Autonomy excels at analyzing the vast amounts of "unstructured data" being produced every day.
Tom Simonite Technology Review (by MIT) Thursday, August 18, 2011
News broke today that HP, the world's biggest manufacturer of personal computers, had offered to acquire the British software company Autonomy. While the latter is hardly a household name, it gets close to $1 billion in revenue each year from software that can turn huge volumes of images, text, and video into useful statistics and insights for businesses.
Acquiring that technology will enable HP to expand its business software products, and put it in a good position to exploit a trend dubbed "big data." Businesses are increasingly interested in finding ways to distill meaning from the growing piles of digital information, from tweets to video, flowing through our lives at work and at home.
Whit Andrews, a vice president and analyst with Gartner who specializes in technology that processes and organizes information, says that Autonomy was years ahead of other companies in making such analysis possible. "They have had this vision for over a decade that there was immense value in being able to do statistical analysis for data like audio and video that conventional technology cannot handle."
Autonomy's products enable companies to do things like analyze transcripts from call centers; discover which sales strategies work best; and process troves of e-mails and other documents to match whether what is being said and done comports with a company's legal responsibilities. Such analysis can be automated using software that looks for certain things automatically, or performed manually by a person entering queries, and then sifting through the results themselves.
Andrews says business and technology companies are beginning to realize that both types of analysis could offer much more than conventional approaches, which rely on so-called "structured" data, such as a spreadsheet organized into labelled columns. "Business analytics is about structured data, like spreadsheets," says Andrews. "Autonomy does an exceptional job at analyzing unstructured data, which may prove even more valuable."
In an interview with Technology Review published last year, Autonomy's founder and CEO, Mike Lynch, estimated that about 85 percent of the information inside a business is unstructured. "[W]e are human beings, and unstructured information is at the core of everything we do," he said. "Most business is done using this kind of human-friendly information."
Lynch founded the company to commercialize statistical techniques developed at Cambridge University based on Bayesian inference, a mathematical technique that can estimate the probability of potential outcomes based on previous evidence.
Companies like IBM are working hard on their own approaches to analyzing unstructured data, but Autonomy has been at it for longer, says Andrews. Acquiring the company could enable HP to take a much more dominant position in the growing market for what Autonomy's Lynch dubs "meaning-based computing."
Monday, August 22, 2011
4G a boon to U.S. economy and jobs, study says
Roger Cheng CNet News August 21, 2011 9:01 PM PDT
The wireless carriers' investment in 4G networks could be the salve that the ailing U.S. economy is looking for.
The carriers could invest between $25 billion and $53 billion in building out their 4G network through 2016, according to a study from Deloitte. That in turn could lead to the creation of 371,000 to 771,000 jobs, and gross domestic product growth of $73 billion to $151 billion.
"Investment in such a powerful form of communication contributes to the economic recovery and provides a job-creating engine for the future," said Phil Asmundson a consultant for Deloitte.
The rise of 4G networks could provide some support for an economy still struggling to recover, and which some believe is slipping back into a recession. The recent bitter political struggle to raise the national debt ceiling, the sharp declines in the stock market, and the continued high rate of unemployment have many still concerned.
The wide-ranging estimate assumes two different scenarios. The baseline scenario has the carriers deploying 4G technology at a moderate pace with a slow transition from 3G to 4G extending into the middle of the decade. Deloitte warns that under these conditions, the U.S. firms will be vulnerable to foreign competitors looking to jump ahead in the 4G race.
The second scenario predicts a more rapid investment in 4G networks and the creation of 4G-based services before global competitors gain momentum. Deloitte said the demand stimulated by the new services would propel more network investment, "setting off a virtuous cycle of investment and market response." Cloud services are among the primary catalysts for investment, according to Deloitte.
Telecommunications investment has remained strong over the past few years, with large companies such as AT&T and Verizon pouring money into network upgrades. AT&T has argued that its acquisition of T-Mobile would lead to new jobs and investment because it is able to expand its future 4G network across a wider stretch of the country. Chief Executive Randall Stephenson has long argued that investment in telecommunications technology is crucial to staying ahead in the world.
AT&T plans to launch its first 4G LTE markets later this summer.
Verizon, meanwhile, has spent billions of dollars upgrading its fixed-line infrastructure with fiber-optic lines to deliver television content and faster Internet service. On the wireless side, the company has been racing to build out its 4G LTE network, and recently said that it covers more than half the country.
Clearwire is also switching gears from its current 4G WiMax standard and moving toward LTE, but the company said it plans to spend only $600 million for the upgrade.
Clearwire's largest customer and shareholder, Sprint Nextel, is planning to unveil its 4G plans in October. The company has already signed a network-hosting deal with LightSquared, which plans to start testing its 4G network with customers next year.
The widespread adoption of 4G services should also help certain segments such as disadvantaged minority groups; rural communities and areas with limited full broadband access; and small businesses, the firm said, adding the advent of 4G could work to bring those groups further into the economic mainstream.
Read more: http://news.cnet.com/8301-1035_3-20094588-94/4g-a-boon-to-u.s-economy-and-jobs-study-says/#ixzz1VleV8J20
The wireless carriers' investment in 4G networks could be the salve that the ailing U.S. economy is looking for.
The carriers could invest between $25 billion and $53 billion in building out their 4G network through 2016, according to a study from Deloitte. That in turn could lead to the creation of 371,000 to 771,000 jobs, and gross domestic product growth of $73 billion to $151 billion.
"Investment in such a powerful form of communication contributes to the economic recovery and provides a job-creating engine for the future," said Phil Asmundson a consultant for Deloitte.
The rise of 4G networks could provide some support for an economy still struggling to recover, and which some believe is slipping back into a recession. The recent bitter political struggle to raise the national debt ceiling, the sharp declines in the stock market, and the continued high rate of unemployment have many still concerned.
The wide-ranging estimate assumes two different scenarios. The baseline scenario has the carriers deploying 4G technology at a moderate pace with a slow transition from 3G to 4G extending into the middle of the decade. Deloitte warns that under these conditions, the U.S. firms will be vulnerable to foreign competitors looking to jump ahead in the 4G race.
The second scenario predicts a more rapid investment in 4G networks and the creation of 4G-based services before global competitors gain momentum. Deloitte said the demand stimulated by the new services would propel more network investment, "setting off a virtuous cycle of investment and market response." Cloud services are among the primary catalysts for investment, according to Deloitte.
Telecommunications investment has remained strong over the past few years, with large companies such as AT&T and Verizon pouring money into network upgrades. AT&T has argued that its acquisition of T-Mobile would lead to new jobs and investment because it is able to expand its future 4G network across a wider stretch of the country. Chief Executive Randall Stephenson has long argued that investment in telecommunications technology is crucial to staying ahead in the world.
AT&T plans to launch its first 4G LTE markets later this summer.
Verizon, meanwhile, has spent billions of dollars upgrading its fixed-line infrastructure with fiber-optic lines to deliver television content and faster Internet service. On the wireless side, the company has been racing to build out its 4G LTE network, and recently said that it covers more than half the country.
Clearwire is also switching gears from its current 4G WiMax standard and moving toward LTE, but the company said it plans to spend only $600 million for the upgrade.
Clearwire's largest customer and shareholder, Sprint Nextel, is planning to unveil its 4G plans in October. The company has already signed a network-hosting deal with LightSquared, which plans to start testing its 4G network with customers next year.
The widespread adoption of 4G services should also help certain segments such as disadvantaged minority groups; rural communities and areas with limited full broadband access; and small businesses, the firm said, adding the advent of 4G could work to bring those groups further into the economic mainstream.
Read more: http://news.cnet.com/8301-1035_3-20094588-94/4g-a-boon-to-u.s-economy-and-jobs-study-says/#ixzz1VleV8J20
Friday, August 19, 2011
Computer Analysis Could Find New Uses for Existing Drugs
I HealthBeat August 18, 011
A computer program that analyzes drug data and genetic information could help discover new uses for medicines already on the market, according to two new studies published in the journal Science Translational Medicine, United Press International reports.
Methodology
For the NIH-funded research, Stanford University scientists extracted data from NIH's Gene Expression Omnibus, a public database containing findings from thousands of genomic studies conducted throughout the world.
Researchers focused on 100 diseases and 164 drugs. They analyzed thousands of possible drug-disease combinations to identify which medications and medical conditions had gene expression patterns that could cancel each other out. Such matches indicate that the drug potentially could mitigate the effects of the disease (United Press International, 8/17).
Research Findings
Researchers identified possible drug-disease matches for 53 of the 100 diseases analyzed (Renick, Bloomberg, 8/17).
For example, they found that an epilepsy treatment potentially could treat inflammatory bowel disease and that an ulcer drug might be an effective lung cancer medication (Dockser Marcus, Wall Street Journal, 8/18).
Possible Implications
Researchers noted that re-purposing existing medications to treat different diseases could reduce some of the costs and requirements involved in the drug development process. They noted that it takes an average of 15 years and about $1 billion to bring a single new drug to market (Bloomberg, 8/17).
In an accompanying commentary on the research, Yves Lussier -- a professor of medicine and engineering at the University of Illinois in Chicago -- wrote that the findings should not prompt physicians to prescribe an ulcer drug to treat lung cancer. However, he added that the findings are "impressive enough to be improved upon and studied further."
Lussier also noted that if the computer program is effective at detecting possible off-label uses for existing drugs, it "opens the door to very low-cost, individualized personal therapies" (Wall Street Journal, 8/18).
Read more: http://www.ihealthbeat.org/articles/2011/8/18/computer-analysis-could-find-new-uses-for-existing-drugs.aspx#ixzz1VTsrgrjJ
A computer program that analyzes drug data and genetic information could help discover new uses for medicines already on the market, according to two new studies published in the journal Science Translational Medicine, United Press International reports.
Methodology
For the NIH-funded research, Stanford University scientists extracted data from NIH's Gene Expression Omnibus, a public database containing findings from thousands of genomic studies conducted throughout the world.
Researchers focused on 100 diseases and 164 drugs. They analyzed thousands of possible drug-disease combinations to identify which medications and medical conditions had gene expression patterns that could cancel each other out. Such matches indicate that the drug potentially could mitigate the effects of the disease (United Press International, 8/17).
Research Findings
Researchers identified possible drug-disease matches for 53 of the 100 diseases analyzed (Renick, Bloomberg, 8/17).
For example, they found that an epilepsy treatment potentially could treat inflammatory bowel disease and that an ulcer drug might be an effective lung cancer medication (Dockser Marcus, Wall Street Journal, 8/18).
Possible Implications
Researchers noted that re-purposing existing medications to treat different diseases could reduce some of the costs and requirements involved in the drug development process. They noted that it takes an average of 15 years and about $1 billion to bring a single new drug to market (Bloomberg, 8/17).
In an accompanying commentary on the research, Yves Lussier -- a professor of medicine and engineering at the University of Illinois in Chicago -- wrote that the findings should not prompt physicians to prescribe an ulcer drug to treat lung cancer. However, he added that the findings are "impressive enough to be improved upon and studied further."
Lussier also noted that if the computer program is effective at detecting possible off-label uses for existing drugs, it "opens the door to very low-cost, individualized personal therapies" (Wall Street Journal, 8/18).
Read more: http://www.ihealthbeat.org/articles/2011/8/18/computer-analysis-could-find-new-uses-for-existing-drugs.aspx#ixzz1VTsrgrjJ
Tuesday, August 16, 2011
The web turns twenty
Difference Engine: Happy anniversary?
Aug 12th 2011, 10:37 by N.V. | LOS ANGELES
IT IS always a little disconcerting to realise a generation has grown up never knowing what it was like to manage without something that is taken for granted today. A case in point: the World Wide Web (WWW), which celebrated the 20th anniversary of its introduction last Saturday. It is no exaggeration to say that not since the invention of the printing press has a new media technology altered the way people think, work and play quite so extensively. With the web having been so thoroughly embraced socially, politically and economically, the world has become an entirely different place from what it was just two decades ago. Whether the web has made it a better place or a worse one is for readers to decide.
