Half a gigameter of biking navigation in 12 countries in Google Maps for Android

Whether you’re a seasoned century rider or a casual beach cruiser, finding the best biking routes can be a challenge. That’s why today we’re bringing mobile biking directions and navigation to the 10 countries where we launched desktop biking directions last month (Australia, Austria, Belgium, Denmark, Finland, the Netherlands, Norway, Sweden, Switzerland and the UK). Plus, we’re adding turn-by-turn, voice-guided biking navigation to Google Maps Navigation (beta) in every country with biking directions. Mount your device on your handlebars to see the turn-by-turn directions and navigation, or use speaker-mode to hear voice-guided directions.

Turn-by-turn biking navigation in Copenhagen

We know there are lots of ways to get from here to there, which is why in 2010, we added biking directions to Google Maps in the U.S. and Canada, and continue to work to bring more biking features to more places. Today, there are more than 330,000 miles (equal to more than 530,000 kilometers, or half a gigameter) of green biking lines in Google Maps. Dark green lines on the map show dedicated bike trails and paths with no motor vehicles, light green lines show streets with bike lanes and dashed green lines show other streets recommended for cycling. Biking navigation even helps you avoid steep hills.

Bike layer showing recommended streets for cycling in Stockholm

Where Map Maker and biking directions are both available, riders can add bike trails, lanes and suggested routes to Google Maps, helping to create a more comprehensive map for everyone living in or visiting their community. Thanks to the contributions of members of the biking community like Todd Scott and our partnership with nonprofits like Rails-to-Trails Conservancy, we’ve added bike data for hundreds of cities and trails to Google Maps in the past two-and-a-half years.

When you’re pedaling from Point A to Point B, we hope biking navigation will make Google Maps for Android more useful to you.

Posted by Larry Powelson, Software Engineer, Google Maps

(Cross-posted on the Lat Long blog)

Users love simple and familiar designs – Why websites need to make a great first impression

Posted by Javier Bargas-Avila, Senior User Experience Researcher at YouTube UX Research

I’m sure you’ve experienced this at some point: You click on a link to a website, and after a quick glance you already know you’re not interested, so you click ‘back’ and head elsewhere. How did you make that snap judgment? Did you really read and process enough information to know that this website wasn’t what you were looking for? Or was it something more immediate?

We form first impressions of the people and things we encounter in our daily lives in an extraordinarily short timeframe. We know the first impression a website’s design creates is crucial in capturing users’ interest. In less than 50 milliseconds, users build an initial “gut feeling” that helps them decide whether they’ll stay or leave. This first impression depends on many factors: structure, colors, spacing, symmetry, amount of text, fonts, and more.

In our study we investigated how users' first impressions of websites are influenced by two design factors:

1. Visual complexity -- how complex the visual design of a website looks 
2. Prototypicality -- how representative a design looks for a certain category of websites

We presented screenshots of existing websites that varied in both of these factors -- visual complexity and prototypicality -- and asked users to rate their beauty.

The results show that both visual complexity and prototypicality play crucial roles in the process of forming an aesthetic judgment. It happens within incredibly short timeframes between 17 and 50 milliseconds. By comparison, the average blink of an eye takes 100 to 400 milliseconds.

And these two factors are interrelated: if the visual complexity of a website is high, users perceive it as less beautiful, even if the design is familiar. And if the design is unfamiliar -- i.e., the site has low prototypicality -- users judge it as uglier, even if it’s simple.

In other words, users strongly prefer website designs that look both simple (low complexity) and familiar (high prototypicality). That means if you’re designing a website, you’ll want to consider both factors. Designs that contradict what users typically expect of a website may hurt users’ first impression and damage their expectations. Recent research shows that negative product expectations lead to lower satisfaction in product interaction -- a downward spiral you’ll want to avoid. Go for simple and familiar if you want to appeal to your users’ sense of beauty.

Google at UAI 2012

Posted by Kevin Murphy, Research Scientist

The conference on Uncertainty in Artificial Intelligence (UAI) is one of the premier venues for research related to probabilistic models and reasoning under uncertainty. This year's conference (the 28th) set several new records: the largest number of submissions (304 papers, last year 285), the largest number of participants (216, last year 191), the largest number of tutorials (4, last year 3), and the largest number of workshops (4, last year 1). We interpret this as a sign that the conference is growing, perhaps as part of the larger trend of increasing interest in machine learning and data analysis.

