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My girlfriend is a neuroscientist. Every time she sees something about them 'modeling the brain' she is visibly amused/unhappy. It might be possible, but our current understanding of the brain feels much further away. The concept that we're going to hit some moore's law style thing in science that will propel us to just automatically understand things, which we can barely measure currently, just doesn't line up. Just…
I'm going to take the unpopular stance and say that it's very hard to make a prediction like this. Anyone who has a very strong stance one way or another probably needs to reevaluate their predictive capabilities. I do work in molecular dynamics. To even simulate a million atoms requires huge approximations. You can get more accurate as you simulate less. If you want an almost perfect match with reality, simulation w…
>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 chi…
Right. 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.
1) If we have to simulate it at a low level, the human brain is far too complex for any computer in any timeframe of our current lives to have enough power to simulate properly
2) Working backwards and simulating the high level processes (AI, etc) have been a dismal failure at actually replicating human thought processes, and will continue to be. While NN or the like can theoretically simulate any algorithm, we have no idea how to effectively train them in a way that produces high level thought similar to a human brain.
Generally when discussing this with people, I say this: if you disagree, give me a date by which you think I will be shown wrong, and then we'll reevaluate at that point.
I fully expect I could be proven wrong, and that would be an awesome world to live in, but my bold and unfortunate prediction is that I won't be.
I'm going to take the unpopular stance and say that it's very hard to make a prediction like this. Anyone who has a very strong stance one way or another probably needs to reevaluate their predictive capabilities. I do work in molecular dynamics. To even simulate a million atoms requires huge approximations. You can get more accurate as you simulate less. If you want an almost perfect match with reality, simulation w…
As I understand it, currents attempts to simulate brain activity operate on a slightly higher scale, mimicking the behaviour of neurons and the electronic signals between them, without resorting to modelling the behaviour of individual atoms.
Edit: I'll elaborate a little bit more. We currently simulate large proteins using force fields like CHARMM or AMBER. The problem we're trying to solve is what structure these proteins will fold into, and these force-fields work pretty well for that.
But consider this: these potentials are basically a handful of equations that describe stretching, bending, torsional, van der Waals, and electrostatic interactions. The parameters for these equations come from measurements of simple compounds that have similar structure, and these are used to extrapolate what will happen in a different substance. Good enough for folding, but if you want accurate energy levels? No way.
>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 chi…
>“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.
Earlier quoted context omitted.
Right. 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.
The 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.
>But Nicolelis is in a camp that thinks that human consciousness (and if you believe in it, the soul) simply can’t be replicated in silicon. That’s because its most important features are the result of unpredictable, non-linear interactions amongst billions of cells, Nicolelis says. This is a fringe opinion, and I really wish the title reflected that. Ignoring the absurd 'linear' part of the article, I don't believe…
Earlier quoted context omitted.
The 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.
But does a model of a human neuron require that the initial conditions are perfectly captured? I can't see why it would.