Re:Robots Can’t Dance: Why the singularity is greatly exagge...
by chriswarbo on Tuesday January 27, 2015 @06:52AM
(#8952571)
> 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?
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?