This link has been bookmarked by 61 people . It was first bookmarked on 25 Jun 2009, by Lisa Spiro.
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09 Nov 09
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02 Nov 09
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if a database is generated by user contribution, market leaders will see increasing returns as the size and value of their database grows more quickly than that of any new entrants.
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Key takeaway: A key competency of the Web 2.0 era is discovering implied metadata, and then building a database to capture that metadata and/or foster an ecosystem around it.
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30 Oct 09
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Web Squared
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Web Squared
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building applications that literally get better the more people use them,
harnessing network effects not only to acquire users, but also to learn from
them and build on their contributions. -
Web 2.0 is all about harnessing
collective intelligence.Collective intelligence applications depend on managing, understanding, and
responding to massive amounts of user-generated data in real time. -
real
world objects have "information shadows" in cyberspace -
"crowdsourcing," namely that a large group of people can create a collective
work whose value far exceeds that provided by any of the individual participants -
applications can be constructed in such a way as to direct their users to
perform specific tasks, like building an online encyclopedia (Wikipedia),
annotating an online catalog (Amazon), adding data points onto a map (the many
web mapping applications), or finding the most popular news stories (Digg,
Twine). -
ability of the computer to synthesize imaginary worlds that never existed,
extrapolating a complete 3D experience from a set of photos -
We teach our photo program to recognize faces that matter to us, we share news
that we care about, we add tags to our tweets so that they can be grouped more
easily. In adding value for ourselves, we are adding value to the social web as
well. Our devices extend us, and we extend them. -
sensor web
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taxi driver he met in Wellington, NZ, who kept logs of six weeks of pickups
(GPS, weather, passenger, and three other variables), fed them into his
computer, and did some analysis to figure out where he should be at any given
point in the day to maximize his take. As a result, he’s making a very nice
living with much less work than other taxi drivers. Instrumenting the world pays
off. -
Data analysis, visualization, and other techniques for seeing patterns in data
are going to be an increasingly valuable skillset. Employers take notice -
"We are building an ‘astrometry engine’ to create correct, standards-compliant
astrometric meta data for every useful astronomical image ever taken, past and
future, in any state of archival disarray." Using this engine, the Flickr astrotagger
bot trolls Flickr for images of astronomical objects and gives them proper
metadata, which then allows them to be included in astronomical image search by
name. This is a service directly analogous to CDDB: a
lookup service that maps messy sensor data to a regularized lookup database. -
microblogging requires instantaneous update – which means a significant shift in
both infrastructure and approach. Anyone who searches Twitter on a trending
topic has to be struck by the message: "See what’s happening right now"
followed, a few moments later by "42 more results since you started searching.
Refresh to see them." -
Retweeted "information cascades" spread breaking news across Twitter in moments,
making it the earliest source for many people to learn about what’s just
happened. -
With services like Twitter and Facebook’s status updates, a new data source has
been added to the Web – realtime indications of what is on our collective mind -
see the counter-trend, that communication binds us together, gives us shared
context, and ultimately shared identity. -
Web meets World – that’s Web Squared
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Twitter is being used to report news of disasters, and to coordinate emergency
response
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20 Oct 09
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05 Oct 09
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30 Sep 09
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27 Sep 09
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25 Sep 09
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14 Sep 09
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09 Sep 09
benoit hyrondeJoin us for a webcast about Web Squared on Thursday, June 25 at 10:00 a.m. Pacific time with John Battelle and Tim O'Reilly.
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Allison MillerThe Web is no longer a collection of static pages of HTML that describe something in the world. Increasingly, the Web is the world – everything and everyone in the world casts an "information shadow," an aura of data which, when captured and processed intelligently, offers extraordinary opportunity and mind bending implications. Web Squared is our way of exploring this phenomenon and giving it a name.
timo'reilly timoreilly web2.0 websquared openness transparency collectiveknowledge informationshadows sensoryworld digitalimpact digitalfootprint socialonomics
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03 Sep 09
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Ever since we first introduced the term "Web 2.0," people have been asking, "What’s next?" Assuming that Web 2.0 was meant to be a kind of software version number (rather than a statement about the second coming of the Web after the dotcom bust), we’re constantly asked about "Web 3.0." Is it the semantic web? The sentient web? Is it the social web? The mobile web? Is it some form of virtual reality?