It was on August 6th, 1991, that Tim Berners-Lee, a British physicist at the European Organisation for Nuclear Research (CERN), in Geneva, created the first-ever web page—a summary of his WWW project along with explanations to help visitors build websites of their own and to search the web for information. No screen-shots survive of the original web page; its original address simply redirects visitors to a contemporary site providing details of the project’s early days at CERN.
First, however, a few things to get straight. The web is not to be confused with the internet—a global system of interconnected networks developed in the 1960s, originally for academic and government researchers in America. The internet sends information as discrete packets of data using a suite of protocols known as TCP/IP. The genius of the system is that the data tell the network where they want to go, instead of the network telling the data where they are being sent. All networks adopting this procedure—no matter where they are or how they actually function—are then reduced effectively to the same bare essentials, allowing them to interconnect and exchange data seamlessly.
The web, by contrast, is simply a way of organising information on a computer network by means of “hyperlinks”—ie, references to other resources on the network that users can visit directly from the document they are reading. As conceived, the web is simply another service—albeit a very important one—running on top of the internet.
Apart from coming up with the idea for sharing information embedded with hypertext links over the internet, to make it happen Mr Berners-Lee (subsequently knighted for his efforts) had to create the first web browser-editor, the first web server, and the first version of the hypertext mark-up language (HTML), which would become the primary means for publishing information on the web. Within a year or two of the web’s introduction, software packages such as Viola, Cello and Mosaic had made it possible for users to browse the web graphically—by clicking on highlighted hyperlinks in web pages and being redirected to yet other web pages, and so on.
It is fair to say that, without the internet, the web would not have existed—at least, not in the form we know it today. And without the web, the internet would have remained essentially a tool for geeks and professionals. No doubt, e-mail would have continued to flourish without the web: it was one of the internet’s earliest applications. So would news groups, bulletin boards, instant messaging and listservs. In due course, internet telephony applications like Skype and even streaming video services similar to Hulu or YouTube would have emerged as well. But users would have had to master the vagaries of Archie, Finger, Gopher, Telnet, Veronica and WAIS (don’t even ask). Thanks to the web’s ease of navigation and the richness of its HTML formatting language, most of these arcane internet tools have gone the way of the dodo.
No question that, over the past 20 years, the web has brought numerous benefits. But it has had its dark side, too. Cybercrime has become prevalent as thieves, hucksters, predators, child pornographers, terrorists, drug cartels and even foreign powers have used the anonymity of the so-called “deep web” to perpetrate crimes. In his pioneering study in 2001, Michael Bergman, a semantics-search-engine whiz based in Iowa, reckoned there was 400 to 550 times more information lurking underground in the deep web than on the surface in the public web. Information in the deep web lay hidden from Google’s crawlers by residing behind password-protected firewalls or requiring admission forms to be completed manually to gain access. By Mr Bergman’s estimate, the deep web contained some 7,500 terabytes of information, compared with a mere 19 terabytes in the public web at the time. Put another way, search engines were indexing less than 0.25% of the web pages available.
Things are probably no different today. By and large, though, the bulk of information in such hidden repositories is legitimate, stashed there by private companies, research institutions and government agencies for security reasons. “There’s a lot or legitimate and valuable content in the deep web,” says Juliana Freire, the former leader of a University of Utah project called DeepPeep. Even so, the fact that there is vastly more information on the web that is inaccessible, compared with what is open to public view, gives one pause for thought.
On balance, the world is grateful for what the web has wrought. Despite their cavalier attitudes to privacy, websites like Facebook, Twitter, Tumblr and Foursquare have changed the way a whole generation of people communicates—creating new ways to make friends, find old acquaintances, socialise online and pursue common interests. Business sites like LinkedIn help them further their careers. YouTube and Flickr let enthusiasts share their home videos and snap shots with millions of others. Online dating sites such as Match, with its algorithms for compatibility, have fostered meaningful relationships for many a lonely heart.
From Amazon to Zappos, online retailing sites have taken the drudgery out of shopping, allowing goods to be bought with the click of a mouse at home. E-Bay lets people sell those they no longer want. Meanwhile, music-streaming sites like Spotify have opened millions of ears to melodies they might never otherwise have heard.
At a keystroke, it has become possible to find all sorts of obscure information, thanks to Google, Bing, Ask and other search engines. Wikipedia may not be the most reliable of sources, but at least it provides a quick run-down on practically anything you need to know in a hurry. Compared with printed encyclopaedias and public libraries, the web has democratised the collected wisdom of ages, and redistributed it in a way unimaginable a few decades ago. Meanwhile, people no longer have to wait for newspapers to be delivered in the morning, or for broadcasters to assemble their news shows. Web pages, tweets and blogs deliver the news as it happens.
Few would deny that such services have made the world a smarter, livelier, more interesting place. But while the news travels faster than ever courtesy of the web, so do lies, hyperbole and distortions. All those with access to the web now have a voice to air their grievances, vent their anger, parade their biases, push the boundaries of decency, spill the beans. The gatekeepers have gone.
When WikiLeaks dumps massive volumes of diplomatic correspondence stolen from government computers on its website, it is not engaging in some heroic act of free speech, nor bringing specific cases of wrongdoing to the public’s attention. In a deliberate and calculated manner, it is making the world a more dangerous place. In dealing with issues of privacy, public safety and national security, governments have every right to discuss such matters behind closed doors—indeed, we insist they do. It is dangerously naïve to argue otherwise.
Meanwhile, for every online job the web has created, several others have been lost in the bricks-and-mortar world. And unlike the latter, many of the new online jobs lie beyond a country’s shores. Likewise, for all the new freedoms and certainties the web has created, numerous old ones have disappeared. Consider copyright. Once it provided authors, artists and musicians with a living, and ensured that the fourth estate could do its job of rooting out injustice and corruption. Illegal downloading from the web, and the widespread erosion of copyright protection generally, has put paid to much of that.
You have to wonder whether something is wrong when so many people spend so much of their time these days in front of a computer screen tapping away on a keyboard, instead of going out into the real world to experience life’s actual (as opposed to virtual) adventures. Ironically, for all the labour-saving tools the web has given us, and all the personal connections it has allowed us to make, we seem to have become lonelier and more isolated than ever. That is a rather sorry state of affairs.
Aug 12th 2011, 10:37 by N.V. | LOS ANGELES
IT IS always a little disconcerting to realise a generation has grown up never knowing what it was like to manage without something that is taken for granted today. A case in point: the World Wide Web (WWW), which celebrated the 20th anniversary of its introduction last Saturday. It is no exaggeration to say that not since the invention of the printing press has a new media technology altered the way people think, work and play quite so extensively. With the web having been so thoroughly embraced socially, politically and economically, the world has become an entirely different place from what it was just two decades ago. Whether the web has made it a better place or a worse one is for readers to decide.
It was on August 6th, 1991, that Tim Berners-Lee, a British physicist at the European Organisation for Nuclear Research (CERN), in Geneva, created the first-ever web page—a summary of his WWW project along with explanations to help visitors build websites of their own and to search the web for information. No screen-shots survive of the original web page; its original address simply redirects visitors to a contemporary site providing details of the project’s early days at CERN.
First, however, a few things to get straight. The web is not to be confused with the internet—a global system of interconnected networks developed in the 1960s, originally for academic and government researchers in America. The internet sends information as discrete packets of data using a suite of protocols known as TCP/IP. The genius of the system is that the data tell the network where they want to go, instead of the network telling the data where they are being sent. All networks adopting this procedure—no matter where they are or how they actually function—are then reduced effectively to the same bare essentials, allowing them to interconnect and exchange data seamlessly.
The web, by contrast, is simply a way of organising information on a computer network by means of “hyperlinks”—ie, references to other resources on the network that users can visit directly from the document they are reading. As conceived, the web is simply another service—albeit a very important one—running on top of the internet.
Apart from coming up with the idea for sharing information embedded with hypertext links over the internet, to make it happen Mr Berners-Lee (subsequently knighted for his efforts) had to create the first web browser-editor, the first web server, and the first version of the hypertext mark-up language (HTML), which would become the primary means for publishing information on the web. Within a year or two of the web’s introduction, software packages such as Viola, Cello and Mosaic had made it possible for users to browse the web graphically—by clicking on highlighted hyperlinks in web pages and being redirected to yet other web pages, and so on.
It is fair to say that, without the internet, the web would not have existed—at least, not in the form we know it today. And without the web, the internet would have remained essentially a tool for geeks and professionals. No doubt, e-mail would have continued to flourish without the web: it was one of the internet’s earliest applications. So would news groups, bulletin boards, instant messaging and listservs. In due course, internet telephony applications like Skype and even streaming video services similar to Hulu or YouTube would have emerged as well. But users would have had to master the vagaries of Archie, Finger, Gopher, Telnet, Veronica and WAIS (don’t even ask). Thanks to the web’s ease of navigation and the richness of its HTML formatting language, most of these arcane internet tools have gone the way of the dodo.
No question that, over the past 20 years, the web has brought numerous benefits. But it has had its dark side, too. Cybercrime has become prevalent as thieves, hucksters, predators, child pornographers, terrorists, drug cartels and even foreign powers have used the anonymity of the so-called “deep web” to perpetrate crimes. In his pioneering study in 2001, Michael Bergman, a semantics-search-engine whiz based in Iowa, reckoned there was 400 to 550 times more information lurking underground in the deep web than on the surface in the public web. Information in the deep web lay hidden from Google’s crawlers by residing behind password-protected firewalls or requiring admission forms to be completed manually to gain access. By Mr Bergman’s estimate, the deep web contained some 7,500 terabytes of information, compared with a mere 19 terabytes in the public web at the time. Put another way, search engines were indexing less than 0.25% of the web pages available.
Things are probably no different today. By and large, though, the bulk of information in such hidden repositories is legitimate, stashed there by private companies, research institutions and government agencies for security reasons. “There’s a lot or legitimate and valuable content in the deep web,” says Juliana Freire, the former leader of a University of Utah project called DeepPeep. Even so, the fact that there is vastly more information on the web that is inaccessible, compared with what is open to public view, gives one pause for thought.
On balance, the world is grateful for what the web has wrought. Despite their cavalier attitudes to privacy, websites like Facebook, Twitter, Tumblr and Foursquare have changed the way a whole generation of people communicates—creating new ways to make friends, find old acquaintances, socialise online and pursue common interests. Business sites like LinkedIn help them further their careers. YouTube and Flickr let enthusiasts share their home videos and snap shots with millions of others. Online dating sites such as Match, with its algorithms for compatibility, have fostered meaningful relationships for many a lonely heart.
From Amazon to Zappos, online retailing sites have taken the drudgery out of shopping, allowing goods to be bought with the click of a mouse at home. E-Bay lets people sell those they no longer want. Meanwhile, music-streaming sites like Spotify have opened millions of ears to melodies they might never otherwise have heard.
At a keystroke, it has become possible to find all sorts of obscure information, thanks to Google, Bing, Ask and other search engines. Wikipedia may not be the most reliable of sources, but at least it provides a quick run-down on practically anything you need to know in a hurry. Compared with printed encyclopaedias and public libraries, the web has democratised the collected wisdom of ages, and redistributed it in a way unimaginable a few decades ago. Meanwhile, people no longer have to wait for newspapers to be delivered in the morning, or for broadcasters to assemble their news shows. Web pages, tweets and blogs deliver the news as it happens.
Few would deny that such services have made the world a smarter, livelier, more interesting place. But while the news travels faster than ever courtesy of the web, so do lies, hyperbole and distortions. All those with access to the web now have a voice to air their grievances, vent their anger, parade their biases, push the boundaries of decency, spill the beans. The gatekeepers have gone.
When WikiLeaks dumps massive volumes of diplomatic correspondence stolen from government computers on its website, it is not engaging in some heroic act of free speech, nor bringing specific cases of wrongdoing to the public’s attention. In a deliberate and calculated manner, it is making the world a more dangerous place. In dealing with issues of privacy, public safety and national security, governments have every right to discuss such matters behind closed doors—indeed, we insist they do. It is dangerously naïve to argue otherwise.
Meanwhile, for every online job the web has created, several others have been lost in the bricks-and-mortar world. And unlike the latter, many of the new online jobs lie beyond a country’s shores. Likewise, for all the new freedoms and certainties the web has created, numerous old ones have disappeared. Consider copyright. Once it provided authors, artists and musicians with a living, and ensured that the fourth estate could do its job of rooting out injustice and corruption. Illegal downloading from the web, and the widespread erosion of copyright protection generally, has put paid to much of that.
