Reflections on the Google Faculty Institute

Posted by Maggie Johnson, Director of Education and University Relations

Extending the school year one day can result in a year’s worth of learning. This proved true on June 8, when the 2011 Google Faculty Institute (GFI) cohort were welcomed back for a day, to share best practices and perspectives from their funded research over the 2011-12 school year.

For the past year, the GFI Fellows collaborated across 16 California State University campuses, Stanford and UC Berkeley, to execute on ten research initiatives proposed on the final day of the conference. GFI themes of faculty collaboration, project-based learning, universal design and others were implemented in the Fellows’ projects, each of which focused on ways to enhance teaching practices through the use of educational technologies.

At the GFI Redux earlier this month, participants reviewed research initiatives, attended panel discussions, and defined plans for the 2012-13 school year. In a packed day of sessions, the cohort showcased projects ranging from mobile application development to geospatial tool utilization to the success of the flipped classroom. Some highlights of GFI projects:

• Making Teachers “Appy” presented workshops on UC and CSU campuses on mobile application development using App Inventor. While building confidence with new technologies, participants learned to create their own applications to enhance classroom instruction.

• Bird’s Eye Detective encouraged CSU pre-service teachers to explore the world from a new perspective utilizing geospatial tools including Google Earth, Google Maps, and Fusion Tables.

• Transforming STEM Educators included nine hands-on workshops on three CSU campuses, presenting creative ways to engage students in science and engineering courses through the use of technology.

• CSU Digital Learning Ambassadors are faculty creating collaborative communities and customized initiatives from the inside. Initiatives include tech infusion prizes, Hangouts on Air for academic discussions, and webinars.

The Google Faculty Institute served as a catalyst and incubator for innovative educational technology. Congratulations to the GFI Fellows on a year of excellent research and application.

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Google Research Awards: Summer, 2012

Posted by Maggie Johnson, Director of Education, University Relations

We’ve just finished the review process for the latest round of the Google Research Awards, which is our bi-annual open call for proposals on research in areas of mutual interest with Google. Our funding provides full-time faculty the opportunity to fund a graduate student and work directly with Google research scientists and engineers.

This round, we are funding 104 awards across 21 different focus areas for a total of nearly $6 million. The subject areas that received the highest level of support this time were systems and infrastructure, human computer interaction, and mobile. In addition, 28% of the funding was awarded to universities outside the U.S.

Given that our program is merit-based, we make funding decisions via committees of experts, who assess each proposal by its impact, innovation, relevance to Google, and other factors. Over the past two years, we have seen significant growth in the Research Award program. This round, we had 815 proposals—up 11% from last round, which required 1,946 reviews by 654 reviewers.

Our award committees represent a microcosm of Research @ Google. Not only do we work with research scientists in making funding decisions, but also engineers—many of whom have advanced degrees in Computer Science. Our research organization has a similar make-up: both research scientists and engineers working together on innovative projects that are product-focused and relevant to our customers.

Congratulations to the well-deserving recipients of this round’s awards. If you are interested in applying for the next round (deadline is October 15), please visit our website for more information.

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Our Unique Approach to Research

Posted by Alfred Spector, Vice President of Research and Special Initiatives

Google started as a research project—and research has remained a core part of our culture. But we also do research differently than many other places. To shed more light on Google’s unique approach to research, Peter Norvig (Director of Research), Slav Petrov (Senior Research Scientist) and I recently published a paper, “Google’s Hybrid Approach to Research,” in the July issue of Communications of the ACM.

   

In the paper, we describe our hybrid approach to research, which integrates research and development to maximize our impact on users and the speed at which we make progress. Our model allows us to work at unparalleled scale and conduct research in vivo on real systems with millions of users, rather than on artificial prototypes. This yields not only innovative research results and new technologies, but valuable new capabilities for the company—think of MapReduce, Voice Search or open source projects such as Android and Chrome. 

Breaking up long-term research projects into shorter-term, measurable components is another aspect of our integrated model. This is not to say our model precludes longer-term objectives, but we try to achieve these in stages. For example, Google Translate is a multi-year project characterized by the need for both research and complex systems, but we’ve achieved many small objectives along the way—such as adding languages over time for a current total of 64, developing features like two-step translation functionality, enabling users to make corrections, and consideration of syntactic structure.