It is all of those, and more.
The Web is no longer a collection of static pages of HTML that describe something in the world. Increasingly, the Web is the world – everything and everyone in the world casts an "information shadow," an aura of data which, when captured and processed intelligently, offers extraordinary opportunity and mind bending implications. Web Squared is our way of exploring this phenomenon and giving it a name.
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27 Aug 09
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26 Aug 09
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21 Aug 09
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20 Aug 09
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Our phones and cameras are being turned into eyes and ears for applications; motion and location sensors tell where we are
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With more users and sensors feeding more applications and platforms, developers are able to tackle serious real-world problems. As a result, the Web opportunity is no longer growing arithmetically; it’s growing exponentially.
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Gradually, the world begins to make sense. The baby coordinates the input from multiple senses, filters signal from noise, learns new skills, and once-difficult tasks become automatic.
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We don’t have to wait until each item in the supermarket has a unique machine-readable ID. Instead, we can make do with bar codes, tags on photos, and other "hacks" that are simply ways of brute-forcing identity out of reality.
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As the information shadows become thicker, more substantial, the need for explicit metadata diminishes.
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18 Aug 09
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location
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identity
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sensors
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Data is being collected, presented, and acted upon in real time.
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successful network applications are systems for harnessing collective intelligence.
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16 Aug 09
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13 Aug 09
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12 Aug 09
Andrew LongJohn Battelle and Tim O'Reilly discuss the next evolution of Web 2.0 - Web Squared.
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10 Aug 09
Eapen thomas- Companies like 23andMe and PatientsLikeMe are applying crowdsourcing to build databases of use to the personalized medicine community. 23andMe provides genetic testing for personal use, but their long term goal is to provide a database of genetic information that members could voluntarily provide to researchers. PatientsLikeMe has created a social network for people with various life-changing diseases; by sharing details of treatment – what’s working and what’s not – they are in effect providing a basis for the world’s largest longitudinal medical outcome testing service. What other creative applications of Web 2.0 technology are you seeing to advance the state of the art in healthcare?
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Companies like 23andMe and PatientsLikeMe are applying crowdsourcing to build databases of use to the personalized medicine community. 23andMe provides genetic testing for personal use, but their long term goal is to provide a database of genetic information that members could voluntarily provide to researchers. PatientsLikeMe has created a social network for people with various life-changing diseases; by sharing details of treatment – what’s working and what’s not – they are in effect providing a basis for the world’s largest longitudinal medical outcome testing service. What other creative applications of Web 2.0 technology are you seeing to advance the state of the art in healthcare?
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07 Aug 09
euro thingJoin us for a webcast about Web Squared on Thursday, June 25 at 10:00 a.m. Pacific time with John Battelle and Tim O'Reilly.
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06 Aug 09
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05 Aug 09
Fernanda IbarraCollective intelligence applications depend on managing, understanding, and responding to massive amounts of user-generated data in real time. The "subsystems" of the emerging internet operating system are increasingly data subsystems: location, identity (of people, products, and places), and the skeins of meaning that tie them together. This leads to new levers of competitive advantage: Data is the "Intel Inside" of the next generation of computer applications.
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29 Jul 09
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27 Jul 09
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21 Jul 09
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13 Jul 09
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09 Jul 09
Martin Lindner"the network as platform" means far more than just offering old applications via the network ("software as a service"); it means building applications that literally get better the more people use them, harnessing network effects not only to acquire users
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08 Jul 09
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07 Jul 09
Dennis Richards7.21.09
*...Web Squared. 1990-2004 was the match being struck; 2005-2009 was the fuse; and 2010 will be the explosion.
*...we’re constantly asked about "Web 3.0." Is it the semantic web? The sentient web? Is it the social web? The mobile web? Is it some form of virtual reality? It is all of those, and more.