You have to wonder whether something is wrong when so many people spend so much of their time these days in front of a computer screen tapping away on a keyboard, instead of going out into the real world to experience life’s actual (as opposed to virtual) adventures. Ironically, for all the labour-saving tools the web has given us, and all the personal connections it has allowed us to make, we seem to have become lonelier and more isolated than ever. That is a rather sorry state of affairs.
Wednesday, August 3, 2011
Medicines bright future
by Vivek Wadhwa • July 28, 2011
Internet and social media are capturing the public’s attention, but some of the most significant advances today are happening in medicine. Technology and medicine are converging in new ways to make possible the types of innovations that could be seen on “Star Trek.” Consider this: We spend the majority of our health-care dollars on treating chronic diseases. Technological advances will enable us to shift those investments into improving our health and preventing disease.
My colleague Daniel Kraft is a physician who chairs the medicine track and heads the FutureMed Program for Singularity University. The Silicon Valley-based university teaches business executives, technologists and government leaders about “exponential technologies.” These are inventions in fields that experience faster growth than average — such as robotics, nanotechnology and artificial intelligence. Singularity University’s founders believe that these technologies, when combined in new ways, could solve some of the world’s major problems, such as poverty, hunger, energy shortages and disease.
Here are the three major trends Kraft sees in health and medicine:
Medicine goes mobile and goes home.
Many aspects of health care and disease management will become cheaper and more effective as our mobile phones and other, similar technology platforms become smaller, Web-enabled and interconnected. In essence, these smartphones will become health platforms. They already contain a wide array of sensors, including an accelerometer that can serve as a pedometer, a camera that can photograph external ailments and transmit them for analysis, and a global positioning system (GPS) that can track our locations.
Developers are also looking beyond the smartphone when it comes to developing these new technologies.
For example, Fitbit is a clip-on, Web-integrated device that helps track how many calories you burn during the day; Zeo is a wireless headband that helps you track the quality and duration of your sleep. Other devices, such as the Basis monitor, which is still in development, can keep track of heart rates and movement. Meanwhile, an array of devices, including scales, blood pressure monitors and blood glucose monitors, are becoming Wi-Fi-enabled. These technologies, when they are connected to electronic and personal health records and to social networks, can create powerful feedback loops with friends, and provide clinicians with better information for helping their patients.
Expect to see products that keep track of your health by connecting to global health-care systems similar to the in-car assistance program OnStar. These will incorporate ubiquitous sensors embedded in toothbrushes and clothes, for example. They may even analyze our bathroom visits and food intake. They will likely use artificial-intelligence to constantly monitor our health data, predict disease and summon help in the event we fall ill.
Personalization: From genomics to proteomics
We learned how to sequence the genome a decade ago, and doing it cost billions of dollars. Companies like 23andMe are now offering partial DNA genotyping for as low as $99 (with a one-year subscription to their information service). Expect prices to continue to rapidly decline to that of a regular blood test.
This means that it is now becoming more affordable to compare one person’s DNA with another’s, learn what diseases those with similar genetics have had and discover how effective different medications or other interventions were in treating them. Imagine doing a Google search on specific genes to find others like you and learn their abilities, allergies, likes and dislikes and what diseases they are predisposed to. That future is closer than you may think.
This opens up an era of crowd-sourced, data-driven, participatory, genomics-based medicine. Today, medicines are prescribed on a “one size fits all” basis. When a particular medication causes a significant negative reaction with a small part of the population, it is prevented from being available to anyone. In the future, expect to see doctors prescribing and selecting the most patient-appropriate medicines based on a person’s DNA (the field of “pharmacogenomics”).
Regenerative medicine
Physicians have been conducting adult stem-cell therapy for more than 40 years in the field of bone-marrow transplantation, which involves transplanting stem cells that become red blood cells. Adult stem cells are now being applied in a variety of arenas, from orthopedics to cardiovascular therapy. The first trials using cells derived from embryonic stem cells were for acute spinal cord injury and started within the last year. But embryonic stem cells have raised ethical and moral controversy even though the research remains critical for future progress.
The good news is a new type of cell, induced pluripotent stem cells, which will enable the generation of personalized stem cell lines for use in diagnostics, prognosis or potentially for therapy in the same patient. IPS cells can replace embryonic stem cells for some applications and are, for example, being used to develop neurons from patients with ALS/Lou Gehrig’s disease in order to better understand the disease and develop new therapies.
Tissue engineering and 3-D printing technologies are also beginning to merge. The combination of the two technologies could lead to an era of personalized organ generation. Indeed, earlier this month, surgeons in Sweden carried out the world’s first synthetic organ transplant— a synthetic trachea/windpipe structure created and seeded with the patient’s own progenitor cells.
These developments are just the beginning. There will undoubtedly be regulatory, reimbursement and other challenges. And there will be heated debates about ethics and morals. But it won’t be long before we are using devices similar to the “Star Trek” tricorder and synthesizing our medications.
Internet and social media are capturing the public’s attention, but some of the most significant advances today are happening in medicine. Technology and medicine are converging in new ways to make possible the types of innovations that could be seen on “Star Trek.” Consider this: We spend the majority of our health-care dollars on treating chronic diseases. Technological advances will enable us to shift those investments into improving our health and preventing disease.
My colleague Daniel Kraft is a physician who chairs the medicine track and heads the FutureMed Program for Singularity University. The Silicon Valley-based university teaches business executives, technologists and government leaders about “exponential technologies.” These are inventions in fields that experience faster growth than average — such as robotics, nanotechnology and artificial intelligence. Singularity University’s founders believe that these technologies, when combined in new ways, could solve some of the world’s major problems, such as poverty, hunger, energy shortages and disease.
Here are the three major trends Kraft sees in health and medicine:
Medicine goes mobile and goes home.
Many aspects of health care and disease management will become cheaper and more effective as our mobile phones and other, similar technology platforms become smaller, Web-enabled and interconnected. In essence, these smartphones will become health platforms. They already contain a wide array of sensors, including an accelerometer that can serve as a pedometer, a camera that can photograph external ailments and transmit them for analysis, and a global positioning system (GPS) that can track our locations.
Developers are also looking beyond the smartphone when it comes to developing these new technologies.
For example, Fitbit is a clip-on, Web-integrated device that helps track how many calories you burn during the day; Zeo is a wireless headband that helps you track the quality and duration of your sleep. Other devices, such as the Basis monitor, which is still in development, can keep track of heart rates and movement. Meanwhile, an array of devices, including scales, blood pressure monitors and blood glucose monitors, are becoming Wi-Fi-enabled. These technologies, when they are connected to electronic and personal health records and to social networks, can create powerful feedback loops with friends, and provide clinicians with better information for helping their patients.
Expect to see products that keep track of your health by connecting to global health-care systems similar to the in-car assistance program OnStar. These will incorporate ubiquitous sensors embedded in toothbrushes and clothes, for example. They may even analyze our bathroom visits and food intake. They will likely use artificial-intelligence to constantly monitor our health data, predict disease and summon help in the event we fall ill.
Personalization: From genomics to proteomics
We learned how to sequence the genome a decade ago, and doing it cost billions of dollars. Companies like 23andMe are now offering partial DNA genotyping for as low as $99 (with a one-year subscription to their information service). Expect prices to continue to rapidly decline to that of a regular blood test.
This means that it is now becoming more affordable to compare one person’s DNA with another’s, learn what diseases those with similar genetics have had and discover how effective different medications or other interventions were in treating them. Imagine doing a Google search on specific genes to find others like you and learn their abilities, allergies, likes and dislikes and what diseases they are predisposed to. That future is closer than you may think.
This opens up an era of crowd-sourced, data-driven, participatory, genomics-based medicine. Today, medicines are prescribed on a “one size fits all” basis. When a particular medication causes a significant negative reaction with a small part of the population, it is prevented from being available to anyone. In the future, expect to see doctors prescribing and selecting the most patient-appropriate medicines based on a person’s DNA (the field of “pharmacogenomics”).
Regenerative medicine
Physicians have been conducting adult stem-cell therapy for more than 40 years in the field of bone-marrow transplantation, which involves transplanting stem cells that become red blood cells. Adult stem cells are now being applied in a variety of arenas, from orthopedics to cardiovascular therapy. The first trials using cells derived from embryonic stem cells were for acute spinal cord injury and started within the last year. But embryonic stem cells have raised ethical and moral controversy even though the research remains critical for future progress.
The good news is a new type of cell, induced pluripotent stem cells, which will enable the generation of personalized stem cell lines for use in diagnostics, prognosis or potentially for therapy in the same patient. IPS cells can replace embryonic stem cells for some applications and are, for example, being used to develop neurons from patients with ALS/Lou Gehrig’s disease in order to better understand the disease and develop new therapies.
Tissue engineering and 3-D printing technologies are also beginning to merge. The combination of the two technologies could lead to an era of personalized organ generation. Indeed, earlier this month, surgeons in Sweden carried out the world’s first synthetic organ transplant— a synthetic trachea/windpipe structure created and seeded with the patient’s own progenitor cells.
These developments are just the beginning. There will undoubtedly be regulatory, reimbursement and other challenges. And there will be heated debates about ethics and morals. But it won’t be long before we are using devices similar to the “Star Trek” tricorder and synthesizing our medications.
Thursday, July 28, 2011
5 real-world uses of big data
5 real-world uses of big data
By David Smith Jul. 17, 2011,
http://gigaom.com/cloud/5-real-world-uses-of-big-data/
In the past year, big data has emerged as one of the most closely watched trends in IT. Organizations today are generating more data in a single day than that the entire Internet was generated as recently as 2000. The explosion of “big data”–much of it in complex and unstructured formats–has presented companies with a tremendous opportunity to leverage their data for better business insights through analytics.
Wal-Mart was one of the early pioneers in this field, using predictive analytics to better identify customer preferences on a regional basis and stock their branch locations accordingly. It was an incredibly effective tactic that yielded strong ROI and allowed them to separate themselves from the retail pack. Other industries took notice of Wal-Mart’s tactics — and the success they gleaned from processing and analyzing their data — and began to employ the same tactics.
While data analytics was once considered a competitive advantage, it’s increasingly being seen as a necessity for enterprises–to the point that those that aren’t employing some kind of analytics are seen to be at a competitive disadvantage. Driven by the rise of modern statistical languages like R, there’s been a surge in enterprises hiring data analysts–which has in turn given rise to the larger data science movement. Data is a huge asset for enterprises, and they’re beginning to treat it accordingly.
For all the talk about the need to effectively analyze your data, though, there’s been relatively little written about how organizations are using data to achieve actionable results. With that in mind, here are five use cases involving analyses of large data sets that brought about valuable new insight:
· NYU Ph.D. student conducts comprehensive analysis of Wikileaks data for greater insight into the Afghanistan conflict: Drew Conway is a Ph.D. student at New York University who also runs the popular, data-centric Zero Intelligence Agents blog. Last year, he analyzed several terabytes worth of Wikileaks data to determine key trends around U.S. and coalition troop activity in Afghanistan. Conway used the R statistics language first to sort the overall flow of information in the five Afghanistan regions, categorized by type of activity (enemy, neutral, ally), and then to identify key patterns from the data. His findings gave credence to a number of popular theories on troop activity there–that there were seasonal spikes in conflict with the Taliban and most coalition activity stemmed from the “Ring Road” that surrounds the capitol, Kabul, to name a few. Through this work, Conway helped the public glean additional insight into the state of affairs for American troops in Afghanistan and the high degree of combat they experienced there.
· International non-profit organization uses data science to confirm Guatemalan genocide: Benetech is a non-profit organization that has been contracted by the likes of Amnesty International and Human Rights Watch to address controversial geopolitical issues through data science. Several years ago, they were contracted to analyze a massive trove of secret files from Guatemala’s National Police that were discovered in an abandoned munitions depot. The documents, of which there were over 80 million, detailed state-sanctioned arrests and disappearances that occurred during the country’s decades-long civil conflict that occurred between 1960 and 1996. There had long been whispers of a genocide against the country’s Mayan population during that period, but no hard evidence had previously emerged to verify these claims. Benetech’s scientists set up a random sample of the data to analyze its content for details on missing victims from the decades-long conflict. After exhaustive analysis, Benetech was able to come to the grim conclusion that genocide had in fact occurred in Guatemala. In the process, they were able to give closure to grieving relatives that had wondered about the fate of their loved ones for decades.
