Google Slashes Data Center Cooling Costs By 40 Percent In First Real-World Application Of the DeepMind AI

[Lucian Armasu]

Google uses its DeepMind AI to cut the cooling bill of one of its data centers by 40 percent, proving its AI can show significant improvements in real-world applications as well.

Google Slashes Data Center Cooling Costs By 40 Percent In First Real-World Application Of the DeepMind AI : Read more

 

[anbello262]

These kind of articles are the ones that make me thinkb"We are in the future" (as in the future I saw in movies when I was little, 15~20 years ago).
I'm glad to be the generation that gets to explore cyberspace.

 

[drozd81]

So Google replaced their default Building Automation System with its own "AI" which in this case is simply their own version of a Building Automation System that is custom tailored to their particular data center, probably has capability to control more points than there were originally and optimized PID's based on environmental factors. I applaud the 40% improvement, but realistically, is artificial intelligence something that's really required here to make that improvement? It seems that a team of skilled data center engineers would do no worse than that. Looking forward to reading that publication and hoping to find out that AI really did something incredible there that couldn't be done with reasonable human-based resources. Right now I'm skeptical but I would love to be wrong about that.

 

[anbello262]

I think that the improvement made is humanely possible.
But that's exactly the thing that surprises me.
It means that AI is already on a deployable level. It doesn't need to be 'better than humans' at some complex task. The fact that it is 'as good as', is already more than enough for me.

After all, the main point is the ability to deploy it multiple times with little modification, and get a semi-optimum result each time. If using a teams of engineers, they usually have to pretty much start over every time.

Like comparing doing certain task, or programming something to do it for you. If it's only one time, just doing it is better. But if it needs to be dlne several times (or there's hope of reusing it in the future) programming is usually the best choice.


I hope to see more, how far this goes in the near future.

 

[Genevieve_1]

next task, climate change! 😛

 

[uglyduckling81]

The answer to climate change will no doubt be exterminate all humans as the route cause of the problem. Skynet confirmed...

 

[jtown82]

its not that this could not have been done by humans its that the amount of humans it would have taken to extrapolate enough data and then convert it into useable information to be used to then compare and contrast this type of problem would not be efficient. There is no such thing as an AI currently. Every super computer runs off of hard set parameters using simple if, or, then , when, where, ect ect ect statements. they all do the same thing. take data they are hardset to look at, run them against the hard set parameters and out put it in a meaningful way that humans can use efficiently. Nothing about that is AI. it is 100% human intervention I wish people would stop incorrectly labeling things as AI when it isn't.

 

[alextheblue]

The answer to climate change will no doubt be exterminate all humans as the route cause of the problem. Skynet confirmed...

What about non-anthropogenic climate change?