*...successful network applications are systems for harnessing collective intelligence.
*The question before us is this: Is the Web getting smarter as it grows up?
*The Web is growing up, and we are all its collective parents.
*Key takeaway: A key competency of the Web 2.0 era is discovering implied metadata, and then building a database to capture that metadata and/or foster an ecosystem around it.
*The Net is getting smarter faster than you might think.
*The increasing richness of both sensor data and machine learning will lead to new frontiers in creative expression and imaginative reconstruction of the world.
*All of these breakthroughs are reflections of the fact noted by Mike Kuniavsky of ThingM, that real world objects have "information shadows" in cyberspace.
*In adding value for ourselves, we are adding value to the social web as well. Our devices extend us, and we extend them.
*Data analysis, visualization, and other techniques for seeing patterns in data are going to be an increasingly valuable skillset. Employers take notice.
*Anyone who searches Twitter on a trending topic has to be struck by the message: "See what’s happening right now" followed, a few moments later by "42 more results since you started searching. Refresh to see them."
*Businesses must learn to harness real-time data as key signals that inform a far more efficient feedback loop for product development, customer service, and resource allocation.
*But 2009 marks a pivot point in the history of the Web. It’s time to leverage the true power of the platform we’ve built. The Web is no longer an industry unto itself – the Web is now the world.
*...we must take the Web to another level. We can’t afford incremental evolution anymore. It’s -
06 Jul 09
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it means building applications that literally get better the more people use them, harnessing network effects not only to acquire users, but also to learn from them and build on their contributions.
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05 Jul 09
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02 Jul 09
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01 Jul 09
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Alex PopescuTim O'Reilly's unique perspective on the future of the internet
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"the network as platform" means far more than just offering old applications via the network ("software as a service"); it means building applications that literally get better the more people use them, harnessing network effects not only to acquire users, but also to learn from them and build on their contributions.
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Collective intelligence applications depend on managing, understanding, and responding to massive amounts of user-generated data in real time.
- 21 more annotations...
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Data is the "Intel Inside" of the next generation of computer applications.
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Many people now understand this idea in the sense of "crowdsourcing," namely that a large group of people can create a collective work whose value far exceeds that provided by any of the individual participants.
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But is this really what we mean by collective intelligence? Isn’t one definition of intelligence, after all, that characteristic that allows an organism to learn from and respond to its environment?
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Coordinating speech recognition and search, search results and location, is similar to the "hand-eye" coordination the baby gradually acquires. The Web is growing up, and we are all its collective parents.
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"data is the Intel Inside" of the next generation of computer applications. That is, if a company has control over a unique source of data that is required for applications to function, they will be able to extract monopoly rents from the use of that data. In particular, if a database is generated by user contribution, market leaders will see increasing returns as the size and value of their database grows more quickly than that of any new entrants.
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We see the era of Web 2.0, therefore, as a race to acquire and control data assets.
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machine learning techniques apply to far more than just sensor data. For example, Google’s ad auction is a learning system, in which optimal ad placement and pricing is generated in real time by machine learning algorithms.
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Some of the most fundamental and useful services on the Web have been constructed in this way, by recognizing and then teaching the overlooked regularity of what at first appears to be unstructured data.
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Ti Kan, Steve Scherf, and Graham Toal, the creators of CDDB, realized that the sequence of track lengths on a CD formed a unique signature that could be correlated with artist, album, and song names. Larry Page and Sergey Brin realized that a link is a vote. Marc Hedlund at Wesabe realized that every credit card swipe is also a vote, that there is hidden meaning in repeated visits to the same merchant. Mark Zuckerberg at Facebook realized that friend relationships online actually constitute a generalized social graph. They thus turn what at first appeared to be unstructured into structured data. And all of them used both machines and humans to do it.
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Key takeaway: A key competency of the Web 2.0 era is discovering implied metadata, and then building a database to capture that metadata and/or foster an ecosystem around it.
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Today’s smartphones contain microphones, cameras, motion sensors, proximity sensors, and location sensors (GPS, cell-tower triangulation, and even in some cases, a compass).