· Statistician develops innovative metrics tracking for baseball players, gains widespread recognition and a job with the Boston Red Sox: Bill James (he of Moneyball fame) is a well-known figure in the world of both baseball and statistics at this point, but that has not always been the case. James, a classically trained statistician and avid baseball fan, began publishing research in the early 1970s that took a more quantitative approach to analyzing the performance of baseball players. His work focused on providing specific metrics that could empirically support or refute specific claims about players, be it the amount of runs they contributed to in a given season or how their defensive abilities contributed to or detracted from a team’s success. James’ approach became known as sabermetrics and has since expanded to incorporate a wide range of quantitative analyses for measuring baseball metrics. Over time, sabermetrics has gained wide recognition in baseball to the point that it’s now employed by all 30 Major League Baseball teams for tracking player metrics. In 2003, James was named Senior Advisor of Baseball Operations by the Boston Red Sox, a position he holds to this day.
· U.S. government uses R to coordinate disaster response to BP oil spill: In the early days of last year’s Deepwater Horizon disaster, the flow of oil rate from the spill was of primary concern; estimating it accurately was key to coordinating the scale and scope of the U.S. government’s response to the emergency. The National Institute of Science and Technology (NIST) was charged with making sense of the varying estimates that existed from both BP and independent third-parties. To do so, NIST used the open source R language to run an uncertainty analysis that harmonized the estimates from various sources to come up with actionable intelligence around which disaster response efforts could be coordinated.
· Medical diagnostics company analyzes millions of lines of data to develop first non-intrusive test for predicting coronary artery disease: CardioDX is a relatively small, Palo Alto, Calif.-based company that performs genomic research. One of their major initiatives over the past several years was developing a predictive test that could identify coronary artery disease in its most nascent stages. To do so, researchers at the company analyzed over 100 million gene samples to ultimately identify the 23 primary predictive genes for coronary artery disease. The resulting test, known as the “Corus CAD Test,” was recognized as on of the “Top Ten Medical Breakthroughs of 2010” by TIME Magazine.
These are but a few brief examples of the exciting work that’s being undertaken in the rapidly growing discipline of data science. More and more, data analysis is being relied on to provide context for critical business decisions, a trend that promises to increase as data sets grow larger and more complex and scientists continue to push the limits of statistical innovation.
David Smith is vice president of community at Revolution Analytics, a company founded in 2007 to foster R analytics by creating programs to make it easier for data scientists to analyze large amounts of data.
By David Smith Jul. 17, 2011,
http://gigaom.com/cloud/5-real-world-uses-of-big-data/
In the past year, big data has emerged as one of the most closely watched trends in IT. Organizations today are generating more data in a single day than that the entire Internet was generated as recently as 2000. The explosion of “big data”–much of it in complex and unstructured formats–has presented companies with a tremendous opportunity to leverage their data for better business insights through analytics.
Wal-Mart was one of the early pioneers in this field, using predictive analytics to better identify customer preferences on a regional basis and stock their branch locations accordingly. It was an incredibly effective tactic that yielded strong ROI and allowed them to separate themselves from the retail pack. Other industries took notice of Wal-Mart’s tactics — and the success they gleaned from processing and analyzing their data — and began to employ the same tactics.
While data analytics was once considered a competitive advantage, it’s increasingly being seen as a necessity for enterprises–to the point that those that aren’t employing some kind of analytics are seen to be at a competitive disadvantage. Driven by the rise of modern statistical languages like R, there’s been a surge in enterprises hiring data analysts–which has in turn given rise to the larger data science movement. Data is a huge asset for enterprises, and they’re beginning to treat it accordingly.
For all the talk about the need to effectively analyze your data, though, there’s been relatively little written about how organizations are using data to achieve actionable results. With that in mind, here are five use cases involving analyses of large data sets that brought about valuable new insight:
· NYU Ph.D. student conducts comprehensive analysis of Wikileaks data for greater insight into the Afghanistan conflict: Drew Conway is a Ph.D. student at New York University who also runs the popular, data-centric Zero Intelligence Agents blog. Last year, he analyzed several terabytes worth of Wikileaks data to determine key trends around U.S. and coalition troop activity in Afghanistan. Conway used the R statistics language first to sort the overall flow of information in the five Afghanistan regions, categorized by type of activity (enemy, neutral, ally), and then to identify key patterns from the data. His findings gave credence to a number of popular theories on troop activity there–that there were seasonal spikes in conflict with the Taliban and most coalition activity stemmed from the “Ring Road” that surrounds the capitol, Kabul, to name a few. Through this work, Conway helped the public glean additional insight into the state of affairs for American troops in Afghanistan and the high degree of combat they experienced there.
· International non-profit organization uses data science to confirm Guatemalan genocide: Benetech is a non-profit organization that has been contracted by the likes of Amnesty International and Human Rights Watch to address controversial geopolitical issues through data science. Several years ago, they were contracted to analyze a massive trove of secret files from Guatemala’s National Police that were discovered in an abandoned munitions depot. The documents, of which there were over 80 million, detailed state-sanctioned arrests and disappearances that occurred during the country’s decades-long civil conflict that occurred between 1960 and 1996. There had long been whispers of a genocide against the country’s Mayan population during that period, but no hard evidence had previously emerged to verify these claims. Benetech’s scientists set up a random sample of the data to analyze its content for details on missing victims from the decades-long conflict. After exhaustive analysis, Benetech was able to come to the grim conclusion that genocide had in fact occurred in Guatemala. In the process, they were able to give closure to grieving relatives that had wondered about the fate of their loved ones for decades.
· Statistician develops innovative metrics tracking for baseball players, gains widespread recognition and a job with the Boston Red Sox: Bill James (he of Moneyball fame) is a well-known figure in the world of both baseball and statistics at this point, but that has not always been the case. James, a classically trained statistician and avid baseball fan, began publishing research in the early 1970s that took a more quantitative approach to analyzing the performance of baseball players. His work focused on providing specific metrics that could empirically support or refute specific claims about players, be it the amount of runs they contributed to in a given season or how their defensive abilities contributed to or detracted from a team’s success. James’ approach became known as sabermetrics and has since expanded to incorporate a wide range of quantitative analyses for measuring baseball metrics. Over time, sabermetrics has gained wide recognition in baseball to the point that it’s now employed by all 30 Major League Baseball teams for tracking player metrics. In 2003, James was named Senior Advisor of Baseball Operations by the Boston Red Sox, a position he holds to this day.
· U.S. government uses R to coordinate disaster response to BP oil spill: In the early days of last year’s Deepwater Horizon disaster, the flow of oil rate from the spill was of primary concern; estimating it accurately was key to coordinating the scale and scope of the U.S. government’s response to the emergency. The National Institute of Science and Technology (NIST) was charged with making sense of the varying estimates that existed from both BP and independent third-parties. To do so, NIST used the open source R language to run an uncertainty analysis that harmonized the estimates from various sources to come up with actionable intelligence around which disaster response efforts could be coordinated.
· Medical diagnostics company analyzes millions of lines of data to develop first non-intrusive test for predicting coronary artery disease: CardioDX is a relatively small, Palo Alto, Calif.-based company that performs genomic research. One of their major initiatives over the past several years was developing a predictive test that could identify coronary artery disease in its most nascent stages. To do so, researchers at the company analyzed over 100 million gene samples to ultimately identify the 23 primary predictive genes for coronary artery disease. The resulting test, known as the “Corus CAD Test,” was recognized as on of the “Top Ten Medical Breakthroughs of 2010” by TIME Magazine.
These are but a few brief examples of the exciting work that’s being undertaken in the rapidly growing discipline of data science. More and more, data analysis is being relied on to provide context for critical business decisions, a trend that promises to increase as data sets grow larger and more complex and scientists continue to push the limits of statistical innovation.
David Smith is vice president of community at Revolution Analytics, a company founded in 2007 to foster R analytics by creating programs to make it easier for data scientists to analyze large amounts of data.
Tuesday, July 19, 2011
PM-ISE Releases the 2011 ISE Annual Report to the Congress
The PM-ISE has officially released its 2011 ISE Annual Report to the Congress and we are proud of the information sharing success stories featured in the Report – stories that describe the outstanding accomplishments of our mission partners across the federal, state, local, and tribal governments, the private sector, and foreign allies.
The Annual Report is required by law to provide the Congress “a progress report on the extent to which the ISE has been implemented.”[1] The Report highlights major ISE activities since July 2010 and is organized around five themes:
Strengthening Management and Oversight - The Annual Report describes the work of the Information Sharing and Access Interagency Policy Committee (ISA IPC) and its sub-committees and working groups; of particular note, the Report highlights how these bodies expanded to include representatives of non-federal organizations and are reaching out to engage the private sector in developing the ISE, as well.
Improving Information Sharing Activities - Among the many activities presented, the Report describes how the Nationwide Suspicious Activity Reporting Initiative has made substantial progress toward streamlining reporting and analysis within fusion centers by implementing new standards, policies, and processes. Another notable interagency effort involved the Baseline Capabilities Assessment, during which federal, state, and local officials completed the first nationwide, in-depth assessment of fusion centers to baseline their capabilities.
Establishing Standards for Responsible Information Sharing and Protection - Standards are critical to powering the ISE, and so the Report describes the efforts by the PM-ISE, its mission partners, and standards organizations to identify the best existing standards for reuse and implementation across the ISE.
Enabling Assured Interoperability across Networks - The Report details the tremendous progress made toward implementing a Simplified Sign On that will enable federal, state, local, and tribal law enforcement officers and analysts to more easily access a rich variety of data services provided by Assured Sensitive but Unclassified (SBU) networks. The Report also describes similar efforts for classified information sharing.
Enhancing Privacy, Civil Rights, and Civil Liberties Protections - Balancing the need for national security with the need to protect privacy and civil liberties, the Report provides information on policies and training activities designed to enhance these protections.
These are only a few of the activities that are helping the nation build a robust information sharing environment. And, while the Annual Report is primarily focused on terrorism-related initiatives, it also describes mission partner accomplishments that may not have been developed explicitly to support CT, but which may ultimately become best practices for information sharing and collaboration government-wide.
The Annual Report is required by law to provide the Congress “a progress report on the extent to which the ISE has been implemented.”[1] The Report highlights major ISE activities since July 2010 and is organized around five themes:
Strengthening Management and Oversight - The Annual Report describes the work of the Information Sharing and Access Interagency Policy Committee (ISA IPC) and its sub-committees and working groups; of particular note, the Report highlights how these bodies expanded to include representatives of non-federal organizations and are reaching out to engage the private sector in developing the ISE, as well.
Improving Information Sharing Activities - Among the many activities presented, the Report describes how the Nationwide Suspicious Activity Reporting Initiative has made substantial progress toward streamlining reporting and analysis within fusion centers by implementing new standards, policies, and processes. Another notable interagency effort involved the Baseline Capabilities Assessment, during which federal, state, and local officials completed the first nationwide, in-depth assessment of fusion centers to baseline their capabilities.
Establishing Standards for Responsible Information Sharing and Protection - Standards are critical to powering the ISE, and so the Report describes the efforts by the PM-ISE, its mission partners, and standards organizations to identify the best existing standards for reuse and implementation across the ISE.
Enabling Assured Interoperability across Networks - The Report details the tremendous progress made toward implementing a Simplified Sign On that will enable federal, state, local, and tribal law enforcement officers and analysts to more easily access a rich variety of data services provided by Assured Sensitive but Unclassified (SBU) networks. The Report also describes similar efforts for classified information sharing.
Enhancing Privacy, Civil Rights, and Civil Liberties Protections - Balancing the need for national security with the need to protect privacy and civil liberties, the Report provides information on policies and training activities designed to enhance these protections.
These are only a few of the activities that are helping the nation build a robust information sharing environment. And, while the Annual Report is primarily focused on terrorism-related initiatives, it also describes mission partner accomplishments that may not have been developed explicitly to support CT, but which may ultimately become best practices for information sharing and collaboration government-wide.
