TE
科技回声
首页24小时热榜最新最佳问答展示工作
GitHubTwitter
首页

科技回声

基于 Next.js 构建的科技新闻平台,提供全球科技新闻和讨论内容。

GitHubTwitter

首页

首页最新最佳问答展示工作

资源链接

HackerNews API原版 HackerNewsNext.js

© 2025 科技回声. 版权所有。

DeepMind AI Reduces Google Data Centre Cooling Bill by 40%

135 点作者 ernesto95将近 9 年前

12 条评论

dang将近 9 年前
<a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=12126298" rel="nofollow">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=12126298</a>
ankurdhama将近 9 年前
Replace the word &quot;AI&quot; with &quot;optimisation algorithm&quot; and you are safe from AI hype.
评论 #12134668 未加载
评论 #12141099 未加载
评论 #12135089 未加载
评论 #12134709 未加载
empath75将近 9 年前
This is pretty stunning and should make a lot of knowledge workers terrified. I&#x27;m sure Google has a bunch of really smart guys working on figuring out how to reduce energy costs. To have a computer come in and get those kinds of results on the first attempt is pretty mindblowing.
评论 #12134878 未加载
评论 #12134584 未加载
评论 #12134628 未加载
评论 #12134563 未加载
评论 #12134510 未加载
评论 #12134792 未加载
评论 #12134781 未加载
argonaut将近 9 年前
Always fascinating how it turns out many ideas in research were already tested in the past (of course DeepMind is most likely aware of and has improved on prior work).<p>From NIPS in 2008: &quot;Managing Power Consumption and Performance of Computing Systems Using Reinforcement Learning&quot; (<a href="http:&#x2F;&#x2F;papers.nips.cc&#x2F;paper&#x2F;3251-managing-power-consumption-and-performance-of-computing-systems-using-reinforcement-learning.pdf" rel="nofollow">http:&#x2F;&#x2F;papers.nips.cc&#x2F;paper&#x2F;3251-managing-power-consumption-...</a>)
pm90将近 9 年前
&gt;<i>Our machine learning system was able to consistently achieve a 40 percent reduction in the amount of energy used for cooling, which equates to a 15 percent reduction in overall PUE after accounting for electrical losses and other non-cooling inefficiencies</i><p>So the actual savings were 15%? Which is still significant for sure. I&#x27;m guessing their next step will be to reduce those non-cooling inefficiencies.
kevindong将近 9 年前
I&#x27;m very interested in exactly what actions the machine learning algorithms recommended Google take.
评论 #12134553 未加载
评论 #12134558 未加载
vessenes将近 9 年前
This makes me wonder what a next-gen datacenter would look like; far more control points, far more data gathering, probably some combination of high- and low-inertia cooling with different characteristics -- essentially you are going to want to start giving your NN more knobs to tweak.<p>That seems very singularity&#x2F;jackpot-ish to me. Cool, but will have some interesting unexpected consequences, I bet.
zer0gravity将近 9 年前
At some point in the near future the AI itself will be posting blog posts about its achievements.<p>Very soon after that, the AI will be revisiting the stored history of the internet, will be reading this post, and laugh its ass bits off...<p>HELLO FROM THE PAST! WE WERE HUMANS!
cranesan将近 9 年前
&quot;We are planning to roll out this system more broadly and will share how we did it in an upcoming publication, so that other data centre and industrial system operators -- and ultimately the environment -- can benefit from this major step forward.&quot;<p>Please do, I am hungry for details here. The one chart they put in has no scale on it&#x27;s axis, and as another comment pointed out, they didn&#x27;t give any details about what recommendations were followed to achieve the improvements.
hyh1048576将近 9 年前
Very cool. I wonder how many more sensors do they installed to collect necessary data.
amasad将近 9 年前
I&#x27;d be interested in learning how much saving this is in dollars -- anyone here knowledgeable enough in data centre cooling to estimate this?
tener将近 9 年前
I wonder if anyone has done the math on total cost savings for Google and how it will impact their earnings&#x2F;stock price.