
How was your day? Fine? Stressful? Boring? It might soon be a bit easier to flesh out your answer, or find out how someone else’s day really went.
All you need is a smartphone, a sensor and a high-tech “mirror”.

How was your day? Fine? Stressful? Boring? It might soon be a bit easier to flesh out your answer, or find out how someone else’s day really went.
All you need is a smartphone, a sensor and a high-tech “mirror”.

IN the 1960s, mainframe computers posed a significant technological challenge to common notions of privacy. That’s when the federal government started putting tax returns into those giant machines, and consumer credit bureaus began building databases containing the personal financial information of millions of Americans. Many people feared that the new computerized databanks would be put in the service of an intrusive corporate or government Big Brother.
What if you could know everything about your network? Instead of getting snapshots — albeit very rapid snapshops — you could see the path of every packet and run basic analytics on that stream of data in real time? It’s the difference between watching a Pixar cartoon as opposed to viewing a flip book. And that changes things.

During the 20-year period from 1989 to 2008, 21% of of all stocks listed in US stock markets became bankrupt. Since bankruptcies affect many investors and have played a large role in the recent global financial crisis, predicting bankruptcy before it happens could help some investors avoid large losses. In a new study, a team of physicists has used concepts from statistical physics to identify some characteristic behaviors of pre-bankrupt stocks that differ significantly from stocks that don’t become bankrupt. The approach may eventually help investors forecast stock bankruptcies weeks or months in advance.

Much ink has been spilled on the huge leaps in communications, social networking, and commerce that have resulted from impressive gains in IT and processing power over the last 30 years. However, relatively little has been said about how computing power is about to impact our lives in the biggest way yet: Health. Two things are happening in parallel: technology to collect biological data is taking off and computing is becoming massively scalable. The combination of the two is about to revolutionize health care.
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The Future Attribute Screening Technology project (FAST) was not dreamed up by Philip K. Dick, but it could have been. Lead by the U.S. Department of Homeland Security, the initiative aims to use sensor technology to detect cues “indicative of mal-intent,” defined by the DHS as intent or desire to cause real harm — “rapidly, reliably, and remotely.” It would be used, they say, to fight terror.

There’s a radical transformation happening in information technology today, one that promises to be every bit as significant—and every bit as disruptive to existing business models—as were Web applications in the 1990s and virtualization in the first decade of the 21st century. It’s a foundational change in the way enterprises, their employees, and their customers manage, share, and secure the staggering amounts of data that pass through their hands every day. It will make data available at higher speeds, on more massive scales and at lower costs that anyone could have imagined even a few years ago. It’s Storage 3.0, and it’s happening right now.

GOOD with numbers? Fascinated by data? The sound you hear is opportunity knocking.
Mo Zhou was snapped up by I.B.M. last summer, as a freshly minted Yale M.B.A., to join the technology company’s fast-growing ranks of data consultants. They help businesses make sense of an explosion of data — Web traffic and social network comments, as well as software and sensors that monitor shipments, suppliers and customers — to guide decisions, trim costs and lift sales. “I’ve always had a love of numbers,” says Ms. Zhou, whose job as a data analyst suits her skills.
The European Union (EU) is pledging 1 billion euros on a set of advanced computer technologies, including a supercomputing network, for predicting the future. But in this case, it’s not about forecasting climate change, finding marauding asteroids, or the determining the ultimate fate of the universe. Rather it is specifically designed to forecast social and economic events, in particular crisis events.
New data tools, perhaps best described as Web analytics on steroids and with psychic powers, are making their way into newsrooms and changing the way that editors decide what stories to promote, where, and when.
It’s part of an emerging technology trend called “big data” — a process of gathering large, comprehensive, complex datasets and using advanced computer algorithms to visualize them, extract patterns, and use them to make decisions.