FT: A brave new networked world
July 18, 2011 11:15 pm
A brave new networked world
By Philip Delves Broughton
http://www.ft.com/intl/cms/s/0/2fe38490-b176-11e0-9444-00144feab49a.html#axzz1SSrsjjWo
We are under siege by social networks, from Facebook to LinkedIn to school, university and even corporate alumni organisations, which are ever more aggressive and sophisticated in their networking efforts.
Facebook has more than 750m users, LinkedIn 100m, and Twitter is handling 1bn tweets a week. Technology-driven social networks have been credited with propelling the revolutionaries of the Arab spring.
Marketers and venture investors salivate over any company promising to identify and assemble networks of like-minded consumers. Social network analysis software has become a fast-growing sector of IT services. IBM alone has spent $11bn in the past five years buying makers of such software.
A brave new networked world
By Philip Delves Broughton
http://www.ft.com/intl/cms/s/0/2fe38490-b176-11e0-9444-00144feab49a.html#axzz1SSrsjjWo
We are under siege by social networks, from Facebook to LinkedIn to school, university and even corporate alumni organisations, which are ever more aggressive and sophisticated in their networking efforts.
Facebook has more than 750m users, LinkedIn 100m, and Twitter is handling 1bn tweets a week. Technology-driven social networks have been credited with propelling the revolutionaries of the Arab spring.
Marketers and venture investors salivate over any company promising to identify and assemble networks of like-minded consumers. Social network analysis software has become a fast-growing sector of IT services. IBM alone has spent $11bn in the past five years buying makers of such software.
But there are sceptics questioning the power of these networks. Malcolm Gladwell wrote in The New Yorker last year that the impact of new forms of communication in fomenting political change was exaggerated. He distinguished between the strong ties that bind groups of revolutionaries and the weak ties that link 1m Facebook fans.
“The platforms of social media are built around weak ties,” he wrote. “Twitter is a way of following (or being followed by) people you may never have met. Facebook is a tool for efficiently managing your acquaintances, for keeping up with the people you would not otherwise be able to stay in touch with. That’s why you can have a thousand ‘friends’ on Facebook, as you never could in real life.”
While the significance of social networks for political activists may be open to question, companies are starting to find real value in mapping and analysing the strength and frequency of connections between employees and customers, and their behaviour.
Social network analysis is being used to measure job performance and forecast turnover, to rate employees for promotion, monitor their ethical standards and improve the systems for collaboration. It is now a standard diagnostic and prescriptive tool for management consultants advising companies.
By measuring who talks to whom, when and for how long, companies can uncover hidden stars. They can develop an index that reveals where real power lies – and it may not be with the people who hold the grandest titles. When the US was tracking Saddam Hussein it mapped the networks of his former chauffeurs, which led to his hideout. The Iraqi elite had no idea where he was.
Businesses also use social network analysis to help categorise customers. Nike tracks bloggers to find out whose posts most influence sales of their shoes. Telecoms companies seek out the “influencers”, those thrifty types who shop around for the best plan and take their Facebook friends and Twitter followers with them when they switch.
Rob Cross is a professor of management at the University of Virginia’s McIntire School of Commerce and a consultant on corporate social networks to companies ranging from American Express to Intel. Through web-based surveys, he maps “who creates enthusiasm within organisations and who drains it. This turns out to be wildly predictive of success or failure in innovation”.
Prof Cross also finds that social networks can create another level of work for employees. “Due to the recession, people’s workloads and spans of accountability have increased, the tools of collaboration have multiplied, and we’re seeing people can’t keep up with collaborative demands any more,” he says.
Social media tools have only made this worse. Much of his work is therefore about reducing unnecessary collaboration. Organisations can benefit from protecting key people, such as research scientists or top salespeople, from the deluge of fruitless networking and information sharing.
Social network sites, Prof Cross says, are good for creating interest groups or sharing tactical information, but in situations where you need to solve a problem it is necessary to resort to old-fashioned means of developing trust and sharing information.
At agribusiness Monsanto, executives spread across the world who were forced to implement a new global transaction system were much more productive, more quickly, when they had previous experience of collaborating.
Another useful aspect of social network sites is in reactivating dormant ties. In research published in MIT Sloan Management Review, Daniel Levin, Jorge Walter and Keith Murnighan have shown that we underestimate the power of our dormant relationships.
People we once knew well but have not seen for a while turn out to be delighted to hear from us. They also have novel insights and are happy to help. Social network sites make these dormant relationships easier to rediscover and resume, but they are only a start.
“People who haven’t seen each other in a while are delighted to e-mail, until something goes beyond expectation in a negative way,” says Prof Murnighan. “Then they might realise why the relationship was dormant.”
For substantive interactions, you still need to get on the phone or meet in person. But the lesson of his research into dormant ties, he says, is that “people move on with their lives, but they don’t forget each other. An awful lot of substance remains”.
No amount of e-mailing or Facebook poking can substitute for extended time spent with others.
Lauren Cohen and Christopher Malloy of Harvard Business School have written a series of papers on the continuing importance of old-fashioned ties in investment performance. They found mutual fund managers and sell-side analysts made much better investment returns and recommendations in companies where they had strong university alumni connections.
In the US, they found that before new regulations came into effect in 2000 to limit selective disclosure of corporate information, the return premium from the old school tie was 8.16 per cent a year. Since 2000, it has fallen to zero. But in the UK, where the rules about selective disclosure are less rigorous, the old school tie premium persists.
Prof Cohen says that the premium is explained by the many clubs and networking events laid on by universities and the informal networks and gossip shared among old friends.
People who went to the same university, she says, are “more likely to have met each other or have common acquaintances. They understand what it means if a person belonged to a certain club or participated in a specific study programme. They may know people who hired them previously. All this helps them better assess executives’ potential as leaders and business owners”.
Technology may have made everyone accessible, but it has not yet made all social networks equal.
Harnessing networks
Not all networks are equal but all have their uses. So it is important to identify the differing strength of connections within a network in order to determine how best to use it.
Weak ties Good for forming groups around shared interests, hobbies and projects as well as tactical information sharing. Twitter hashtags and Facebook groups can cluster people with similar interests, but not for long unless strong ties can be developed.
Strong ties Vital for trust-based activities and complex collaboration among remote groups. Monsanto found that executives who had worked together in the past, even though now dispersed around the world, were much more effective at complex, collaborative tasks.
Dormant ties People whom we once knew well are happy to be “reactivated”. They can be great sources of new information and perspectives.
Old school ties Alumni networks still provide access to information which can affect hiring and improve investor returns.
Wednesday, June 29, 2011
WSJ on Big Data: Filtering Profits
Businesses must find ways to transform 'big data' into big money, or risk falling behind their competitors
By Nick Clayton WSJ June 29, 2011
Big data is a term bandied around the technology sector with great ease, but little precision. While exact definitions are hard to come by, what is clear is that the ability to gather, process and store huge amounts of data is unparalleled. The sheer quantity of information and the speed at which it is consumed means conventional methods of handling it are no longer sufficient.
According to analysts IDC, the amount of digital information created and replicated rose by 62% in 2010 to nearly 800,000 petabytes, which, IDC says, would fill a stack of DVDs reaching from the earth to the moon and back. By 2020, that pile of DVDs would stretchhalfway to Mars.
Nick Halstead, CEO of DataSift, a company that specializes in handling massive data, says the New York Stock Exchange produces one terabyte of data a day; Facebook generates in excess of 20 terabytes every day; while the CERN laboratory in Geneva produces more than 40 terabytes a day, or roughly twice the entire text content of the U.S. Library of Congress every day.
In its recent report, "Big data: The next frontier for innovation, competition and productivity", McKinsey Global Institute estimated that a retailer using big data could increase its operating margin by more than 60%. The U.S. could reduce its healthcare expenditure by 8% and government administrators in Europe could save more than €100 billion ($143 billion).
The definition MGI uses for big data is deliberately vague and not based on a specific number.
It refers instead to sets of data which are too large for current conventional database tools to capture, store, manage and analyze. It also takes account of the differences between sectors in the type of data and software available.
The ability to process this vast flow of data in real time will become a business imperative. In a traditional environment, information is gathered, put in a database, which is stored on a disc, and then indexed. Queries are then run against the database. But traditional databases are simply not up to the task of storing and handling the sheer quantity of data. It requires new types of databases able to span tens, hundreds, even thousands of servers. Yahoo, for example, runs a database cluster that spans 40,000 servers.
Advanced processing power is necessary in an environment where decisions are made in nanoseconds. At the very least, databases have to be stored in memory, demanding massive increases in server power and storage.
At its most extreme is a process called "complex event processing", which instead uses the flow of raw data and matches the query against it, looking for patterns. Typical uses of CEP include high-frequency financial trading, but other examples include sending a game player a special offer at exactly the right moment in a game, persuading them to make an in-game purchase.
This is a point picked up by Kristian Segerstrale, co-founder of social games company Playfish, who says: "Getting the information is important, but even more important will be the ability to react in real time to data and structure experiments to learn empirically from user behavior."
Ilja Laurs, the founder and chief executive of GetJar, the world's largest open mobile application store, says there is a point where, "the level of sophistication and optimization of various business processes starts to exceed a human's capacity to understand them".
Data Mining
He says: "Today, algorithms, used for positioning products in supermarkets to presenting a dynamic price grid when you book a flight ticket to maximize flight occupancy, are becoming critical to every business. To achieve the next step in efficiency it's necessary to build data mining, machine learning, optimization algorithms for every business."
Some remain skeptical about the current claims being made for big data. They point out that not all data is created equal and that, according to IDC, the fastest growing type of data is unstructured in the form of e-mails, instant messages and other "human-friendly data".
This may not be appropriate for some of the much-vaunted new tools for analyzing big data, such as in-memory database technology. This is extremely fast because it does not have to read and write from a disc: "But if you have a paragraph of an email and you put that into an in-memory database it has no more idea of what it means than an in-disc database," says Mike Lynch, chief executive of Autonomy. "If, in a few years time, they do manage to develop tools for analysis of human-friendly data, it will offer great insights into the way organizations are run, but we're not there yet," he says.
The Expert's View: Oliver Bussmann, SAP
Advances in hardware and software will finally lead to the arrival of the "real" real-time enterprise, according to Oliver Bussmann chief information officer at SAP: "In the next few years you'll see 30, 40 or even 50 terabytes of main memory RAM combined with up to 1000 cores in processors, which means you'll be able to do massive parallel processing. At the same time, advances allow data compression of up to 10 times. The price is coming down too."
What does this mean? "Processing that now takes hours or even days can happen in seconds. This will have a huge impact on predictive analytics, seeing what will be the best course of action based on access to historical and current data," he says.
"It will also remove the limitations on accessing information. Instead of having access to just a subset of data, your sales team, for example, will have all the organization's customer relationship management information and be able to change how they query it on the fly," he says.
"Accounting systems will change because you'll be able to move away from overnight processing to real time. There'll be no time limitation because you'll have the processing power." All this will be combined with an enormous growth in the volume of data coming into the enterprise. There are risks: "If you have the power to analyze everything, security is very important. If somebody hacks into this environment, all the information is there for them. You also have to make sure your system of records is properly in place. You can't just think this new technology will solve all your data problems. If the right foundation is not there, all it will mean is you can see the garbage even faster."
By Nick Clayton WSJ June 29, 2011
Big data is a term bandied around the technology sector with great ease, but little precision. While exact definitions are hard to come by, what is clear is that the ability to gather, process and store huge amounts of data is unparalleled. The sheer quantity of information and the speed at which it is consumed means conventional methods of handling it are no longer sufficient.
According to analysts IDC, the amount of digital information created and replicated rose by 62% in 2010 to nearly 800,000 petabytes, which, IDC says, would fill a stack of DVDs reaching from the earth to the moon and back. By 2020, that pile of DVDs would stretchhalfway to Mars.
Nick Halstead, CEO of DataSift, a company that specializes in handling massive data, says the New York Stock Exchange produces one terabyte of data a day; Facebook generates in excess of 20 terabytes every day; while the CERN laboratory in Geneva produces more than 40 terabytes a day, or roughly twice the entire text content of the U.S. Library of Congress every day.