There were many interesting presentations. A couple of my favorites included:

• "Video In Sentences Out," by Andrei Barbu et al. This demonstrated an impressive system that is able to create grammatically correct sentences describing the objects and actions occurring in a variety of different videos. 
• "Exploiting Compositionality to Explore a Large Space of Model Structures," by Roger Grosse et al. This paper (which won the Best Student Paper Award) proposed a way to view many different latent variable models for matrix decomposition - including PCA, ICA, NMF, Co-Clustering, etc. - as special cases of a general grammar. The paper then showed ways to automatically select the right kind of model for a dataset by performing greedy search over grammar productions, combined with Bayesian inference for model fitting.

A strong theme this year was causality. In fact, we had an invited talk on the topic by Judea Pearl, winner of the 2011 Turing Award, in addition to a one-day workshop. Although causality is sometimes regarded as something of an academic curiosity, its relevance to important practical problems (e.g., to medicine, advertising, social policy, etc.) is becoming more clear. There is still a large gap between theory and practice when it comes to making causal predictions, but it was pleasing to see that researchers in the UAI community are making steady progress on this problem.

There were two presentations at UAI by Googlers. The first, "Latent Structured Ranking," by Jason Weston and John Blitzer, described an extension to a ranking model called Wsabie, that was published at ICML in 2011, and is widely used within Google. The Wsabie model embeds a pair of items (say a query and a document) into a low dimensional space, and uses distance in that space as a measure of semantic similarity. The UAI paper extends this to the setting where there are multiple candidate documents in response to a given query. In such a context, we can get improved performance by leveraging similarities between documents in the set.

The second paper by Googlers, "Hokusai - Sketching Streams in Real Time," was presented by Sergiy Matusevych, Alex Smola and Amr Ahmed. (Amr recently joined Google from Yahoo, and Alex is a visiting faculty member at Google.) This paper extends the Count-Min sketch method for storing approximate counts to the streaming context. This extension allows one to compute approximate counts of events (such as the number of visitors to a particular website) aggregated over different temporal extents. The method can also be extended to store approximate n-gram statistics in a very compact way.

In addition to these presentations, Google was involved in UAI in several other ways: I held a program co-chair position on the organizing committee, several of the referees and attendees work at Google, and Google provided some sponsorship for the conference.

Overall, this was a very successful conference, in an idyllic setting (Catalina Island, an hour off the coast of Los Angeles). We believe UAI and its techniques will grow in importance as various organizations -- including Google -- start combining structured, prior knowledge with raw, noisy unstructured data.

Making it easier to cast your ballot

The first presidential nominating convention, held in 1832, was meant to give Americans a voice in the selection of the presidential nominee. Fast forward to 2012 and these conventions still represent a major moment in American politics—and we’re helping the conventions reach a larger audience by being the official live stream provider and social networking platform for the Republican National Convention in Tampa and the Democratic National Convention in Charlotte.

In conjunction with our on-the-ground efforts, we’re making a number of online tools available to help you get organized and informed as Election Day approaches.

Get informed
Our Google Politics & Elections site enables you to see the latest Google News, YouTube videos, search and video trends, and Google+ content about the election in one place. You can also visit our live Elections Hub to watch the national political conventions, debates and even election night LIVE right from your mobile phone or laptop.

Register to vote
To make it easy to navigate the rules and deadlines about registering to vote and how to vote by mail, we put together an online voter guide. We’ve also added a special section to make it easier for military and overseas voters to find information about their different rules and deadlines.

As we approach the final days of the election, we’ll continue to develop useful ways for voters and campaigns to engage one another around the important issues in 2012.

We hope these tools will help you stay informed and participate in the election!

Posted by Eric Hysen, Google Politics & Elections Team

Better table search through Machine Learning and Knowledge

Posted By Johnny Chen, Product Manager, Google Research

The Web offers a trove of structured data in the form of tables. Organizing this collection of information and helping users find the most useful tables is a key mission of Table Search from Google Research. While we are still a long way away from the perfect table search, we made a few steps forward recently by revamping how we determine which tables are "good" (one that contains meaningful structured data) and which ones are "bad" (for example, a table that hold the layout of a Web page). In particular, we switched from a rule-based system to a machine learning classifier that can tease out subtleties from the table features and enables rapid quality improvement iterations. This new classifier is a support vector machine (SVM) that makes use of multiple kernel functions which are automatically combined and optimized using training examples. Several of these kernel combining techniques were in fact studied and developed within Google Research [1,2].