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mobile applications are connected applications. The fundamental lessons of Web 2.0 apply to any network application, whether web- or mobile phone-based (and the lines between the two are increasingly blurred). Sensor-based applications can be designed to get better the more people use them, collecting data that creates a virtuous feedback loop that creates more usage. Speech recognition in Google Mobile App is one such application. New internet-connected GPS applications also have built-in feedback loops, reporting your speed and using it to estimate arrival time based on its knowledge of traffic ahead of you. Today, traffic patterns are largely estimated; increasingly, they will be measured in real time.
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It’s the first taste of an "augmented reality" future.
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real world objects have "information shadows" in cyberspace. For instance, a book has information shadows on Amazon, on Google Book Search, on Goodreads, Shelfari, and LibraryThing, on eBay and on BookMooch, on Twitter, and in a thousand blogs.
A song has information shadows on iTunes, on Amazon, on Rhapsody, on MySpace, or Facebook. A person has information shadows in a host of emails, instant messages, phone calls, tweets, blog postings, photographs, videos, and government documents. A product on the supermarket shelf, a car on a dealer’s lot, a pallet of newly mined boron sitting on a loading dock, a storefront on a small town’s main street — all have information shadows now.
In many cases, these information shadows are linked with their real world analogues by unique identifiers: an ISBN or ASIN, a part number, or getting more individual, a social security number, a vehicle identification number, or a serial number. Other identifiers are looser, but identity can be triangulated: a name plus an address or phone number, a name plus a photograph, a phone call from a particular location undermining what once would have been a rock-solid alibi.
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What the Web 2.0 sensibility tells us is that we’ll get to the Internet of Things via a hodgepodge of sensor data contributing, bottom-up, to machine-learning applications that gradually make more and more sense of the data that is handed to them.
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As the information shadows become thicker, more substantial, the need for explicit metadata diminishes.
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Data analysis, visualization, and other techniques for seeing patterns in data are going to be an increasingly valuable skillset. Employers take notice.
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Mapping from unstructured data to structured data sets will be a key Web Squared competency.
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With services like Twitter and Facebook’s status updates, a new data source has been added to the Web – realtime indications of what is on our collective mind.
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Real-time is not limited to social media or mobile. Much as Google realized that a link is a vote, WalMart realized that a customer purchasing an item is a vote, and the cash register is a sensor counting that vote. Real-time feedback loops drive inventory. WalMart may not be a Web 2.0 company, but they are without doubt a Web Squared company: one whose operations are so infused with IT, so innately driven by data from their customers, that it provides them immense competitive advantage.
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Businesses must learn to harness real-time data as key signals that inform a far more efficient feedback loop for product development, customer service, and resource allocation.
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30 Jun 09
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The Web is no longer an industry unto itself – the Web is now the world.
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29 Jun 09
Christophe Deschamps!! Cet article est long mais ne pas le lire serait se priver d'éléments essentiels pour comprendre comment le web va encore se transformer (et transformer le monde). Il est de Tim O'Reilly, "découvreur" du web 2.0, et par John Battelle, spécialiste reconnu de la recherche sur le web.
ib Prospective intelligence économique UbiquitousComputing web2.0
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it means building applications that literally get better the more people use them, harnessing network effects not only to acquire users, but also to learn from them and build on their contributions.
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This leads to new levers of competitive advantage: Data is the "Intel Inside" of the next generation of computer applications.
- 28 more annotations...
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Data is being collected, presented, and acted upon in real time. The scale of participation has increased by orders of magnitude.
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we’re constantly asked about "Web 3.0." Is it the semantic web? The sentient web? Is it the social web? The mobile web? Is it some form of virtual reality?
It is all of those, and more.
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Imagine the Web (broadly defined as the network of all connected devices and applications, not just the PC-based application formally known as the World Wide Web) as a newborn baby. She sees, but at first she can’t focus. She can feel, but she has no idea of size till she puts something in her mouth. She hears the words of her smiling parents, but she can’t understand them. She is awash in sensations, few of which she understands. She has little or no control over her environment.
