If EfficientZero-9000 is using 10,000 times the energy of John von Neumann, and thinks 1,000 times faster, it’s actually actually 10 times less energy efficient.
The point of this post is that there is some small amount of evidence that you can’t make a computer think significantly faster, or better, than a brain without potentially critical trade offs.
I’m saying we will build AGI and it will be significantly faster and more capable than the brain. According to this post that means it will be significantly less energy-efficient. I agree. I don’t see why that matters. Energy is cheap, and people building AGI are wealthy.
I don’t see why that matters. Energy is cheap, and people building AGI are wealthy.
We don’t quite have self driving cars yet because current tech isn’t net efficient enough to run in the 200W or whatever power budget of a car, and also because the training algorithms aren’t data or power efficient enough yet - even with OOM more data than a human needs, and with training supercomputers using many MW of power.
With current tech someone arguably could piece together a low-level knowledge worker AGI, but it would cost $billions to train, and perhaps a MW to run at human performance, so it’s unlikely to outcompete humans and thus is economically near worthless.
If EfficientZero-9000 is using 10,000 times the energy of John von Neumann, and thinks 1,000 times faster, it’s actually actually 10 times less energy efficient.
The point of this post is that there is some small amount of evidence that you can’t make a computer think significantly faster, or better, than a brain without potentially critical trade offs.
I’m saying we will build AGI and it will be significantly faster and more capable than the brain. According to this post that means it will be significantly less energy-efficient. I agree. I don’t see why that matters. Energy is cheap, and people building AGI are wealthy.
We don’t quite have self driving cars yet because current tech isn’t net efficient enough to run in the 200W or whatever power budget of a car, and also because the training algorithms aren’t data or power efficient enough yet - even with OOM more data than a human needs, and with training supercomputers using many MW of power.
With current tech someone arguably could piece together a low-level knowledge worker AGI, but it would cost $billions to train, and perhaps a MW to run at human performance, so it’s unlikely to outcompete humans and thus is economically near worthless.