5 ms·
> Why is having a huge cluster of GPUs/CPUs so important for AlphaGo? We humans only using about 100 Watts of power. We don't need megawatts of datacenter power
by MichaelBurge 10y ago
> Why is having a huge cluster of GPUs/CPUs so important for AlphaGo? We humans only using about 100 Watts of power. We don't need megawatts of datacenter power.
This argument loses a lot of its bite after AlphaGo beats the top humans.
You could argue that you still need lots of energy for training: Even a 100 watt human needs to live for 30/40 years before he's a top Go player. So it's not unreasonable that accelerating the process might use more power. And if you have all that power for training, you might as well use it for inference.
You can probably build a bad Go playing machine in much less than 100 watts. There might be a way to extract something more power-efficient from AlphaGo, but it doesn't seem to be important to anyone.
- BoorishBears 10y agoWhy can't you apply the same logic in reverse then? We're not able to speed up and compress what takes the 100 Watt machine as much as 21 years to fully develop, into something cars use locally yet, so we sidestep the problem with Lidar. Honestly both seem a little silly though, would an early, poorly trained version of Alpha GO confirm the need for lidar because it doesn't beat top humans?
- Cybiote 10y agoThe human brain is doing the playing so we can focus on 20 watts. We can also ignore the on going visual and audio processing, complex motion planning, on line learning, signal filtering and focus on just the Go part (in other words, < 20 watts is dedicated to Go playing). Humans also are unable to learn effectively, due to limits on attention we are not sure of yet, beyond ~4 hours per day. A talented human can reach pro level in about 8 years, enough to beat a neural net only player. The total energy use in joules spent learning is still about an order of magnitude less.
- deleted 10y ago[deleted]