Friday, September 23, 2011

Googland

Googland

[G] Disaster recovery - built right in to Google Apps

Posted: 23 Sep 2011 04:24 AM PDT

Official Google Enterprise Blog: Disaster recovery - built right in to Google Apps

Posted by John Collins, Senior Global Trust PM, Google Apps

Editors note: This post is part of a series that explores the top ten reasons why customers trust Google with their business data. A complete top ten list can be found here.

Technology failures and natural disasters can significantly impact your business. Planning for them can be cumbersome and expensive. In a typical on-premise IT environment disaster recovery often means redundant infrastructure, backup tapes or storage area networks and a lot of IT complexity. Some businesses even build and manage duplicate data centers, specifically for disaster recovery, and those data centers sit idle the majority of the time.

The effectiveness of a disaster recovery plan is commonly measured in two ways: Recovery Time Objective (RTO) and Recovery Point Objective (RPO). RTO measures how long before users can access systems in the event of a failure. RPO measures how much of a time gap exists when the data is restored. Businesses that have invested lots of time and money in disaster recovery preparation are typically able to set RTO and RPO goals at a few hours or less for critical systems, with the cost increasing as those timeframes decrease. For other businesses that haven't invested at that level, RTO and RPO can stretch into hours or days. And in extreme cases, if disaster strikes, some businesses just have to start over.

Google Apps offers a better way, with robust disaster recovery capabilities built right in. Our RPO design target is zero data loss and our RTO design target is instant failover. This means that if there is a disaster or disruption that affects one of our data centers, we are able to shift users to an alternate data center, so they can can continue working uninterrupted. And while no disaster recovery solution from any provider is perfect, we are proud of the benefits our customers gain.

In the words of Mark Switalski, Macomb County Circuit Court Chief Judge, and Carmella Sabaugh, Macomb County Clerk:

"We know that when a disaster happens, our system will not go down and because our data is in the cloud, it is protected and accessible from anywhere. After a rare tornado hit last summer, briefly disrupting power and some network services, the clerk's Google service remained accessible via cell phone and other networks."

Planning for disasters is a big challenge, but with Google Apps you have fewer things to worry about. Your email and documents will be accessible so your business can continue despite the disaster. It's one of the main reasons that businesses trust Google Apps with their data.
URL: http://googleenterprise.blogspot.com/2011/09/disaster-recovery-built-right-in-to.html

[G] Gmail and Gmail for mobile go global again, available in Persian

Posted: 22 Sep 2011 06:31 PM PDT

Official Gmail Blog: Gmail and Gmail for mobile go global again, available in Persian

Posted by Ian Hill, Localization Project Manager

At Google, we want to make our products universally accessible and useful, and that means providing them for as many people as possible in the language they speak. The Gmail and Google Localization teams have worked together to bring Gmail to people around the world in 53 languages. Today that number grows to 54, because we're proud to announce that through working with the Persian Initiative Team, we are able to release Persian (Farsi - فارسی), as the newest language available in Gmail. If you or someone you know speaks Persian, they can change the language in Gmail by selecting it on the Gmail settings page, under the language dropdown.


Gmail for mobile is also now available in Persian through your mobile browser.


To read this announcement in Persian, visit the Google Persian blog.
URL: http://gmailblog.blogspot.com/2011/09/gmail-and-gmail-for-mobile-go-global.html

[G] SHOGUN aims high with Google Summer of Code

Posted: 22 Sep 2011 03:38 PM PDT

Google Open Source Blog: SHOGUN aims high with Google Summer of Code

Google Summer of Code 2011 gave a big boost to the development of the SHOGUN machine learning toolbox. In case you have never heard of SHOGUN or machine learning, machine learning involves algorithms that do 'intelligent' and even automatic data processing and is currently used in many different settings. You will find machine learning in the face detection in your camera, compressing the speech in your mobile phone, and powering the recommendations in your favorite online shop, as well as predicting the solubility of molecules in water and the location of genes in humans, to name just a few examples. Interested? Shogun can help you give it a try.

SHOGUN is a machine learning toolbox, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers a considerable number of machine learning models such as support vector machines for classification and regression, hidden Markov models, multiple kernel learning, linear discriminant analysis, linear programming machines, and perceptrons. Most of the specific algorithms are able to deal with several different data classes, including dense and sparse vectors and sequences using floating point or discrete data types. We have used this toolbox in several applications from computational biology, some of them coming with no less than 10 million training examples and others with 7 billion test examples. With more than a thousand installations worldwide, SHOGUN is already widely adopted in the machine learning community and beyond.