Overall, our success in the areas of systems, speech recognition, language translation, machine learning, market algorithms, computer vision and many other areas has stemmed from our hybrid research approach. While there are risks associated with the close integration of research and development activities—namely the concern that research will take a back seat in favor of shorter-term projects—we mitigate those by focusing on the user and empirical data, maintaining a flexible organizational structure, and engaging with the academic community. We have a portfolio of timescales, with some researchers working with engineers to rapidly iterate on existing products, and others working on forward-looking projects that will benefit people in the future.

We hope “Google’s Hybrid Approach to Research” helps explain our method. We feel it will bring some clarification and transparency to our approach, and perhaps merit consideration by other technology companies and academic labs that organize research differently.

To learn more about what we do and see see real-time applications of our hybrid research model, add Research at Google to your circles on Google+.

(Cross-posted on the Official Google Blog) 

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Introducing new Fusion Tables API

Posted by Warren Shen, Fusion Tables team

We are very pleased to announce the public availability of the new Fusion Tables API. The new API includes all of the functionality of the existing SQL API, plus the ability to read and modify table and column metadata as well as the definitions of styles and templates for data visualization. This API is also integrated with the Google APIs console which lets developers manage all their Google APIs in one place and take advantage of built-in reporting and authentication features.

With this launch, we are also announcing a six month deprecation period for the existing SQL API. Since the new API includes all of the functionality of the existing SQL API, developers can easily migrate their applications using our migration guide.

For a detailed description of the features in the new API, please refer to the API documentation.

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Become a Google Power Searcher

Posted by Terry Ednacot, Education Program Manager

Cross-posted with the Official Google Blog

You may already be familiar with some shortcuts for Google Search, like using the search box as a calculator or finding local movie showtimes by typing [movies] and your zip code. But there are many more tips, tricks and tactics you can use to find exactly what you’re looking for, when you most need it.

Today, we’ve opened registration for Power Searching with Google, a free, online, community-based course showcasing these techniques and how you can use them to solve everyday problems. Our course is aimed at empowering you to find what you need faster, no matter how you currently use search. For example, did you know that you can search for and read pages written in languages you’ve never even studied? Identify the location of a picture your friend took during his vacation a few months ago? How about finally identifying that green-covered book about gardening that you’ve been trying to track down for years? You can learn all this and more over six 50-minute classes.

Lessons will be released daily starting on July 10, 2012, and you can take them according to your own schedule during a two-week window, alongside a worldwide community. The lessons include interactive activities to practice new skills, and many opportunities to connect with others using Google tools such as Google Groups, Moderator and Google+, including Hangouts on Air, where world-renowned search experts will answer your questions on how search works. Googlers will also be on hand during the course period to help and answer your questions in case you get stuck.

Power Searching with Google blends the MOOC (Massive Open Online Course) learning format pioneered by Stanford and MIT with our social and communication tools to create what we hope is a true community learning experience.

Visit the course homepage to learn more. By the end of this course, you'll know several new techniques that will make you a Google Power Searcher and help you find out information about whatever you can imagine—from how to prepare for a new family pet to where moss grows on Stonehenge or how to grow katniss in your garden. Sign up now!

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Third Market Algorithms and Optimization Workshop at Google NYC

Posted by Nitish Korula and Vahab Mirrokni, Google Research, New York

There are fascinating algorithmic and game theoretic challenges in designing both Google’s internal systems and our core products facing hundreds of millions of users. For example, both Google AdWords and the Ad Exchange run billions of auctions a day; showing the perfect ad to every user requires simple mechanisms to align incentives while simultaneously optimizing efficiency and revenue.

We think that research in these areas benefits from close cooperation between academia and industry. To this end, last week we held the Third Market Algorithms and Optimization Workshop at Google, immediately after STOC 2012. We invited several leading academics in these fields to meet with researchers and engineers at Google for a day of talks and discussions.

As a recent winner of the Godel prize, Éva Tardos from Cornell led off with a discussion of how to achieve efficiency in sequential auctions where bidders arrive and depart one at a time instead of all bidding simultaneously.

Eyal Manor, Google engineering director for the Ad Exchange, gave an overview of the design and functioning of the exchange. This was an opportunity to have questions answered by the absolute expert, and the participants took full advantage of it!

Costis Daskalakis and Pablo Azar from MIT and Tim Roughgarden from Stanford talked about different aspects of Optimal Auctions in Bayesian Settings. Costis talked about efficient implementation of optimal auctions in a class of combinatorial auctions. Both Tim and Pablo discussed optimal auctions in Bayesian settings with limited information. Tim, our other Godel prize winner, promoted the idea of designing simple auction rules that are independent of the distributions of buyers’ valuations, and Pablo presented optimal auction rules using only the mean and standard deviation of buyers’ valuations.

