These people’s objections are not entirely unfounded. It’s true that there is little evidence the brain exploits QM effects (which is not to say that it is completely certain it does not). However, if you try to pencil in real numbers for the hardware requirements for a whole brain emulation, they are quite absurd. Assumptions differ, but it is possible that to build a computational system with sufficient nodes to emulate all 100 trillion synapses would cost hundreds of billions to over a trillion dollars if you had to use today’s hardware to do it.
The point is : you can simplify people’s arguments to “I’m not worried about the imminent existence of AI because we cannot build the hardware to run one”. The fact that a detail about their argument is wrong doesn’t change the conclusion.
Building a whole brain emulation right now is completely impractical. In ten or twenty years, though… well, let’s just say there are a lot of billionaires who want to live forever, and a lot of scientists who want to be able to play with large-scale models of the brain.
I’d also expect de novo AI to be capable of running quite a bit more efficiently than a brain emulation for a given amount of optimization power.. There’s no way simulating cell chemistry is a particularly efficient way to spend computational resources to solve problems.
An optimal de novo AI, sure. Keep in mind that human beings have to design this thing, and so the first version will be very far from optimal. I think it’s a plausible guess to say that it will need on the order of the same hardware requirements as an efficient whole brain emulator.
And this assumption shows why all the promises made by past AI researchers have so far failed : we are still a factor of 10,000 or so away from having the hardware requirements, even using supercomputers.
These people’s objections are not entirely unfounded. It’s true that there is little evidence the brain exploits QM effects (which is not to say that it is completely certain it does not). However, if you try to pencil in real numbers for the hardware requirements for a whole brain emulation, they are quite absurd. Assumptions differ, but it is possible that to build a computational system with sufficient nodes to emulate all 100 trillion synapses would cost hundreds of billions to over a trillion dollars if you had to use today’s hardware to do it.
The point is : you can simplify people’s arguments to “I’m not worried about the imminent existence of AI because we cannot build the hardware to run one”. The fact that a detail about their argument is wrong doesn’t change the conclusion.
Building a whole brain emulation right now is completely impractical. In ten or twenty years, though… well, let’s just say there are a lot of billionaires who want to live forever, and a lot of scientists who want to be able to play with large-scale models of the brain.
I’d also expect de novo AI to be capable of running quite a bit more efficiently than a brain emulation for a given amount of optimization power.. There’s no way simulating cell chemistry is a particularly efficient way to spend computational resources to solve problems.
An optimal de novo AI, sure. Keep in mind that human beings have to design this thing, and so the first version will be very far from optimal. I think it’s a plausible guess to say that it will need on the order of the same hardware requirements as an efficient whole brain emulator.
And this assumption shows why all the promises made by past AI researchers have so far failed : we are still a factor of 10,000 or so away from having the hardware requirements, even using supercomputers.