New Ways to Exploit Raw Data May Bring Surge of Innovation, a Study Says
New York Times (05/13/11) Steve Lohr
Mining and analyzing large datasets will lead to a new wave of innovation, according to a new report from the McKinsey Global Institute. The report, "Big Data: The Next Frontier for Innovation, Competition and Productivity," estimates the potential benefits of using data-harvesting technologies and skills. For example, it says the technology could be worth $300 billion annually to the U.S.'s health care system, while retailers could use it to boost profits by 60 percent. However, the study also identifies challenges to managing big data, such as a talent and skills gap. The report estimates that the United States will need at least 140,000 more experts in statistical methods and data-analysis technologies, as well as 1.5 million more data-literate managers. "Every manager will really have to understand something about statistics and experimental design going forward," says McKinsey's Michael Chui. The use of personal location data could save consumers more than $600 billion worldwide by 2020, according to the report. Consumers will benefit the most from time and fuel savings gained from location-based services that can monitor traffic and weather data to help drivers avoid congestion and suggest alternative routes, the report says. "It's clear that data is an important factor of production now," says McKinsey's James Manyika.
Friday, May 13, 2011
Blog: New Ways to Exploit Raw Data May Bring Surge of Innovation, a Study Says
Thursday, May 12, 2011
Blog: How to Control Complex Networks
How to Control Complex Networks
MIT News (05/12/11) Anne Trafton
Researchers at the Massachusetts Institute of Technology (MIT) and Northeastern University have developed a computational model that can analyze any type of complex network and find the critical points that can be used to control the entire system. The method can be used to reprogram adult cells and identify new drug targets, among other applications, says MIT professor Jean-Jacques Slotine. The researchers developed an algorithm that determines how many nodes in a network need to be controlled for total network control. They then adapted the algorithm to show how many points are needed and where those points are located. The number of points needed depends on the network's degree distribution, which describes the number of connections per node. The researchers applied their model to several real-life networks, including cell phone networks, social networks, and neuronal networks, calculating the percentage of points that need to be controlled in order to gain total control of the system. The researchers found that sparse networks require a higher number of controlled points than denser networks. "The area of control of networks is a very important one, and although much work has been done in this area, there are a number of open problems of outstanding practical significance," says Northeastern professor Adilson Motter.
Wednesday, May 4, 2011
Blog: Revolutionary New Paper Computer Shows Flexible Future for Smartphones and Tablets
Revolutionary New Paper Computer Shows Flexible Future for Smartphones and Tablets
Queen's University (Canada) (05/04/11)
Researchers at Queen's University, Arizona State University, and E Ink Corp. have developed the PaperPhone, an interactive paper-sized computer. "This computer looks, feels, and operates like a small sheet of interactive paper," says Roel Vertegaal, director of the Human Media Lab at Queen's University. "You interact with it by bending it into a cell phone, flipping the corner to turn pages, or writing on it with a pen." Vertegaal expects paper computers to revolutionize interactive computing within five years. The PaperPhone smartphone prototype offers all of the functions of a smartphone, but has a 9.5 cm diagonal thin film flexible E Ink display, which makes it more portable than mobile computers. The researchers say that the interactive paper-sized computers do not consume power when nobody is using them, and the devices do not feel like a sheet of glass or metal. Larger versions will be able to store and interact with documents. The researchers also developed a wristband computer based on the technology called Snaplet.
Blog: Intel Increases Transistor Speed by Building Upward
Intel Increases Transistor Speed by Building Upward
New York Times (05/04/11) John Markoff
Intel announced that it has begun manufacturing microprocessors with a three-dimensional (3D) design known as a fin field-effect transistor (Finfet), which is based on an extremely small pillar of silicon that rises above the surface of the chip. Intel says the 3D design runs as much as 37 percent faster in low-voltage applications and it will be able to cut power consumption by as much as 50 percent. The 3D transistors could be used to develop chips as small as 10 nanometers, a size that Intel researchers believe could be achieved by 2015. Intel's Mark T. Bohr says the new technology indicates that the company is maintaining the progress in chip development called for by Moore's Law, which states that the number of transistors that can be etched on a piece of silicon doubles every two years. However, Intel's competitors say that Finfet technology is risky because although it may be faster, it also may provide less control over power consumption. ST Microelectronics is developing an alternative technology based on placing a thin insulating layer below traditional transistors, which could result in low-power applications for mobile devices.
Tuesday, May 3, 2011
Blog: Wall Street Traders Mine Tweets to Gain a Trading Edge
Wall Street Traders Mine Tweets to Gain a Trading Edge
USA Today (05/03/11) Adam Shell
Wall Street traders are using social networking sites and computer algorithms to decipher the mood of the general public to predict market fluctuations. The use of linguistic analysis of online posts could prompt a computer program designed to interpret the data to place a trade with no human intervention. Researchers know that emotions play a significant role in markets and analyzing millions of tweets is similar to a "large-scale emotional thermometer for society as a whole," says Indiana University professor Johan Bollen, who recently completed a study that links Twitter mood measurements to stock market performance. Bollen used two mood-tracking tools to analyze the text of 9.6 million Twitter feeds over a nine-month period. One tool measured whether tweets were positive or negative, while the other tool categorized tweets into one of six moods. The measuring tools resulted in 87 percent accuracy in predicting Dow stock prices three to four days later, according to Bollen. Meanwhile, Pace University's Arthur O'Connor recently conducted a study showing a positive correlation between stock price performance and the social media popularity of brands such as Starbucks, Coca-Cola, and Nike. Market traders also are using computer algorithms to speed-read and analyze news to search for investing clues.