Bobby Kleinberg from Cornell and Gagan Goel from Google NYC presented recent work on pricing with budget constraints. Bobby’s talk was about procurement auctions where the auctioneer acts as a buyer with a budget constraining her procurements. Gagan, on the other hand, discussed Pareto-optimal ascending auctions where the auctioneer is selling to budget-constrained buyers. This has direct applications in Google AdWords auctions as advertisers aim to increase performance while staying within budget constraints.

With our mission of organizing all the world’s information, Google needs superior algorithmic techniques to analyze extremely large data sets. We had two talks on new algorithmic ideas for Big Data. From academia, Andrew McGregor gave an introduction to the new field of graph sketching. Though a graph on n nodes is O(n^2)-dimensional, Andy described how to find interesting properties of the graph (such as connectivity, approximate Minimum Spanning Trees, etc.) using only O(n polylog(n)) bits of information. These algorithms were based on clever use of the homomorphic properties of random projections of the graph’s adjacency matrix. In the next talk, Mohammad Mahdian from Google MTV explained a new model for evolving data; even a ‘simple’ problem like sorting becomes interesting when the order of elements changes over time. Mohammad showed that even if element swaps occur at the same rate as comparisons, one can compute an ordering with Kendall-Tau distance O(n ln ln n) from the true ordering at any time, very close to the optimal Ω(n).

Later, Mukund Sundararajan from Google MTV discussed algorithmic problems in interpreting and presenting sales data to advertisers. He challenged us to design flexible human-friendly optimization algorithms that can be adopted and tuned by humans. Toward the end of the workshop, Varun Gupta, Google NYC postdoctoral researcher, gave a short presentation about the use of primal-dual techniques for online stochastic bin packing with application in assigning jobs to data centers.

We also discussed some of the main activities in the algorithms research group in New York, like the use of primal-dual techniques in online stochastic display ad allocation at Google and large-scale graph mining techniques based on MapReduce and Pregel. Corinna Cortes, Director of Research in New York, and Alfred Spector, VP of Research and Special Projects, gave short speeches. Corinna talked about our statistics, machine learning, and NLP research groups in New York, and Alfred challenged us to design mechanisms to take into account fairness in allocations and pricing. For more details, see the blog post by our colleague, ‘Muthu’ Muthukrishnan.

Part of what makes Google a fascinating place to work is the wealth of algorithmic and economic research challenges posed by Google advertising and large-scale data analysis systems. These challenges define research directions for the computer science and economics research communities. Workshops like this and our weekly research seminars help us continue collaborations between Google and academia. We hope to post videos of this workshop shortly, and look forward to organizing many more such events in the future.

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Recap of NAACL-12 including two Best Paper awards for Googlers

Posted by Ryan McDonald, Research Scientist, Google Research

This past week, researchers from across the world descended on Montreal for the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). NAACL, as with other Association for Computational Linguistics meetings (ACL), is a premier meeting for researchers who study natural language processing (NLP). This includes applications such as machine translation and sentiment analysis, but also low-level language technologies such as the automatic analysis of morphology, syntax, semantics and discourse.

Like many applied fields in computer science, NLP underwent a transformation in the mid ‘90s from a primarily rule- and knowledge-based discipline to one whose methods are predominantly statistical and leverage advances in large data and machine learning. This trend continues at NAACL. Two common themes dealt with a historical deficiency of machine-learned NLP systems -- that they require expensive and difficult-to-obtain annotated data in order to achieve high accuracies. To this end, there were a number of studies on unsupervised and weakly-supervised learning for NLP systems, which aim to learn from large corpora containing little to no linguistic annotations, instead relying only on observed regularities in the data or easily obtainable annotations. This typically led to much talk during the question periods about how reliable it might be to use services such as Mechanical Turk to get the detailed annotations needed for difficult language prediction tasks. Multilinguality in statistical systems also appeared to be a common theme as researchers have continued to move their focus from building systems for resource-rich languages (e.g., English) to building systems for the rest of the world’s languages, many of which do not have any annotated resources. Work here included focused studies on single languages to studies aiming to develop techniques for a wide variety of languages leveraging morphology, parallel data and regularities across closely-related languages.

