Watching Google's Data Center Machine Learning News spread

I was curious on how Google’s Data Center Machine Learning news would spread. 

At 1a on May 28, 2014 google posted on its main company blog with this kind of traffic over the past two days.


The following are three posts that went live at 1a PT May 28, 2014 as well with the google post and they were able to interview Joe Kava, VP of Data Centers

Google’s head of data center operations, Joe Kava, says that the company is now rolling out the machine learning model for use on all of its data centers. Gao has spent about a year building it, testing it out and letting it learn and become more accurate. Kava says the model is using unsupervised learning, so Gao didn’t have to specificy the interactions between the data is — the model will learn those interactions over time.

The Wired article spun the machine learning as an Artificial Brain which gave them more traffic than others.


But as I wrote Google’s machine learning is not really AI the way people would think.

BTW, in looking at the other articles, I realized my mistake.  In my post at 1a on May 28, I was a total nerd and got focused on the technology and didn’t mention Joe Kava’s name in my post even though I had interviewed him.  Damn.

Throughout the day the rest of the tech media were able to add their own posts.  I don’t know about you, but I am pretty impressed that Google was able to execute a media strategy that got the range of tech media to post on its Going Beyond PUE with Machine Learning.  PUE is not something widely discussed beyond the data center crowd.

Note the ComputerWeekly post was at the event where Joe Kava Keynoted and got 10 minutes of Joe’s time.  

My 10 minutes with Google's datacentre VP (blog) - ‎May 28, 2014‎
Google's Joe Kava speaking at the Google EU Data Center Summit (Photo credit: Tom Raftery) ... Google's network division, which is the size of a medium enterprise, had a technology refresh and by spending between $25,000 and $50,000 per site, we could improve their high availability features and improve their PUEs from 2.2 to 1.5. The savings ... As more volumes of data are created and as mass adoption of the cloud takes place, naturally it will require IT to think about datacentres and its efficiency differently.

Google Blog: Better Data Centers Through Machine Learning

PCBDesign007 - ‎May 28, 2014‎
It's no secret that we're obsessed with saving energy. For over a decade we've been designing and building data centers that use half the energy of a typicaldata center, and we're always looking for ways to reduce our energy use even further. In our pursuit ...

Google is improving its data centers with the power of machine learning

GeekWire - ‎May 28, 2014‎
google-datacenter-tech-05 In its continuing quest to improve the efficiency of its data centers, Google has found a new solution: machine learning. Jim Gao, an engineer on the company's data center team, has been hard at work on building a model of how ...

Google crafts neural network to watch over its data centers

Register - ‎May 28, 2014‎
The project began as one of Google's vaunted "20 per cent projects" by engineer Jim Gao, who decided to apply machine learning to the problem of predicting how the power usage effectiveness of Google's data centers would change in response to tweaking ...

Google's Machine Learning: It's About More Than Spotting Cats

Wall Street Journal (blog) - ‎May 28, 2014‎
Google said in a blog post Wednesday that it is using so-called neural networks to reduce energy usage in its data centers. These computer brains are able to recognize patterns in the huge amounts of data they are fed and “learn” how things like air ...

Google data centers get smarter all on their own -- no humans required

VentureBeat - ‎May 28, 2014‎
While most of us were thinking that research would turn out speech recognition consumer products, it actually turns out that Google has applied its neural networks to the challenge of making its vast data centers run as efficiently as possible, preventing the ...

Google AI improves datacentre energy efficiency - ‎May 28, 2014‎
“Realising that we could be doing more with the data coming out of datacentres, Jim studied machine learning and started building models to predict – and improve – datacentre performance.” The team's machine learning model behaves like other machine ...

Google taps machine learning technology to zap data center electricity costs

Network World (blog) - ‎May 28, 2014‎
Google is using machine learning technology to forecast - with an astounding 99.6% accuracy -- the energy usage in its data centers and automatically shift power to certain sites when needed. Using a machine learning system developed by its self ...

Google's machine-learning data centers make themselves more efficient

Ars Technica - ‎May 28, 2014‎
Google's data centers are famous for their efficient use of power, and now they're (literally) getting even smarter about how they consume electricity. Google today explained how it uses neural networks, a form of machine learning, to drive energy usage in its ...

Google is harnessing machine learning to cut data center energy

Bayoubuzz - ‎May 28, 2014‎
Leave it to Google to have an engineer so brainy he hacks out machine learning models in his 20 percent time. Google says that recently it's been using machine learning — developed by data center engineer Jim Gao (his Googler nickname is “Boy Wonder”) ...

Google turns to machine learning to build a better datacentre

ZDNet - ‎May 28, 2014‎
"The application of machine learning algorithms to existing monitoring data provides an opportunity to significantly improve DC operating efficiency," Google'sJim Gao, a mechanical engineer and data analyst, wrote in a paper online. "A typical large-scale ... These models can accurately predict datacentre PUE and be used to automatically flag problems if a centre deviates too far from the model's forecast, identify energy saving opportunities and test new configurations to improve the centre's efficiency. "This type of ...