In its recent report, "Big data: The next frontier for innovation, competition and productivity", McKinsey Global Institute estimated that a retailer using big data could increase its operating margin by more than 60%. The U.S. could reduce its healthcare expenditure by 8% and government administrators in Europe could save more than €100 billion ($143 billion).
The definition MGI uses for big data is deliberately vague and not based on a specific number.
It refers instead to sets of data which are too large for current conventional database tools to capture, store, manage and analyze. It also takes account of the differences between sectors in the type of data and software available.
The ability to process this vast flow of data in real time will become a business imperative. In a traditional environment, information is gathered, put in a database, which is stored on a disc, and then indexed. Queries are then run against the database. But traditional databases are simply not up to the task of storing and handling the sheer quantity of data. It requires new types of databases able to span tens, hundreds, even thousands of servers. Yahoo, for example, runs a database cluster that spans 40,000 servers.
Advanced processing power is necessary in an environment where decisions are made in nanoseconds. At the very least, databases have to be stored in memory, demanding massive increases in server power and storage.
At its most extreme is a process called "complex event processing", which instead uses the flow of raw data and matches the query against it, looking for patterns. Typical uses of CEP include high-frequency financial trading, but other examples include sending a game player a special offer at exactly the right moment in a game, persuading them to make an in-game purchase.
This is a point picked up by Kristian Segerstrale, co-founder of social games company Playfish, who says: "Getting the information is important, but even more important will be the ability to react in real time to data and structure experiments to learn empirically from user behavior."
Ilja Laurs, the founder and chief executive of GetJar, the world's largest open mobile application store, says there is a point where, "the level of sophistication and optimization of various business processes starts to exceed a human's capacity to understand them".
Data Mining
He says: "Today, algorithms, used for positioning products in supermarkets to presenting a dynamic price grid when you book a flight ticket to maximize flight occupancy, are becoming critical to every business. To achieve the next step in efficiency it's necessary to build data mining, machine learning, optimization algorithms for every business."
Some remain skeptical about the current claims being made for big data. They point out that not all data is created equal and that, according to IDC, the fastest growing type of data is unstructured in the form of e-mails, instant messages and other "human-friendly data".
This may not be appropriate for some of the much-vaunted new tools for analyzing big data, such as in-memory database technology. This is extremely fast because it does not have to read and write from a disc: "But if you have a paragraph of an email and you put that into an in-memory database it has no more idea of what it means than an in-disc database," says Mike Lynch, chief executive of Autonomy. "If, in a few years time, they do manage to develop tools for analysis of human-friendly data, it will offer great insights into the way organizations are run, but we're not there yet," he says.
The Expert's View: Oliver Bussmann, SAP
Advances in hardware and software will finally lead to the arrival of the "real" real-time enterprise, according to Oliver Bussmann chief information officer at SAP: "In the next few years you'll see 30, 40 or even 50 terabytes of main memory RAM combined with up to 1000 cores in processors, which means you'll be able to do massive parallel processing. At the same time, advances allow data compression of up to 10 times. The price is coming down too."
What does this mean? "Processing that now takes hours or even days can happen in seconds. This will have a huge impact on predictive analytics, seeing what will be the best course of action based on access to historical and current data," he says.
"It will also remove the limitations on accessing information. Instead of having access to just a subset of data, your sales team, for example, will have all the organization's customer relationship management information and be able to change how they query it on the fly," he says.
"Accounting systems will change because you'll be able to move away from overnight processing to real time. There'll be no time limitation because you'll have the processing power." All this will be combined with an enormous growth in the volume of data coming into the enterprise. There are risks: "If you have the power to analyze everything, security is very important. If somebody hacks into this environment, all the information is there for them. You also have to make sure your system of records is properly in place. You can't just think this new technology will solve all your data problems. If the right foundation is not there, all it will mean is you can see the garbage even faster."
Friday, June 17, 2011
Health IT Exchange and Analytics: The Final Frontiers
Thursday, June 16, 2011
by Jennifer Covich Bordenick
In the 10 years since the eHealth Initiative was established, we have witnessed unparalleled growth and enthusiasm for health IT solutions. The progress we have made is undeniable.
Over the last decade, the number of health information exchange initiatives grew from a couple dozen to more than 250. We have witnessed three national coordinators for health IT lead the industry in different and significant ways. Most importantly, we have seen a dramatic uptick in electronic health record adoption levels from single digits in 2001 to nearly a quarter of clinicians now using EHRs.
According to CDC, approximately 25% of office-based physicians had access to a "basic" EHR system in 2010. Moreover, patients better understand the need for connectivity, as evidenced by recent surveys. The majority of patients see health information exchange as a necessity, as evidenced by an April Commonwealth Fund survey that found 92% of patient respondents agree it is important for physicians to be able to share data electronically with other physicians.
A confluence of events made all of this possible: money, policy and technology. A huge infusion of federal money -- $27 billion -- for meaningful use helped kick start efforts in the private sector. Public-private sector policy efforts began with the federal advisory body American Health Information Community in 2005; they have continued with the Health IT Policy Committee and Health IT Standards Committee. And, finally, technology and timing have played a key role in our success. With the advent of social media, PDAs and "apps" over the last decade, patients are open to technology now more than ever.
According to a 2011 Pew Internet and American Life Project/California HealthCare Foundation survey, of the 74% of U.S. residents who use the Internet, 80% have looked online for health information about one of 15 health topics, such as a specific disease or treatment.
The progress we have made to date has been hard fought and expensive and the growing pains have been severe, but the real promise has yet to be realized. If you talk to a cancer patient waiting for information to be sent from a lab, a public health official trying to track the source of an outbreak, a sick patient waiting months and years for a clinical trial to wrap up or any mother toting around paper copies of immunization forms -- you will find many health care users who have yet to see the promise realized.
It's time for the nation to double down on the health IT bet, redouble our efforts and take it to the next level. Why? Because the next ten years will make or break this industry, the next decade will be even more challenging than the last one.
Expectations are exceedingly high. Everyone, including politicians, is looking for proof that health IT improves care, outcomes and reduces cost, proof that our investment financially and politically was worth it. We have raised expectations for good reason; we know it works. Those of us who work in the industry have seen the results, but we have done a bad job of communicating the successes. More importantly, we have stopped focusing on what we are going to do with the data. We have stopped talking about why it is so important that we have this data.
Getting to the next level requires two things: exchange and analytics.
Health information exchange, that old familiar phrase, is back in the spotlight. It is not good enough to store information in a deluxe EHR. Health information needs to move, it has to be accessible to the specialist, connect to your smartphone app, flow from your home device, transfer to your pharmacy and download into your personal device -- so that you can use the data. Because without "exchange," all of this talk about EHRs is not very useful. Health information needs to move with patients, so patients and doctors can use the data.
Lastly, analytics remains the final frontier we need to conquer. Right now, we have an overwhelming volume of data from a multitude of sources. The culmination of recent efforts will exponentially increase the amount of data. The real promise of health IT was never about the technology, it was always about leveraging the data. We need to safely and securely aggregate, stratify, investigate, test and dish out the data in 10 different ways for clinical researchers, public health and, of course, patient care.
Given the groundwork we established over the last 10 years, public sentiment, new regulations and the investments that have been made, we are on the right track. All of these things will make faster progress possible in the next 10 years. Let's be sure to keep a clear focus on the promise of the data.
MORE ON THE WEB
· Federal Health IT Strategic Plan
· "A Call for Change: The 2011 Commonwealth Fund Survey of Public Views of the U.S. Health System" (4/2011).
· CDC survey on EHR adoption
Read more: http://www.ihealthbeat.org/perspectives/2011/exchange-and-analytics-the-final-frontiers.aspx#ixzz1PZ3NagCh
by Jennifer Covich Bordenick
In the 10 years since the eHealth Initiative was established, we have witnessed unparalleled growth and enthusiasm for health IT solutions. The progress we have made is undeniable.
Over the last decade, the number of health information exchange initiatives grew from a couple dozen to more than 250. We have witnessed three national coordinators for health IT lead the industry in different and significant ways. Most importantly, we have seen a dramatic uptick in electronic health record adoption levels from single digits in 2001 to nearly a quarter of clinicians now using EHRs.
According to CDC, approximately 25% of office-based physicians had access to a "basic" EHR system in 2010. Moreover, patients better understand the need for connectivity, as evidenced by recent surveys. The majority of patients see health information exchange as a necessity, as evidenced by an April Commonwealth Fund survey that found 92% of patient respondents agree it is important for physicians to be able to share data electronically with other physicians.
A confluence of events made all of this possible: money, policy and technology. A huge infusion of federal money -- $27 billion -- for meaningful use helped kick start efforts in the private sector. Public-private sector policy efforts began with the federal advisory body American Health Information Community in 2005; they have continued with the Health IT Policy Committee and Health IT Standards Committee. And, finally, technology and timing have played a key role in our success. With the advent of social media, PDAs and "apps" over the last decade, patients are open to technology now more than ever.
According to a 2011 Pew Internet and American Life Project/California HealthCare Foundation survey, of the 74% of U.S. residents who use the Internet, 80% have looked online for health information about one of 15 health topics, such as a specific disease or treatment.
The progress we have made to date has been hard fought and expensive and the growing pains have been severe, but the real promise has yet to be realized. If you talk to a cancer patient waiting for information to be sent from a lab, a public health official trying to track the source of an outbreak, a sick patient waiting months and years for a clinical trial to wrap up or any mother toting around paper copies of immunization forms -- you will find many health care users who have yet to see the promise realized.
It's time for the nation to double down on the health IT bet, redouble our efforts and take it to the next level. Why? Because the next ten years will make or break this industry, the next decade will be even more challenging than the last one.
Expectations are exceedingly high. Everyone, including politicians, is looking for proof that health IT improves care, outcomes and reduces cost, proof that our investment financially and politically was worth it. We have raised expectations for good reason; we know it works. Those of us who work in the industry have seen the results, but we have done a bad job of communicating the successes. More importantly, we have stopped focusing on what we are going to do with the data. We have stopped talking about why it is so important that we have this data.
Getting to the next level requires two things: exchange and analytics.
Health information exchange, that old familiar phrase, is back in the spotlight. It is not good enough to store information in a deluxe EHR. Health information needs to move, it has to be accessible to the specialist, connect to your smartphone app, flow from your home device, transfer to your pharmacy and download into your personal device -- so that you can use the data. Because without "exchange," all of this talk about EHRs is not very useful. Health information needs to move with patients, so patients and doctors can use the data.
Lastly, analytics remains the final frontier we need to conquer. Right now, we have an overwhelming volume of data from a multitude of sources. The culmination of recent efforts will exponentially increase the amount of data. The real promise of health IT was never about the technology, it was always about leveraging the data. We need to safely and securely aggregate, stratify, investigate, test and dish out the data in 10 different ways for clinical researchers, public health and, of course, patient care.
Given the groundwork we established over the last 10 years, public sentiment, new regulations and the investments that have been made, we are on the right track. All of these things will make faster progress possible in the next 10 years. Let's be sure to keep a clear focus on the promise of the data.
MORE ON THE WEB
· Federal Health IT Strategic Plan
· "A Call for Change: The 2011 Commonwealth Fund Survey of Public Views of the U.S. Health System" (4/2011).
· CDC survey on EHR adoption
Read more: http://www.ihealthbeat.org/perspectives/2011/exchange-and-analytics-the-final-frontiers.aspx#ixzz1PZ3NagCh
A. Huffington: The Internet Grows Up: Goodbye Messy Adolescence
Arriana Huffington HuffPost June 16, 2011
I'm off to take part in the 58th Annual Cannes Lions International Festival of Creativity. Tim Armstrong and I will be speaking on a theme that we have been talking a lot about lately -- the fact that the Internet has grown up.
Its adolescence was, like most formative years, filled with late nights, video games, loud music, junk food, and trying to figure out exactly what it wanted to be when it grew up.
Now, it has matured to the point where our online and our offline lives have merged.
Indeed, the qualities we care most about offline are being increasingly reflected in our experience online. We're leaving behind worshiping at the altar of algorithms and entering a brave new world of community, connections and engagement.