There was also an abundance of papers on text analysis for non-traditional domains. This includes the now standard tracks on sentiment analysis, but combined with this, a new focus on social-media, and in particular NLP for microblogs. There was even a paper on predicting whether a given bill will pass committee in the U.S. Congress based on the text of the bill. The presentation of this paper included the entire video on how a bill becomes a law.

There were two keynote talks. The first talk by Ed Hovy of the Information Sciences Institute of the University of Southern California was on “A New Semantics: Merging Propositional and Distributional Information.” Prof. Hovy gave his insights into the challenge of bringing together distributional (statistical) lexical-semantics and compositional semantics, which has been a need espoused recently by many leaders in the field. The second, by James W. Pennebaker, was called “A, is, I, and, the: How our smallest words reveal the most about who we are.” As a psychologist, Prof. Pennebaker represented the “outsider” keynote that typically draws a lot of interest from the audience, and he did not disappoint. Prof. Pennebaker spoke about how the use of function words can provide interesting social observations. One example was personal pronouns like “we,” whose increased usage now causes people to feel the speaker is colder and more distant as opposed to engaging the audience and making them appear accessible. This is partly due to a second and increasingly more common meaning of “we” that is much more like “you,” e.g., when a boss says: “We must increase sales”.

Finally, this year the organizers of NAACL decided to do something new called “NLP Idol.” The idea was to have four senior researchers in the community select a paper from the past that they think will have (or should have) more impact on future directions of NLP research. The idea is to pluck a paper from obscurity and bring it to the limelight. Each researcher presented their case and three judges gave feedback American Idol-style, with Brian Roark hosting a la Ryan Seacrest. The winner was "PAM - A Program That Infers Intentions," published in Inside Computer Understanding in 1981 by Robert Wilensky, which was selected and presented by Ray Mooney. PAM (“Plan Applier Mechanism”) was a system for understanding agents and their plans, and more generally, what is happening in a discourse and why. Some of the questions that PAM could answer were astonishing, which reminded the audience (or me at least) that while statistical methods have brought NLP broader coverage, this is often at the loss of specificity and deep knowledge representation that previous closed-world language understanding systems could achieve. This echoed sentiments in Prof. Hovy’s invited talk.

Ever since the early days of Google, Googlers have had a presence at NAACL and other ACL-affiliated events. NAACL this year was no different. Googlers authored three papers at the conference, one of which merited the conference’s Best Full Paper Award, and the other the Best Student Paper:

Cross-lingual Word Clusters for Direct Transfer of Linguistic Structure - IBM Best Student Paper
Award Oscar Täckström (Google intern), Ryan McDonald (Googler), Jakob Uszkoreit (Googler)

Vine Pruning for Efficient Multi-Pass Dependency Parsing - Best Full Paper Award
Alexander Rush (Google intern) and Slav Petrov (Googler)

Unsupervised Translation Sense Clustering
Mohit Bansal (Google intern), John DeNero (Googler), Dekang Lin (Googler)

Many Googlers were also active participants in the NAACL workshops, June 7 - 8:

Computational Linguistics for Literature 
David Elson (Googler), Anna Kazantseva, Rada Mihalcea, Stan Szpakowicz

Automatic Knowledge Base Construction/Workshop on Web-scale Knowledge Extraction
Invited Speaker - Fernando Pereira, Research Director (Googler)

Workshop on Inducing Linguistic Structure
Accepted Paper - Capitalization Cues Improve Dependency Grammar Induction
Valentin I. Spitkovsky (Googler), Hiyan Alshawi (Googler) and Daniel Jurafsky

Workshop on Statistical Machine TranslationProgram
Committee members - Keith Hall, Shankar Kumar, Zhifei Li, Klaus Macherey, Wolfgang Macherey, Bob Moore, Roy Tromble, Jakob Uszkoreit, Peng Xu, Richard Zens, Hao Zhang (Googlers) 

Workshop on the Future of Language Modeling for HLT 
Invited Speaker - Language Modeling at Google, Shankar Kumar (Googler)
Accepted Paper - Large-scale discriminative language model reranking for voice-search
Preethi Jyothi, Leif Johnson (Googler), Ciprian Chelba (Googler) and Brian Strope (Googler)

First Workshop on Syntactic Analysis of Non-Canonical Language
Invited Speaker - Keith Hall (Googler)
Shared Task Organizers - Slav Petrov, Ryan McDonald (Googlers)

Evaluation Metrics and System Comparison for Automatic Summarization
Program Committee member - Katja Filippova (Googler)

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