Some very simple examples stemming from a sub-branch of machine learning called supervised learning illustrate how objects represented by two-dimensional vectors can be classified into good or bad, by learning a support vector machine. I would suggest installing the python_modular interface of SHOGUN and to run the example interactive_svm_demo.py also included in the source tarball. Two images illustrating the training of a support vector machine follow:



We were a first time organization this year, i.e. taking part in our first Google Summer of Code. Having received many student applications, we were very happy to hear that we were given 5 very talented students but we had to reject about 60 students (only 7% acceptance rate). Deciding which 5 students we would accept was an extremely tough decision for us. So in the end we raised the bar by requiring sample contributions even before the actual Google Summer of Code started. The quality of the contributions and independence of the student aided our decision on the selection of the final five students.

At the end of the summer we now have a new core developer and various new features implemented in SHOGUN: Interfaces to new languages like Java, C#, Ruby, and Lua, a model selection framework, many dimension reduction techniques, Gaussian Mixture Model estimation and a full-fledged online learning framework. All of this work has already been integrated in the newly released shogun 1.0.0. To find out more about the newly implemented features read below.

Interfaces to the Java, C#, Lua and Ruby Programming Languages
Baozeng
Boazeng implemented swig-typemaps that enable transfer of objects native to the language one wants to interface to. In his project he added support for Java, Ruby, C# and Lua. His knowledge about Swig helped us to drastically simplify shogun's typemaps for existing languages like Octave and Python, resolving other corner-case type issues. In addition, the typemaps bring a high-performance and versatile machine learning toolbox to these languages. It should be noted that shogun objects trained in e.g. Python can be serialized to disk and then loaded from any other language like Lua or Java. We hope this helps users working in multiple-language environments. Note that the syntax is very similar across all languages used, compare for yourself, various examples for all languages (Python, Octave, Java, Lua, Ruby, and C#) are available.

Cross-Validation Framework
Heiko Strathmann
Nearly every learning machine has parameters which have to be determined manually. Before Heiko started his project, one had to manually implement cross-validation using (nested) for-loops. In his highly involved project Heiko extended shogun's core to register parameters and ultimately made cross-validation possible. He implemented different model selection schemes (train, validation, test split, n-fold cross-validation, stratified cross-validation, etc.) and created some examples for illustration. Note that various performance measures are available to measure how "good" a model is. The figure below shows the area under the receiver operator characteristic curve as an example.

Dimension Reduction Techniques
Sergey Lisitsyn
Dimensionality reduction is the process of finding a low-dimensional representation of a high-dimensional one while maintaining the core essence of the data. For one of the most important practical issues of applied machine learning, it is widely used for preprocessing real data. With a strong focus on memory requirements and speed, Sergey implemented the following dimension reduction techniques:
See below for some illustrations of dimension reduction/embedding techniques.



Expectation Maximization Algorithms for Gaussian Mixture Models
Alesis Novik
The Expectation-Maximization algorithm is well known in the machine learning community. The goal of this project was the robust implementation of the Expectation-Maximization algorithm for Gaussian Mixture Models. Several computational tricks have been applied to address numerical and stability issues, like:
Representing covariance matrices as their SVD
Doing operations in log domain to avoid overflow/underflow
Setting minimum variances to avoid singular Gaussians
Merging/splitting of Gaussians.

An illustrative example of estimating a one and two-dimensional Gaussian follows below.


Large Scale Learning Framework and Integration of Vowpal Wabbit
Shashwat Lal Das
Shashwat introduced support for 'streaming' features into shogun. That is, instead of shogun's traditional way of requiring all data to be in memory, features can now be streamed from a disk, enabling the use of massively big data sets. He implemented support for dense and sparse vector based input streams as well as strings and converted existing online learning methods to use this framework. He was particularly careful and even made it possible to emulate streaming from in-memory features. He finally integrated (parts of) Vowpal Wabbit, which is a very fast large scale online learning algorithm based on SGD.

By Sören Sonnenburg, Shogun Machine Learning Toolbox Organization Administrator and Co-mentor for Google Summer of Code

This is cross posted from Dr. Sonnenburg's blog, where you can find more details on his personal experience with Google Summer of Code.


URL: http://feedproxy.google.com/~r/GoogleOpenSourceBlog/~3/XbNgEMbqNdU/shogun-aims-high-with-google-summer-of.html

[G] This week in Docs: Import/export and paste special improvements

Posted: 22 Sep 2011 03:38 PM PDT

Docs Blog: This week in Docs: Import/export and paste special improvements

Yesterday, we announced the vertical merge feature in Google spreadsheets, and today we're happy to share two new features that we hope will make analyzing data a little more efficient.