And the companies and brands that succeed in the coming years will be those that most take advantage of the fact that there is increasingly little distinction between "virtual reality" and, well, reality. People don't want to give up their humanity when they go online. The Internet is no longer a "virtual" public space where we have the semblance of connection -- it's a real public space where we really connect.
Remember all those scary movies about how humans were going to become machines in the future? Well, as it turned out, the machines ended up enabling us to be more human instead.
The long prelude to this coming-of-age moment has been a time of amazing change. We have watched the Web evolve to meet our hunger for connection and community. But it hasn't always been easy. As Clay Shirky recently noted, history shows that changes in the way we relate to information are inevitably accompanied by resistance. "Every increase in freedom to create or consume media," he wrote, "from paperback books to YouTube, alarms people accustomed to the restrictions of the old system, convincing them that the new media will make young people stupid." It was, after all, predicted that the printing press would lead to "chaos and the dismemberment of European intellectual life."
And yes, along with our increased access to ideas, information -- and each other -- comes the tendency to create what Shirky calls "throwaway material." And the Internet is certainly no slouch at producing throwaway material -- a tendency that won't be going away. But something else has emerged among all the random searching: a search for greater meaning.
We're now more thoughtful and deliberate about choosing our friends and how we spend our online time. Adulthood is a time when our lives become about curating, selecting, saying "no" more often than we say "yes," being forced to decide what we really value, realizing what's really important to us. Increasingly, that's exactly how people are using the Internet as well.
To be sure, the adolescent Internet will always be with us. But now there's a choice -- not just for individuals, but for companies as well. One way forward is to continue down the path where noise and half-truths trump facts, where confusion and data overload overwhelm any possibility of balance and wisdom. The other way is to stake out a place in this new world of community, connections and collaboration.
The Internet of the future, the mature, grown-up Internet, has the potential to take what's best about the human experience -- our passion, our knowledge, our desire to connect -- and channel it into an online experience that truly resonates with how people live.
The bridge to this more connected, more human future is to be found in directing our energy and resources to the foundational pillars of trust, authenticity and engagement -- principles that can help all of us navigate the world, whether it's the real world or the World Wide Web.
Let's start with trust:
In the newer, more mature, more human Internet, trust isn't something that comes because an old institution or authority figure demands it. It comes the same way it comes offline: It's born out of connection and relationships. If brands and institutions want to have our trust, it must be earned, and then continually maintained -- the same way it is in relationships we have in the offline world.
Truth is an important element of trust, but truth isn't just about facts. As NYU professor Jay Rosen says, "information alone will not inform us." Information free from any context isn't meaningful to us and is not going to be trusted. So those who supply the context to the facts and information become extremely important. We know where our friends are coming from, we know who they are. So the information we get from them is more trusted.
The second pillar of the mature Internet is authenticity.
As users of the Web have become increasingly overwhelmed with information, and with competing messages, so too have they become increasingly sophisticated about sorting out the real from the fake, the genuine from the manufactured. The modern media landscape requires authenticity in order to make an impact.
In the new, grown-up Internet, the ordering principle is social, not hierarchical. It's person-to-person, not top-down. And social media turns out to be an incredible tool for recognizing, building and fostering authenticity. That's what it's about -- and this holds true not just for individual users, but for brands as well.
New media and social media tools have enabled people to shift their focus from passive observation to active participation -- millions worldwide now want in on the creative process and have much to contribute to it. And companies are eager to use that passion and connection. But it's a two-way street. Through social media, people tell companies who they are and what they value, and companies also tell people who they are and what their values are. And increasingly, companies that have both of those figured out have also figured out that doing good is good business.
Our third pillar is engagement... the grown-up Internet is all about engagement and community -- after all, we're social animals. The human desire for connectedness is universal. The Knight Foundation and Gallup recently conducted a survey to find out what emotionally attaches people to a community. The results were instructive -- and they were consistent, from people in big cities to those living in small towns. The study found that the key drivers of people's emotional attachment to where they live are: an area's physical beauty, opportunities for socializing and a community's openness to all people.
That's just as true online as off. People will eventually find a way to make any activity into a tool for engagement, connection and community, and the Internet is the most effective tool for community building the world has ever seen. In fact, this invention -- this thing we think of as a piece of technology or a series of machines -- is now at the stage where it's actually allowing us to tap into our full humanity.
So now that the Internet has arrived at adulthood, the next stage will be what we euphemistically call the Golden Years. That Internet won't have the drawbacks of our old age, but I'm hoping it will have its main benefit: wisdom.
I'm off to take part in the 58th Annual Cannes Lions International Festival of Creativity. Tim Armstrong and I will be speaking on a theme that we have been talking a lot about lately -- the fact that the Internet has grown up.
Its adolescence was, like most formative years, filled with late nights, video games, loud music, junk food, and trying to figure out exactly what it wanted to be when it grew up.
Now, it has matured to the point where our online and our offline lives have merged.
Indeed, the qualities we care most about offline are being increasingly reflected in our experience online. We're leaving behind worshiping at the altar of algorithms and entering a brave new world of community, connections and engagement.
And the companies and brands that succeed in the coming years will be those that most take advantage of the fact that there is increasingly little distinction between "virtual reality" and, well, reality. People don't want to give up their humanity when they go online. The Internet is no longer a "virtual" public space where we have the semblance of connection -- it's a real public space where we really connect.
Remember all those scary movies about how humans were going to become machines in the future? Well, as it turned out, the machines ended up enabling us to be more human instead.
The long prelude to this coming-of-age moment has been a time of amazing change. We have watched the Web evolve to meet our hunger for connection and community. But it hasn't always been easy. As Clay Shirky recently noted, history shows that changes in the way we relate to information are inevitably accompanied by resistance. "Every increase in freedom to create or consume media," he wrote, "from paperback books to YouTube, alarms people accustomed to the restrictions of the old system, convincing them that the new media will make young people stupid." It was, after all, predicted that the printing press would lead to "chaos and the dismemberment of European intellectual life."
And yes, along with our increased access to ideas, information -- and each other -- comes the tendency to create what Shirky calls "throwaway material." And the Internet is certainly no slouch at producing throwaway material -- a tendency that won't be going away. But something else has emerged among all the random searching: a search for greater meaning.
We're now more thoughtful and deliberate about choosing our friends and how we spend our online time. Adulthood is a time when our lives become about curating, selecting, saying "no" more often than we say "yes," being forced to decide what we really value, realizing what's really important to us. Increasingly, that's exactly how people are using the Internet as well.
To be sure, the adolescent Internet will always be with us. But now there's a choice -- not just for individuals, but for companies as well. One way forward is to continue down the path where noise and half-truths trump facts, where confusion and data overload overwhelm any possibility of balance and wisdom. The other way is to stake out a place in this new world of community, connections and collaboration.
The Internet of the future, the mature, grown-up Internet, has the potential to take what's best about the human experience -- our passion, our knowledge, our desire to connect -- and channel it into an online experience that truly resonates with how people live.
The bridge to this more connected, more human future is to be found in directing our energy and resources to the foundational pillars of trust, authenticity and engagement -- principles that can help all of us navigate the world, whether it's the real world or the World Wide Web.
Let's start with trust:
In the newer, more mature, more human Internet, trust isn't something that comes because an old institution or authority figure demands it. It comes the same way it comes offline: It's born out of connection and relationships. If brands and institutions want to have our trust, it must be earned, and then continually maintained -- the same way it is in relationships we have in the offline world.
Truth is an important element of trust, but truth isn't just about facts. As NYU professor Jay Rosen says, "information alone will not inform us." Information free from any context isn't meaningful to us and is not going to be trusted. So those who supply the context to the facts and information become extremely important. We know where our friends are coming from, we know who they are. So the information we get from them is more trusted.
The second pillar of the mature Internet is authenticity.
As users of the Web have become increasingly overwhelmed with information, and with competing messages, so too have they become increasingly sophisticated about sorting out the real from the fake, the genuine from the manufactured. The modern media landscape requires authenticity in order to make an impact.
In the new, grown-up Internet, the ordering principle is social, not hierarchical. It's person-to-person, not top-down. And social media turns out to be an incredible tool for recognizing, building and fostering authenticity. That's what it's about -- and this holds true not just for individual users, but for brands as well.
New media and social media tools have enabled people to shift their focus from passive observation to active participation -- millions worldwide now want in on the creative process and have much to contribute to it. And companies are eager to use that passion and connection. But it's a two-way street. Through social media, people tell companies who they are and what they value, and companies also tell people who they are and what their values are. And increasingly, companies that have both of those figured out have also figured out that doing good is good business.
Our third pillar is engagement... the grown-up Internet is all about engagement and community -- after all, we're social animals. The human desire for connectedness is universal. The Knight Foundation and Gallup recently conducted a survey to find out what emotionally attaches people to a community. The results were instructive -- and they were consistent, from people in big cities to those living in small towns. The study found that the key drivers of people's emotional attachment to where they live are: an area's physical beauty, opportunities for socializing and a community's openness to all people.
That's just as true online as off. People will eventually find a way to make any activity into a tool for engagement, connection and community, and the Internet is the most effective tool for community building the world has ever seen. In fact, this invention -- this thing we think of as a piece of technology or a series of machines -- is now at the stage where it's actually allowing us to tap into our full humanity.
So now that the Internet has arrived at adulthood, the next stage will be what we euphemistically call the Golden Years. That Internet won't have the drawbacks of our old age, but I'm hoping it will have its main benefit: wisdom.
Thursday, June 16, 2011
Computer Science's 'Sputnik Moment'?
Introduction
Computer science is a hot major again. It had been in the doldrums after the dot-com bust a decade ago, but with the social media gold rush and the success of "The Social Network," computer science departments are transforming themselves to meet the demand. At Harvard, the size of the introductory computer science class has nearly quadrupled in five years.
The spike has raised hopes of a ripple effect throughout the American education system -- so much so that Mehran Sahami, the associate chairman for computer science at Stanford, can envision "a national call, a Sputnik moment."
What would a "Sputnik moment" entail today? Will the surge of students into computer science last, and could it help raise American educational achievement?
Debate at http://www.nytimes.com/roomfordebate/2011/06/15/computer-sciences-sputnik-moment?ref=opinion
Some taking part of the debate below:
Thinking Beyond the Bubble
Updated June 16, 2011, 02:24 AM
Vivek Wadhwa is a visiting scholar at University of California, Berkeley, senior research associate at Harvard Law School and director of research at the Center for Entrepreneurship and Research Commercialization at Duke University. Follow him on Twitter at @wadhwa.
As we learned from the last technology bubble — the dot-com era — high-flying tech careers can be very seductive. When students started reading about the young millionaires of that era, they flocked to computer science, and enrollments reached record levels. And then the bubble burst, and so did enrollments.
Social media apps are cool, but what do they have to do with saving the world?
We’re in the middle of a new bubble now, with a fresh set of millionaires. There is little doubt that this will burst and enrollments will drop again. And we’ll have another generation of students who joined computer science for the wrong reasons.
If we want a real Sputnik moment, we need to create the same demand — and excitement — we had for engineers and scientists in the ’60s, when it seemed that the nation’s survival was at stake. Parents encouraged their children to become scientists; the president told us it was a national priority; and we made huge investments. Science was sexy, chic and essential.
Social media apps such as the ones these kids want to learn how to develop are cool, but not earth-shattering. Students are flocking to computer science because they dream of being the next Mark Zuckerberg, not of saving the world. This burst of enrollments is the equivalent of a sugar high.
It is not that we don’t have real problems to fix. Our economy is still in a slump; greenhouse gases threaten to turn the earth into a giant steam room; scarce natural resources like food, water and oil have already become international flash points as the developing and developed worlds jockey for position to sustain or improve their standards of living. Drug-resistant bacteria threaten us with doomsday plagues. In other words, if there ever was a time for a Scientific Renaissance, now is it.
By the time these computer science majors graduate, we may be in the middle of yet another tech bubble, so these kids may do O.K. But we will not have made any progress toward fixing the real problems and may have celebrated for nothing.
Encourage More Hackathons
June 15, 2011
Jonathan Zittrain is a professor at Harvard Law School and a professor of computer science at the university's School of Engineering and Applied Sciences. He is a co-founder of the Berkman Center for Internet and Society.
