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>That’s because its most important features are the result of unpredictable, non-linear interactions amongst billions of cells, Nicolelis says. Replace "cells"
by mistercow 14y ago
>That’s because its most important features are the result of unpredictable, non-linear interactions amongst billions of cells, Nicolelis says.
Replace "cells" with "molecules" and "consciousness" with "fluid dynamics", and you can see what a vague, hand-waving argument this is.
>“You can’t predict whether the stock market will go up or down because you can’t compute it,” he says. “You could have all the computer chips ever in the world and you won’t create a consciousness.”
You can't predict the precise behavior of an analog amplifier, either, but you can still model it and produce a digital equivalent.
- Aqueous 14y agoRight. Tell this to the field of meteorology, or any other discipline that uses computers to simulate chaotic systems. We simulate complex, non-linear systems with computers all the time. Just because we don't have the solution for the differential equation that describes these dynamics doesn't mean that we can't simulate them.
- defen 14y agoThe problem with chaotic systems isn't simulating them, it's measuring the initial conditions. Arbitrarily small differences blow up exponentially fast even if your simulation has really, really small time steps.
- VMG 14y agoBut does a model of a human neuron require that the initial conditions are perfectly captured? I can't see why it would.
- defen 14y agoI have no idea :-) But I'm guessing the guy in the article thinks so, since he talks about non-linear effects. Linear systems cannot be chaotic.
- Aqueous 14y agoThe differences in initial conditions do cause the trajectories to diverge, but in certain systems they don't just diverge, they also get pulled into the orbit of an attractor, such as the Lorenz attractor. So, the behavior overall, despite being seemingly chaotic, is actually predictable and ordered.
- MaysonL 14y agoAssumning there aren't multiple competing attractors.
- defen 14y agoTo what extent is that actually useful if I want to know the specific state of the system at some point in the future, though? Even if I know the attractor I still can't measure the current state accurately enough to simulate its future state.
- VMG 14y agoThis quote also stumped me >“You can’t predict whether the stock market will go up or down because you can’t compute it,” If you had an accurate model of the agents, you could easily compute the stock market.