Interesting Snippets

a program called GLEAM (Global Epidemic and Mobility Model) that divides the world into hundreds of thousands of squares. It models travel patterns between these squares (busy roads, flight paths and so on) using equations based on data as various as international air links and school holidays. The result is impressive. In 2009, for example, there was an outbreak of a strain of influenza called H1N1. GLEAM mimicked what actually happened with great fidelity. In most countries it calculated to within a week when the number of new infections peaked. In no case was the calculation out by more than a fortnight.

People ask what the next web will be like, but there won’t be a next web.

The space-based web we currently have will gradually be replaced by a time-based worldstream. It’s already happening… this lifestream — a heterogeneous, content-searchable, real-time messaging stream — arrived in the form of blog posts and RSS feeds, Twitter and other chatstreams, and Facebook walls and timelines. …. All the information on the internet will soon be a time-based structure. In the world of bits, space-based structures are static. Time-based structures are dynamic, always flowing — like time itself.

The web will be history.

there will be a new literature from the mapping dictionary that’s now being built. There’s an Android app we’ve released called Field Trip…
Then when you’re walking around, say in Washington, D.C., the phone will buzz and say, “You are 25 feet from an accurate map of 2,700 solar objects. If you go over there to the Einstein Memorial, you can see them.” Or you might be walking down the street and it will beep and say… “Around the corner behind you is where a scene from your favorite movie was filmed.” It is using your location to search in a database of “interesting things,” and it learns what kinds of things you care about. It means having your life enlightened by travel knowledge, every-where, or getting to walk around with local experts who know your tastes, wherever in the world you go.

[Ubiquitous computing] - The idea is that computing devices will disappear into the background and what you’re left with is the benefit of computing, which is information and activities.
… Even though it’s possible to do a lot of things with your phone today, often that has the effect of pulling you into a bubble, instead of enhancing your experience.
When you’re out walking with your family, you’re not going to pause every 20 feet and do a Google search. So the notion [behind FieldTrip app] is that you can have this process that runs in the background that knows something about where you are, and about your interests. It can proactively offer up information that can help you have a richer experience but in a way that’s seamless and doesn’t interrupt the flow of your activity.

In Eric E. Schmidt’s future, his life will be a lot easier. His bed will wake him up when he cycles out of R.E.M. sleep. A driverless car will take him to work. Returning phone calls, scheduling events and other routine tasks will be taken care of by devices using artificial intelligence. A microrobot he swallows will monitor his insides and alert his doctor if something is wrong. At night, a robot will go to parties in his place.

In this world of huge and big data, you won’t be able to program machines for everything they should know,” said Ms. Rometty. “These machines will have to learn what is right, what is wrong, what is a pattern.” It is the third wave of computing, she said. At first, computers could count. Today, they are programmed to follow “if this, then that.” Next they will need to discover and learn on their own, she said, not just as a search engine, but proactively.

Expect Labs, a San Francisco start-up, have spent the past two years building an “anticipatory computing engine” - a platform for applications that predicts what people want or need before they explicitly ask or search for it.

Its first app for the iPad is MindMeld, a group voice and video-calling app that analyses what’s being talked about in real-time and “predicts” the type of information participants may want or need, pushing it to their tablets within seconds.

MindMeld listens to its users’ conversation and brings up related information
For example, let’s say, several co-workers are planning to meet up for bar snacks after work.

Depending on what types of food, drinks and possible meeting places are mentioned, MindMeld “listens” in the background and pulls up pertinent restaurant suggestions, reviews, maps, images and phone numbers using data from across the web and social networks

consider the case of Belgian telecom companies fighting for their share of triple play. Typically, companies would predict sales based on their past sales performance and marketing effort activations. Sales data from competition would be a good add-on to better prediction. However, data released from costly market research or from public sources, is only released quarter by quarter, thus a few months after sales have been processed. Looking at data retrieval in real time for all telecom operators—the intensity of branded search queries on Google as well as the amount of social mention valence on sites such as Twitter, Facebook and others—we found that the correlation with operator’s sales is strongly positive. Further, the correlation increased when sales was matched with search queries and social mentions captured six weeks in advance of sales.7 This time lag suggests that online data is leading and a powerful indicator of future sales for a company and their competitors

IBM is running in partnership with police departments across the nation, crunching massive amounts of public information to try to predict where and when crimes will occur. The project, known as CRUSH — Criminal Reduction Utilizing Statistical History — has proven very effective in pilot programs in several American cities, including Memphis, Tennessee, where it been credited with reducing serious crimes by 30 percent and violent crimes by 15 percent