Gradually, the world begins to make sense. The baby coordinates the input from multiple senses, filters signal from noise, learns new skills, and once-difficult tasks become automatic.
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The question before us is this: Is the Web getting smarter as it grows up?
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All of a sudden, we’re not using search via a keyboard and a stilted search grammar, we’re talking to and with the Web. It’s getting smart enough to understand some things (such as where we are) without us having to tell it explicitly. And that’s just the beginning.
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Clearly, this is a "smarter" system than what we saw even a few years ago. Coordinating speech recognition and search, search results and location, is similar to the "hand-eye" coordination the baby gradually acquires. The Web is growing up, and we are all its collective parents.
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As we first noted back in 2003, "data is the Intel Inside" of the next generation of computer applications. That is, if a company has control over a unique source of data that is required for applications to function, they will be able to extract monopoly rents from the use of that data. In particular, if a database is generated by user contribution, market leaders will see increasing returns as the size and value of their database grows more quickly than that of any new entrants.
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We see the era of Web 2.0, therefore, as a race to acquire and control data assets.
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Some people imagine that for computer programs to understand and react to meaning, meaning needs to be encoded in some special taxonomy. What we see in practice is that meaning is learned "inferentially" from a body of data.
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Some of the most fundamental and useful services on the Web have been constructed in this way, by recognizing and then teaching the overlooked regularity of what at first appears to be unstructured data.
-
Ti Kan, Steve Scherf, and Graham Toal, the creators of CDDB, realized that the sequence of track lengths on a CD formed a unique signature that could be correlated with artist, album, and song names. Larry Page and Sergey Brin realized that a link is a vote. Marc Hedlund at Wesabe realized that every credit card swipe is also a vote, that there is hidden meaning in repeated visits to the same merchant. Mark Zuckerberg at Facebook realized that friend relationships online actually constitute a generalized social graph. They thus turn what at first appeared to be unstructured into structured data. And all of them used both machines and humans to do it.
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Key takeaway: A key competency of the Web 2.0 era is discovering implied metadata, and then building a database to capture that metadata and/or foster an ecosystem around it.
-
Sensor-based applications can be designed to get better the more people use them, collecting data that creates a virtuous feedback loop that creates more usage. Speech recognition in Google Mobile App is one such application.
-
A person has information shadows in a host of emails, instant messages, phone calls, tweets, blog postings, photographs, videos, and government documents.
-
Other identifiers are looser, but identity can be triangulated: a name plus an address or phone number, a name plus a photograph, a phone call from a particular location undermining what once would have been a rock-solid alibi.
-
What the Web 2.0 sensibility tells us is that we’ll get to the Internet of Things via a hodgepodge of sensor data contributing, bottom-up, to machine-learning applications that gradually make more and more sense of the data that is handed to them.
-
We don’t have to wait until each item in the supermarket has a unique machine-readable ID. Instead, we can make do with bar codes, tags on photos, and other "hacks" that are simply ways of brute-forcing identity out of reality.
-
As the information shadows become thicker, more substantial, the need for explicit metadata diminishes. Our cameras, our microphones, are becoming the eyes and ears of the Web, our motion sensors, proximity sensors its proprioception, GPS its sense of location. Indeed, the baby is growing up. We are meeting the Internet, and it is us.
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Data analysis, visualization, and other techniques for seeing patterns in data are going to be an increasingly valuable skillset. Employers take notice.
-
evidence shows that formal systems for adding a priori meaning to digital data are actually less powerful than informal systems that extract that meaning by feature recognition.
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Mapping from unstructured data to structured data sets will be a key Web Squared competency.
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Real-time search encourages real-time response. Retweeted "information cascades" spread breaking news across Twitter in moments, making it the earliest source for many people to learn about what’s just happened. And again, this is just the beginning.
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Which leads us to a timely debate: There are many who worry about the dehumanizing effect of technology. We share that worry, but also see the counter-trend, that communication binds us together, gives us shared context, and ultimately shared identity.