We are also able to achieve a better understanding of the tables by leveraging the Knowledge Graph. In particular, we improved our algorithms for identifying the context and topics of each table, the entities represented in the table and the properties they have. This knowledge not only helps our classifier make a better decision on the quality of the table, but also enables better matching of the table to the user query.

Finally, you will notice that we added an easy way for our users to import Web tables found through Table Search into their Google Drive account as Fusion Tables. Now that we can better identify good tables, the import feature enables our users to further explore the data. Once in Fusion Tables, the data can be visualized, updated, and accessed programmatically using the Fusion Tables API.

These enhancements are just the start. We are continually updating the quality of our Table Search and adding features to it.

Stay tuned for more from Boulos Harb, Afshin Rostamizadeh, Fei Wu, Cong Yu and the rest of the Structured Data Team.

[1] Algorithms for Learning Kernels Based on Centered Alignment
[2] Generalization Bounds for Learning Kernels

Google Maps heads north...way north

Search for [cambridge bay] on Google Maps and you’ll fly to a tiny hamlet located deep in the Kitikmeot Region of Nunavut in Canada’s Arctic, surrounded by an intricate lacework of tundra, waterways and breaking ice. High above the Arctic circle, it’s a place reachable only by plane or boat. Zoom in on the map, and this isolated village of 1,500 people appears as only a handful of streets, with names like Omingmak (“musk ox”) Street and Tigiganiak (“fox”) Road.


View Larger Map
Cambridge Bay in Google Maps
There are 4,000 years’ worth of stories waiting to be told on this map. Today, we’re setting out on an ambitious mission to tell some of those stories and to build the most comprehensive map of the region to date. It is the furthest north the Google Maps Street View team has traveled in Canada, and our first visit to Nunavut. Using the tools of 21st century cartography, we’re empowering a community and putting Cambridge Bay on the proverbial map of tomorrow.

The hamlet of Cambridge Bay
We’re not doing it alone, but with the help of the community and residents like Chris Kalluk. We first met Chris, who works for the nonprofit Nunavut Tunngavik, last September at our Google Earth Outreach workshop in Vancouver, where he learned how to edit Google Maps data using Google Map Maker. Today Chris played host to a community Map Up event in Cambridge Bay, where village elders, local mapping experts and teenagers from the nearby high school gathered around a dozen Chromebooks and used Map Maker to add new roads, rivers and lakes to the Google Map of Cambridge Bay and Canada's North. But they didn’t stop there. Using both English and Inuktitut, one of Nunavut’s official languages, they added the hospital, daycare, a nine-hole golf course, a territorial park and, finally, the remnants of an ancient Dorset stone longhouse which pre-dates Inuit culture.

Catherine Moats, a member of the Google Map Maker Team, working with Chris Kalluk and others at the Community Map Up.
Now we’re pedaling the Street View trike around the gravel roads of the hamlet and using a tripod—the same used to capture business interiors—to collect imagery of these amazing places. We’ll train Chris and others in the community to use some of this equipment so they can travel to other communities in Nunavut and continue to build the most comprehensive and accurate map of Canada’s Arctic. As Chris put it to us, “This is a place with a vast amount of local knowledge and a rich history. By putting these tools in the hands of our people, we will tell Nunavut’s story to the world.”

The Street View Trike collecting imagery of Cambridge Bay.
So stay tuned, world. We look forward to sharing with you the spectacular beauty and rich culture of Canada’s Arctic—one of the most isolated places on the planet that will soon be, thanks to the people of Cambridge Bay, just a click away.

Posted by Karin Tuxen-Bettman, Google Earth Outreach team

(Cross-posted on the Lat Long Blog and new Google Canada Blog)

The U.S. election, live on YouTube

Today we’re introducing the YouTube Elections Hub, a one-stop channel for key political moments from now through the upcoming U.S. election day on November 6. You can watch all of the live speeches from the floor of the upcoming Republican and Democratic National Conventions, see Google+ Hangouts with power brokers behind the scenes, and watch a live stream of the official Presidential and Vice Presidential debates. You won’t need to go anywhere else for the must-watch moments of this election cycle...they’re all happening on the Hub live.

In addition to videos from politicians and parties, a diverse range of news organizations—both established names in media and sought-after new voices—are sharing their coverage of the political process on the new hub. You’ll find live and on-demand reporting and analysis from ABC News, Al Jazeera English, BuzzFeed, Larry King, The New York Times, Phil DeFranco, Univision and the Wall Street Journal. Each will put their own stamp on the Presidential race—from the conventions to the debates to election night.