More import and export support in Google spreadsheets
Now you can convert most pivot tables between Microsoft Excel files and Google spreadsheets for powerful data analysis in whatever file format you prefer. Additionally, filters that help you better visualize and organize your data are now supported in our import and export conversion tools.

To import a pivot table you created in Microsoft Excel, click the File menu in Excel, and select import, then select the file from the import options, and click the import button. If you've created a pivot table in Google spreadsheets, go to File in the spreadsheet, then click Download As, and choose Excel.

More paste special options in Google spreadsheets
Sometimes you need to copy data in cells that have lots of formatting and formulas, but you don't always want to paste everything in the cell. For instance, you may want to copy and paste the data in a range of cells, but not the borders that you placed around the cells.

We've added four new paste special options including: paste all cell contents except borders, formulas only, data validation only, or conditional formatting only. You can find these new options in a list under "Paste Special" in the Edit menu of Google spreadsheets.


We hope these latest features make working with Google spreadsheets more efficient and productive. As always, let us know what you think in the forum or in the comments.

Posted by: Dan Gundrum, Product Manager
URL: http://googledocs.blogspot.com/2011/09/this-week-in-docs-importexport-and.html

[G] The Fox News/Google Debate live tonight on YouTube: GOP candidates answer your questions

Posted: 22 Sep 2011 03:38 PM PDT

YouTube Blog: The Fox News/Google Debate live tonight on YouTube: GOP candidates answer your questions

Cross posted from the Official Google Blog.



Since we announced the Fox News/Google Debate on September 1, people across the country have submitted more than 18,000 questions to the Fox News YouTube channel on topics ranging from immigration reform, to health care, to foreign aid to social security. Tonight, the Republican presidential candidates will answer those questions in the Fox News/Google Debate, which will be live-streamed on YouTube and broadcast on Fox News Channel starting at 9pm ET. We'll also have an online pre-debate show starting at 8:30pm ET, featuring Fox News's Shannon Bream and Chris Stirewalt, and Steve Grove, YouTube's Head of News and Politics.



Even if you're watching on TV, you can visit youtube.com/foxnews during the debate to vote on real-time polling questions and submit live commentary. Throughout the evening, we'll share Google politics-related search trend information and public data that will provide context to the issues discussed. Fox News moderators will ask specific questions that were submitted by citizens through YouTube, and we'll be looking at overall trends that emerge from the questions in aggregate. To give you an idea, here's a look at the most popular words people used in their submissions (the bigger the word, the more often it was used)







Flex your democratic muscle and tune in to youtube.com/foxnews tonight at 8:30pm ET for a political debate that puts you in the driver's seat of the discussion.



Ramya Raghavan, YouTube News and Politics Manager, recently watched "Candidate Question IRS."


URL: http://feedproxy.google.com/~r/youtube/PKJx/~3/nArnkl490J8/fox-newsgoogle-debate-live-tonight-on.html

[G] The Fox News/Google Debate live tonight on YouTube: GOP candidates answer your questions

Posted: 22 Sep 2011 08:46 AM PDT

Official Google Blog: The Fox News/Google Debate live tonight on YouTube: GOP candidates answer your questions

Since we announced the Fox News/Google Debate on September 1, people across the country have submitted more than 18,000 questions to the Fox News YouTube channel on topics ranging from immigration reform, to health care, to foreign aid to social security. Tonight, the Republican presidential candidates will answer those questions in the Fox News/Google Debate, which will be live-streamed on YouTube and broadcast on Fox News Channel starting at 9pm ET. We'll also have an online pre-debate show starting at 8:30pm ET, featuring Fox News's Shannon Bream and Chris Stirewalt, and Steve Grove, YouTube's Head of News and Politics.

Even if you're watching on TV, you can visit youtube.com/foxnews during the debate to vote on real-time polling questions and submit live commentary. Throughout the evening, we'll share Google politics-related search trend information and public data that will provide context to the issues discussed. Fox News moderators will ask specific questions that were submitted by citizens through YouTube, and we'll be looking at overall trends that emerge from the questions in aggregate. To give you an idea, here's a look at the most popular words people used in their submissions (the bigger the word, the more often it was used).


Flex your democratic muscle and tune in to youtube.com/foxnews tonight at 8:30pm ET for a political debate that puts you in the driver's seat of the discussion.

Posted by Ramya Raghavan, YouTube news and politics manager
URL: http://googleblog.blogspot.com/2011/09/fox-newsgoogle-debate-live-tonight-on.html
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