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Tweets are limited to 140 characters; the very limits of Twitter have led to an outpouring of innovation. Twitter users developed shorthand (@username, #hashtag, $stockticker), which Twitter clients soon turned into clickable links. URL shorteners for traditional web links became popular, and soon realized that the database of clicked links enable new real-time analytics.
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As a result, there’s a new information layer being built around Twitter that could grow up to rival the services that have become so central to the Web: search, analytics, and social networks. Twitter also provides an object lesson to mobile providers about what can happen when you provide APIs.
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Businesses must learn to harness real-time data as key signals that inform a far more efficient feedback loop for product development, customer service, and resource allocation.
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We need machine learning to be applied here, algorithms to detect anomalies, transparency that allows auditing by anyone who cares, not just by overworked understaffed regulators.
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But 2009 marks a pivot point in the history of the Web. It’s time to leverage the true power of the platform we’ve built. The Web is no longer an industry unto itself – the Web is now the world.
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28 Jun 09
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It’s also possible to give structure to what appears to be unstructured data by teaching an application how to recognize the connection between the two.
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Think of sensor-based applications as giving you superpowers.
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Mike Kuniavsky of ThingM, that real world objects have "information shadows" in cyberspace. For instance, a book has information shadows on Amazon, on Google Book Search, on Goodreads, Shelfari, and LibraryThing, on eBay and on BookMooch, on Twitter, and in a thousand blogs.
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brute-forcing identity out of reality.
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Each new load of data made the database smaller, not bigger. 630 million plus 30 million became 600 million, as the subtle calculus of recognition by "context accumulation" worked its magic.
As the information shadows become thicker, more substantial, the need for explicit metadata diminishes
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raman srinivasanFive years ago, we launched a conference based on a simple idea, and that idea grew into a movement. The original Web 2.0 Conference ( now the Web 2.0 Summit ) was designed to restore confidence in an industry that had lost its way after the dotcom bust. The Web was far from done, we argued. In fact, it was on its way to becoming a robust platform for a culture-changing generation of computer applications and services.
In our first program, we asked why some companies survived the dotcom bust, while others had failed so miserably. We also studied a burgeoning group of startups and asked why they were growing so quickly. The answers helped us understand the rules of business on this new platform.
Chief among our insights was that "the network as platform" means far more than just offering old applications via the network ("software as a service"); it means building applications that literally get better the more people use them, harnessing network effects not only to acquire users, but also to learn from them and build on their contributions.
From Google and Amazon to Wikipedia, eBay, and craigslist, we saw that the value was facilitated by the software, but was co-created by and for the community of connected users. Since then, powerful new platforms like YouTube, Facebook, and Twitter have demonstrated that same insight in new ways. Web 2.0 is all about harnessing collective intelligence.
Collective intelligence applications depend on managing, understanding, and responding to massive amounts of user-generated data in real time. The "subsystems" of the emerging internet operating system are increasingly data subsystems: location, identity (of people, products, and places), and the skeins of meaning that tie them together. This leads to new levers of competitive advantage: Data is the "Intel Inside" of the next generation of computer applications.
Today, we realize that these insights were not only directionally right, but are being applied in areas we only imagined in 2004. The smartphone revolution has mov -
26 Jun 09
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the network as platform
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Collective intelligence
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Web Squared
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successful network applications are systems for harnessing collective intelligence.
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Collective intelligence applications depend on managing, understanding, and responding to massive amounts of user-generated data in real time. The "subsystems" of the emerging internet operating system are increasingly data subsystems: location, identity (of people, products, and places), and the skeins of meaning that tie them together. This leads to new levers of competitive advantage: Data is the "Intel Inside" of the next generation of computer applications.
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Web Squared is our way of exploring this phenomenon and giving it a name.
- 22 more annotations...
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Web (broadly defined as the network of all connected devices and applications, not just the PC-based application formally known as the World Wide Web)
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Clearly, this is a "smarter" system than what we saw even a few years ago. Coordinating speech recognition and search, search results and location, is similar to the "hand-eye" coordination the baby gradually acquires. The Web is growing up, and we are all its collective parents.