Of course, we’ll have special live coverage around the Republican National Convention from August 27 to 30, the Democratic National Convention from September 4-6, the Presidential and Vice Presidential debates in October, and election night. Bookmark the Elections Hub now for a front row seat along the road to the White House.

Posted by Olivia Ma, YouTube News Manager

(Cross-posted from the YouTube Blog)

Machine Learning Book for Students and Researchers

Posted by Afshin Rostamizadeh, Google Research

Our machine learning book, The Foundations of Machine Learning, is now published! The book, with authors from both Google Research and academia, covers a large variety of fundamental machine learning topics in depth, including the theoretical basis of many learning algorithms and key aspects of their applications. The material presented takes its origin in a machine learning graduate course, "Foundations of Machine Learning", taught by Mehryar Mohri over the past seven years and has considerably benefited from comments and suggestions from students and colleagues at Google.

The book can serve as a textbook for both graduate students and advanced undergraduate students and a reference manual for researchers in machine learning, statistics, and many other related areas. It includes as a supplement introductory material to topics such as linear algebra and optimization and other useful conceptual tools, as well as a large number of exercises at the end of each chapter whose full solutions are provided online.

Mapping the Motor City with Google Map Maker

Hailed as the birthplace of the automotive revolution, the city of Detroit, Mich. is taking its transportation legacy down new paths. As Detroit embraces a greener, non-motorized outlook, cycling is steadily increasing in popularity. The Michigan Trails and Greenways Alliance is facilitating this transition by creating an interconnected statewide system of trails and greenways, including the development of bike paths throughout the Detroit area.

As these new bike paths change the city’s landscape, Motor City residents need a more comprehensive map showing bike friendly routes. Todd Scott, the Detroit Greenways Coordinator, discovered that he could use Google Map Maker—a free tool that allows anyone to make contributions to Google Maps—to add new information on biking paths and trails in and around Detroit. Adding new bike paths not only makes the map more accurate, it also improves biking directions, making it even easier for people to find the quickest routes through town. Anyone can also enhance existing trails by including details such as the official name, surface type and bicycle suitability. Keeping Google Maps updated with the latest information means everyone in the community is able to find and enjoy these new additions to the trail system.

Learn more about Todd Scott and his mission to improve the map for cyclists in Detroit.
Building a more comprehensive, accurate and usable map for local cyclists is just one part of Todd’s mission. From the smallest town to a rapidly evolving city like Detroit, maps reflect the heart of a community. Whether you’re improving directions, adding local businesses or mapping an entire area from scratch, your local expertise will help make life easier for not only you, but all Google Maps users. As Todd says, “It goes beyond map making. It’s a way to take back your neighborhood.”

How are you mapping your world? Join the Map Maker Community and tell us your story.

Posted by Lori Savageau, Map Maker Community Manager

Faculty Summit 2012: Online Education Panel

Posted by Peter Norvig, Director of Research

On July 26th, Google's 2012 Faculty Summit hosted computer science professors from around the world for a chance to talk and hear about some of the work done by Google and by our faculty partners. One of the sessions was a panel on Online Education. Daphne Koller's presentation on "Education at Scale" describes how a talk about YouTube at the 2009 Google Faculty Summit was an early inspiration for her, as she was formulating her approach that led to the founding of Coursera. Koller started with the goal of allowing Stanford professors to have more time for meaningful interaction with their students, rather than just lecturing, and ended up with a model based on the flipped classroom, where students watch videos out of class, and then come together to discuss what they have learned. She then refined the flipped classroom to work when there is no classroom, when the interactions occur in online discussion forums rather than in person. She described some fascinating experiments that allow for more flexible types of questions (beyond multiple choice and fill-in-the-blank) by using peer grading of exercises.

In my talk, I describe how I arrived at a similar approach but starting with a different motivation: I wanted a textbook that was more interactive and engaging than a static paper-based book, so I too incorporated short videos and frequent interactions for the Intro to AI class I taught with Sebastian Thrun.

Finally, Bradley Horowitz, Vice President of Product Management for Google+ gave a talk describing the goals of Google+. It is not to build the largest social network; rather it is to understand our users better, so that we can serve them better, while respecting their privacy, and keeping each of their conversations within the appropriate circle of friends. This allows people to have more meaningful conversations, within a limited context, and turns out to be very appropriate to education.

By bringing people together at events like the Faculty Summit, we hope to spark the conversations and ideas that will lead to the next breakthroughs, perhaps in online education, or perhaps in other fields. We'll find out a few years from now what ideas took root at this year's Summit.