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There's a lower limit for how much processing power it will take to run a human-level intelligence. The highest that lower limit can be is at the level where w

There's a lower limit for how much processing power it will take to run a human-level intelligence. The highest that lower limit can be is at the level where we can simulate each neuron in a human brain; at that point, we can build an AI merely by simulation. It seems likely, though, that by the time we get to being able to simulate an entire human brain, we'll long have passed the actual lower limit for human-level intelligence, if we knew exactly how to build it. Assuming we survive, it'll be interesting to find out when we passed the lower limit with supercomputers, when we understand enough to figure it out.

jpeterson 17y ago
The highest that lower limit can be is at the level where we can simulate each neuron in a human brain; at that point, we can build an AI merely by simulation. This assumes, of course, that we'll be able to observe every possible action of a neuron, and that these actions are all finitely computable.
a-priori 17y ago
Right now, it's possible to simulate one biologically-accurate neuron at a compartment-level (where you model a neuron by dividing it into many connected compartments), on one CPU core in real-time. Here's the kicker: it's also been shown that these simulations can scale linearly with the number of processors (given sufficient interconnect bandwidth). So with N cores, you can simulate kN neurons for some constant k (and I think that k=1). This implies that the limit is the number of CPU cores you throw at the problem. The human brain has around 100 billion neurons so, in theory, if you had a 100-billion core supercomputer, you could simulate the whole thing. That's a lot, but my point is that scaling a simulation is an engineering problem. This doesn't say anything about the accuracy of the model; that depends on accurate characterisations of each part of the neuron, and of how they're arranged and connected. But the key point here is that these are low-level characteristics that can be individually examined, making whole-brain simulations a tractable problem. Source: Djurfeldt et al. Brain-scale simulation of the neocortex on the IBM Blue Gene/L supercomputer. IBM JOURNAL OF RESEARCH AND DEVELOPMENT (2008)

jpeterson 17y ago

The highest that lower limit can be is at the level where we can simulate each neuron in a human brain; at that point, we can build an AI merely by simulation. This assumes, of course, that we'll be able to observe every possible action of a neuron, and that these actions are all finitely computable.

a-priori 17y ago

Right now, it's possible to simulate one biologically-accurate neuron at a compartment-level (where you model a neuron by dividing it into many connected compartments), on one CPU core in real-time. Here's the kicker: it's also been shown that these simulations can scale linearly with the number of processors (given sufficient interconnect bandwidth). So with N cores, you can simulate kN neurons for some constant k (and I think that k=1). This implies that the limit is the number of CPU cores you throw at the problem. The human brain has around 100 billion neurons so, in theory, if you had a 100-billion core supercomputer, you could simulate the whole thing. That's a lot, but my point is that scaling a simulation is an engineering problem. This doesn't say anything about the accuracy of the model; that depends on accurate characterisations of each part of the neuron, and of how they're arranged and connected. But the key point here is that these are low-level characteristics that can be individually examined, making whole-brain simulations a tractable problem. Source: Djurfeldt et al. Brain-scale simulation of the neocortex on the IBM Blue Gene/L supercomputer. IBM JOURNAL OF RESEARCH AND DEVELOPMENT (2008)