-day lives (let alone in engineering), which depends on us simulating the world all the time, at least to some degree.
Now, I'd be interested in understanding how you reconcile that.
People use that to extrapolate in the other direction, and assume that because Newton's laws can be simulated, you can simulate an atom, thus everything. We don't have a view of reality at subatomic levels that says: "this is it and there's nothing beyond it". You don't know if your simulation of a brain will show an emergent intelligence if simulated with 'float', 'double' or 'infinite'.
Just a baseless assertion without any evidence.
There is no reason to assume you couldn't build a system that emulates whatever the human brain is doing there.