About Me
Monday, March 31, 2008
Offline access to Google Docs
Our team has a real affinity for free-spirited types, and so we spend a lot of time thinking up ways to make Google Docs friendlier even to people on the go. If you're one of those, you already know how you can access your Google Docs from anywhere, how nice it is to avoid having to email yourself files or back up docs with a thumbdrive, and how easily you can collaborate with others.
Of course there was a teeny thing missing: you needed an Internet connection to make Google Docs work for you. Now, for documents, that's no longer true. As you'll read on the Google Docs blog, starting today and over the coming weeks we're rolling out offline editing access to word processing documents to Google Docs users. You no longer need an Internet connection when inspiration strikes. Whether you're working on an airplane or in a cafe, you can automatically access all your docs on your own computer.
To see how offline access works, watch this video:
Friday, March 28, 2008
Privacy made easier
Because we're strongly committed to protecting your privacy, we want to present our privacy practices in the clearest way possible. Over the past year, we've been experimenting with video to clarify and illustrate the privacy practices set forth in our Google Privacy Policy. We've used videos to communicate with you about things like cookies, IP addresses, and logs. (Check out the Google Privacy Channel on YouTube.) And you've told us that the screen shots, whiteboard drawings, and pointers from the engineers and product managers we've captured on video are helping you better understand the fine points of our Privacy Policy.
With that in mind, today we're announcing a revamp of our Privacy Center. The new Center is a one-stop shop for privacy resources, with various multi-media formats aimed to help you further understand how we store and use data, how to control who you share your data with, and how we protect your privacy. We hope this new Center will help you make more informed privacy choices whenever you use Google products and services.
Wednesday, March 26, 2008
Insight into YouTube videos
I remember the first time a video I posted to YouTube cracked 100 views. I wasn't so much surprised as curious: Who were these people? How did they find this video? Where did they come from?
Today we're taking our first step towards answering these questions with YouTube Insight, a free tool that enables anyone with a YouTube account -- users, partners, and advertisers -- to view detailed statistics about the videos that they upload. For example, uploaders can see how often their videos are viewed in different geographic regions, as well as how popular they are relative to all videos in that market over a given period of time. You can also delve deeper into the lifecycle of your videos, like how long it takes for a video to become popular, and what happens to video views as popularity peaks. For now, you can find currently available metrics by clicking under the "About this Video" button under My account > Videos, Favorites, Playlists > Manage my Videos.
Insight gives the creators an inside look into the viewing trends of their videos on YouTube, and helps them to increase views and become more popular. Partners can evaluate metrics to better serve and understand their audiences, as well as increase ad revenue. And advertisers can study their metrics and successes to tailor their marketing -- both on and off the site -- and reach the right viewers. As a result, Insight turns YouTube into one of the world's largest focus groups.
There's more about this on the YouTube blog.
Today is Document Freedom Day
Today, the world is celebrating the first-ever Document Freedom Day. More than 200 teams in 60 countries are spending today raising awareness about document freedom by hosting speakers, events, and literally raising the DFD flag. Through such activities, these teams are committed to spreading the word about the importance of open documents and the workable open standards that ensure your access to your documents now and in the future. We at Google wholeheartedly join the community of users, organisations, businesses, governments and individuals around the world in today's celebration.
Our mission concerning the world's information is well known. Naturally, your access to your information is also important to us. When you save a document, you need to be sure that the information in it will be accessible tomorrow, a month from now, ten years from now. How and where you choose to access your documents shouldn't make a difference. This is what Document Freedom Day is about.
Five years ago, who would have thought that we'd be accessing the documents we created then on our cell phones? And yet today we expect this. The standard by which your document is formatted today absolutely needs to be readable and available to those who design the technology for tomorrow. This is the only way that you will know for sure that the information you entrust to your documents now will be yours for as long as you want it to be.
So wherever you are, join the fun and support your freedom to access your information. Find out more and help to spread the word: Document freedom means freedom of information for all of us, now, later and long, long into the future.
Tuesday, March 25, 2008
Making search better in Catalonia, Estonia, and everywhere else
We recently began a series of posts on how we harness the power of data. Earlier we told you how data has been critical to the advancement of search; about using data to make our products safe and to prevent fraud; this post is the newest in the series. -Ed.
One of the most important uses of data at Google is building language models. By analyzing how people use language, we build models that enable us to interpret searches better, offer spelling corrections, understand when alternative forms of words are needed, offer language translation, and even suggest when searching in another language is appropriate.
One place we use these models is to find alternatives for words used in searches. For example, for both English and French users, "GM" often means the company "General Motors," but our language model understands that in French searches like seconde GM, it means "Guerre Mondiale" (World War), whereas in STI GM it means "Génie Mécanique" (Mechanical Engineering). Another meaning in English is "genetically modified," which our language model understands in GM corn. We've learned this based on the documents we've seen on the web and by observing that users will use both "genetically modified" and "GM" in the same set of searches.
In the past, language models were built from dictionaries by hand. But such systems are incomplete and don't reflect how people actually use language. Because our language models are based on users' interactions with Google, they are more precise and comprehensive -- for example, they incorporate names, idioms, colloquial usage, and newly coined words not often found in dictionaries.
When building our models, we use billions of web documents and as much historical search data as we can, in order to have the most comprehensive understanding of language possible. We analyze how our users searched and how they revised their searches. By looking across the aggregated searches of many users, we can infer the relationships of words to each other.
Queries are not made in isolation -- analyzing a single search in the context of the searches before and after it helps us understand a searcher's intent and make inferences. Also, by analyzing how users modify their searches, we've learned related words, variant grammatical forms, spelling corrections, and the concepts behind users' information needs. (We're able to make these connections between searches using cookie IDs -- small pieces of data stored in visitors' browsers that allow us to distinguish different users. To understand how cookies work, watch this video.)
To provide more relevant search results, Google is constantly developing new techniques for language modeling and building better models. One element in building better language models is using more data collected over longer periods of time. In languages with many documents and users, such as English, our language models allow us to improve results deep into the "long tail" of searches, learning about rare usages. However, for languages with fewer users and fewer documents on the web, building language models can be a challenge. For those languages we need to work with longer periods of data to build our models. For example, it takes more than a year of searches in Catalan to provide a comparable amount of data as a single day of searching in English; for Estonian, more than two and a half years worth of searching is needed to match a day of English. Having longer periods of data enables us to improve search for these less commonly used languages.
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