Educating students or the general public about computer science isn't easy. Teaching theory can be interesting and mind-expanding, but it may be no more applicable in most people's lives and careers than high school algebra or calculus. Teaching specific programming languages for more concrete purposes can risk having students lose sight of the bigger picture, confining them to rote work without much prospect for intellectual growth.
The creators of many game-changing inventions were not computer science majors.
That bigger picture is what makes mastery of today's technology so special: unlike many other fields of endeavor, anyone with an idea can try it out and garner an audience around it without having to ink a business plan or raise prohibitive amounts of money. Thanks to PCs that run any software they're given, and an Internet that allows anyone to set up shop and start communicating with the world without having to do the equivalent of buying a television broadcast tower and license, we've seen amazing and disruptive ventures from humble beginnings.
Tim Berners-Lee invented the World Wide Web by writing the code for a browser and a Web server and seeing if the world wanted to take it up. No business model, venture capital rounds, or patents were involved. Ward Cunningham invented something called a wiki, where people could collectively edit a document. Jimmy Wales used it to create Wikipedia, a project that was considered foolish at first but has completely reshaped the way people document and share information about the world.
Even the Internet and PC came from unexpected origins. The inventors of the Internet protocol were experimenting; they didn't know what would be done with the network. The Internet didn't and doesn't have a "main menu," but rather, it is raw connectivity waiting for its users to do something with it -- to connect with one another.
The inventors of the first consumer PC -- Steve Wozniak and Steve Jobs -- unveiled an Apple II in 1977 that had a blinking cursor instead of bundled software; other technologists were de facto invited to design applications and then share or sell them to one another. (Two years later, to Apple's surprise, the personal computer became a business when Dan Bricklin and Bob Frankston invented VisiCalc, the first digital spreadsheet, and companies around the world suddenly craved PCs.)
What's notable about most of these and other game-changing inventions is that their creators mostly weren't computer science majors. They were self-taught or learned their craft through apprenticeship to other coders.
Computer science curricula that lack the spirit of exploration and experimentation -- that stick too closely to the textbooks, whether ones of theory or practice -- won't speed the overall pace of innovation. That's why all-night hackathons are good ideas: they encourage people to see that the world can be changed, and that a small but determined handful of people can do it.
Our challenge is to keep alive Sputnik's rallying cry in a world where coding is becoming more confined.
Sputnik itself was first tracked not by professionally trained astronomers but by bands of amateurs spread across the nation, heeding a call to build or acquire their own telescopes and to document what they saw. Our challenge is to keep alive Sputnik's rallying cry in a world where coding is becoming more confined. Web servers where new ideas might take root are consolidating under a few corporate hosts. Today's coders are naturally more interested in writing for the Facebook or Apple iOS platforms, where truly disruptive ideas can be banned or diminished by gatekeepers who want to protect their own business models, or are compelled to carry water for other regulatory purposes.
The reason to teach computer science isn't to turn everyone into a coder. It's to share the insight that today, more than ever, the world can be shaped by good and rigorous ideas hatched by "mere" teenagers or other outsiders, and that these ideas transcend technology.
There's a social and legal dimension to this as well. That's why computer science should include a look at the policy implications of the codes we forge. Moreover, computer science education shouldn't be limited to college. Programs like the Sprouts help make the craft available to everyone, empowering people to affect the world rather than merely marveling at shiny gizmos.
A Key to Critical Thinking
Updated June 15, 2011, 09:15 PM
Ed Lazowska holds the Bill and Melinda Gates chair in computer science and engineering at the University of Washington.
Students are starting to realize that advances in computer science are central to achieving many of our national priorities – in energy, education, health care, national and homeland security, scientific discovery and open government.
As more fields become information fields, "computational thinking” is necessary for success in just about any endeavor.
As more fields become information fields, facility with what we call "computational thinking” is necessary for success in just about any endeavor. Once, the principal qualification for a career in linguistics was the ability to speak multiple languages; but along came Noam Chomsky with transformational grammar, and the world changed. Once, biology was taxonomy; then Watson and Crick discovered that the human genome was a digital code that could be read, deciphered, modified and rewritten. Once, sociologists studied the formation, evolution and dissolution of cliques by paying undergraduates to participate in focus groups; today they mine half a billion users’ worth of Facebook data.
Computer science is a superb preparation for just about anything. And within technology industries, there are plentiful jobs. Those who choose to work in the computing field find it characterized by highly interactive teams that are focused on solving real life problems. The Dilbert stereotype is surely dead.
For students who want to change the world, there is no field with greater impact or leverage than computer science. Just take a look at the 2010 report by the President's Council of Advisers on Science and Technology, which characterized computer science as “arguably unique among all fields of science and engineering in the breadth of its impact.”
Despite all of this good news, we need a national re-commitment to education, innovation, science and engineering. All the facts suggest that we are losing our edge.
Computer science is a hot major again. It had been in the doldrums after the dot-com bust a decade ago, but with the social media gold rush and the success of "The Social Network," computer science departments are transforming themselves to meet the demand. At Harvard, the size of the introductory computer science class has nearly quadrupled in five years.
The spike has raised hopes of a ripple effect throughout the American education system -- so much so that Mehran Sahami, the associate chairman for computer science at Stanford, can envision "a national call, a Sputnik moment."
What would a "Sputnik moment" entail today? Will the surge of students into computer science last, and could it help raise American educational achievement?
Debate at http://www.nytimes.com/roomfordebate/2011/06/15/computer-sciences-sputnik-moment?ref=opinion
Some taking part of the debate below:
Thinking Beyond the Bubble
Updated June 16, 2011, 02:24 AM
Vivek Wadhwa is a visiting scholar at University of California, Berkeley, senior research associate at Harvard Law School and director of research at the Center for Entrepreneurship and Research Commercialization at Duke University. Follow him on Twitter at @wadhwa.
As we learned from the last technology bubble — the dot-com era — high-flying tech careers can be very seductive. When students started reading about the young millionaires of that era, they flocked to computer science, and enrollments reached record levels. And then the bubble burst, and so did enrollments.
Social media apps are cool, but what do they have to do with saving the world?
We’re in the middle of a new bubble now, with a fresh set of millionaires. There is little doubt that this will burst and enrollments will drop again. And we’ll have another generation of students who joined computer science for the wrong reasons.
If we want a real Sputnik moment, we need to create the same demand — and excitement — we had for engineers and scientists in the ’60s, when it seemed that the nation’s survival was at stake. Parents encouraged their children to become scientists; the president told us it was a national priority; and we made huge investments. Science was sexy, chic and essential.
Social media apps such as the ones these kids want to learn how to develop are cool, but not earth-shattering. Students are flocking to computer science because they dream of being the next Mark Zuckerberg, not of saving the world. This burst of enrollments is the equivalent of a sugar high.
It is not that we don’t have real problems to fix. Our economy is still in a slump; greenhouse gases threaten to turn the earth into a giant steam room; scarce natural resources like food, water and oil have already become international flash points as the developing and developed worlds jockey for position to sustain or improve their standards of living. Drug-resistant bacteria threaten us with doomsday plagues. In other words, if there ever was a time for a Scientific Renaissance, now is it.
By the time these computer science majors graduate, we may be in the middle of yet another tech bubble, so these kids may do O.K. But we will not have made any progress toward fixing the real problems and may have celebrated for nothing.
Encourage More Hackathons
June 15, 2011
Jonathan Zittrain is a professor at Harvard Law School and a professor of computer science at the university's School of Engineering and Applied Sciences. He is a co-founder of the Berkman Center for Internet and Society.
Educating students or the general public about computer science isn't easy. Teaching theory can be interesting and mind-expanding, but it may be no more applicable in most people's lives and careers than high school algebra or calculus. Teaching specific programming languages for more concrete purposes can risk having students lose sight of the bigger picture, confining them to rote work without much prospect for intellectual growth.
The creators of many game-changing inventions were not computer science majors.
That bigger picture is what makes mastery of today's technology so special: unlike many other fields of endeavor, anyone with an idea can try it out and garner an audience around it without having to ink a business plan or raise prohibitive amounts of money. Thanks to PCs that run any software they're given, and an Internet that allows anyone to set up shop and start communicating with the world without having to do the equivalent of buying a television broadcast tower and license, we've seen amazing and disruptive ventures from humble beginnings.
Tim Berners-Lee invented the World Wide Web by writing the code for a browser and a Web server and seeing if the world wanted to take it up. No business model, venture capital rounds, or patents were involved. Ward Cunningham invented something called a wiki, where people could collectively edit a document. Jimmy Wales used it to create Wikipedia, a project that was considered foolish at first but has completely reshaped the way people document and share information about the world.
Even the Internet and PC came from unexpected origins. The inventors of the Internet protocol were experimenting; they didn't know what would be done with the network. The Internet didn't and doesn't have a "main menu," but rather, it is raw connectivity waiting for its users to do something with it -- to connect with one another.
The inventors of the first consumer PC -- Steve Wozniak and Steve Jobs -- unveiled an Apple II in 1977 that had a blinking cursor instead of bundled software; other technologists were de facto invited to design applications and then share or sell them to one another. (Two years later, to Apple's surprise, the personal computer became a business when Dan Bricklin and Bob Frankston invented VisiCalc, the first digital spreadsheet, and companies around the world suddenly craved PCs.)
What's notable about most of these and other game-changing inventions is that their creators mostly weren't computer science majors. They were self-taught or learned their craft through apprenticeship to other coders.
Computer science curricula that lack the spirit of exploration and experimentation -- that stick too closely to the textbooks, whether ones of theory or practice -- won't speed the overall pace of innovation. That's why all-night hackathons are good ideas: they encourage people to see that the world can be changed, and that a small but determined handful of people can do it.
Our challenge is to keep alive Sputnik's rallying cry in a world where coding is becoming more confined.
Sputnik itself was first tracked not by professionally trained astronomers but by bands of amateurs spread across the nation, heeding a call to build or acquire their own telescopes and to document what they saw. Our challenge is to keep alive Sputnik's rallying cry in a world where coding is becoming more confined. Web servers where new ideas might take root are consolidating under a few corporate hosts. Today's coders are naturally more interested in writing for the Facebook or Apple iOS platforms, where truly disruptive ideas can be banned or diminished by gatekeepers who want to protect their own business models, or are compelled to carry water for other regulatory purposes.
The reason to teach computer science isn't to turn everyone into a coder. It's to share the insight that today, more than ever, the world can be shaped by good and rigorous ideas hatched by "mere" teenagers or other outsiders, and that these ideas transcend technology.
There's a social and legal dimension to this as well. That's why computer science should include a look at the policy implications of the codes we forge. Moreover, computer science education shouldn't be limited to college. Programs like the Sprouts help make the craft available to everyone, empowering people to affect the world rather than merely marveling at shiny gizmos.
A Key to Critical Thinking
Updated June 15, 2011, 09:15 PM
Ed Lazowska holds the Bill and Melinda Gates chair in computer science and engineering at the University of Washington.
Students are starting to realize that advances in computer science are central to achieving many of our national priorities – in energy, education, health care, national and homeland security, scientific discovery and open government.
As more fields become information fields, "computational thinking” is necessary for success in just about any endeavor.
As more fields become information fields, facility with what we call "computational thinking” is necessary for success in just about any endeavor. Once, the principal qualification for a career in linguistics was the ability to speak multiple languages; but along came Noam Chomsky with transformational grammar, and the world changed. Once, biology was taxonomy; then Watson and Crick discovered that the human genome was a digital code that could be read, deciphered, modified and rewritten. Once, sociologists studied the formation, evolution and dissolution of cliques by paying undergraduates to participate in focus groups; today they mine half a billion users’ worth of Facebook data.
Computer science is a superb preparation for just about anything. And within technology industries, there are plentiful jobs. Those who choose to work in the computing field find it characterized by highly interactive teams that are focused on solving real life problems. The Dilbert stereotype is surely dead.
For students who want to change the world, there is no field with greater impact or leverage than computer science. Just take a look at the 2010 report by the President's Council of Advisers on Science and Technology, which characterized computer science as “arguably unique among all fields of science and engineering in the breadth of its impact.”
Despite all of this good news, we need a national re-commitment to education, innovation, science and engineering. All the facts suggest that we are losing our edge.
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