-
"data is the Intel Inside"
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if a company has control over a unique source of data that is required for applications to function, they will be able to extract monopoly rents from the use of that data.
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There is a race on right now to own the social graph. But we must ask whether this service is so fundamental that it needs to be open to all.
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Vendors who are competing with a winner-takes-all mindset would be advised to join together to enable systems built from the best-of-breed data subsystems of cooperating companies.
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Key takeaway: A key competency of the Web 2.0 era is discovering implied metadata, and then building a database to capture that metadata and/or foster an ecosystem around it.
-
mobile applications are connected applications.
-
The increasing richness of both sensor data and machine learning will lead to new frontiers in creative expression and imaginative reconstruction of the world.
-
All of these breakthroughs are reflections of the fact noted by Mike Kuniavsky of ThingM, that real world objects have "information shadows" in cyberspace.
-
A person has information shadows in a host of emails, instant messages, phone calls, tweets, blog postings, photographs, videos, and government documents.
-
Other identifiers are looser, but identity can be triangulated: a name plus an address or phone number, a name plus a photograph, a phone call from a particular location undermining what once would have been a rock-solid alibi.
-
Our cameras, our microphones, are becoming the eyes and ears of the Web, our motion sensors, proximity sensors its proprioception, GPS its sense of location.
-
In adding value for ourselves, we are adding value to the social web as well. Our devices extend us, and we extend them.
-
Data analysis, visualization, and other techniques for seeing patterns in data are going to be an increasingly valuable skillset. Employers take notice.
-
But evidence shows that formal systems for adding a priori meaning to digital data are actually less powerful than informal systems that extract that meaning by feature recognition.
-
Mapping from unstructured data to structured data sets will be a key Web Squared competency.
-
There are many who worry about the dehumanizing effect of technology. We share that worry, but also see the counter-trend, that communication binds us together, gives us shared context, and ultimately shared identity.
-
Businesses must learn to harness real-time data as key signals that inform a far more efficient feedback loop for product development, customer service, and resource allocation.
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What have we learned from the consumer internet that could become the basis for a new 21st century financial regulatory system? We need machine learning to be applied here, algorithms to detect anomalies, transparency that allows auditing by anyone who cares, not just by overworked understaffed regulators.
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The Web is no longer an industry unto itself – the Web is now the world.
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It’s time for the Web to engage the real world. Web meets World – that’s Web Squared.
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Chief among our insights was that "the network as platform" means far more than just offering old applications via the network ("software as a service"); it means building applications that literally get better the more people use them, harnessing network effects not only to acquire users, but also to learn from them and build on their contributions.
-
From Google and Amazon to Wikipedia, eBay, and craigslist, we saw that the value was facilitated by the software, but was co-created by and for the community of connected users. Since then, powerful new platforms like YouTube, Facebook, and Twitter have demonstrated that same insight in new ways. Web 2.0 is all about harnessing collective intelligence.
- 29 more annotations...
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"Web 3.0." Is it the semantic web? The sentient web? Is it the social web? The mobile web? Is it some form of virtual reality?
-
Clearly, this is a "smarter" system than what we saw even a few years ago. Coordinating speech recognition and search, search results and location, is similar to the "hand-eye" coordination the baby gradually acquires. The Web is growing up, and we are all its collective parents.
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It’s easy to forget that only 15 years ago, email was as fragmented as social networking is today, with hundreds of incompatible email systems joined by fragile and congested gateways. One of those systems – internet RFC 822 email – became the gold standard for interchange.
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We expect to see similar standardization in key internet utilities and subsystems. Vendors who are competing with a winner-takes-all mindset would be advised to join together to enable systems built from the best-of-breed data subsystems of cooperating companies.
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Speech recognition and computer vision are both excellent examples of this kind of machine learning. But it’s important to realize that machine learning techniques apply to far more than just sensor data. For example, Google’s ad auction is a learning system, in which optimal ad placement and pricing is generated in real time by machine learning algorithms.
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Ti Kan, Steve Scherf, and Graham Toal, the creators of CDDB, realized that the sequence of track lengths on a CD formed a unique signature that could be correlated with artist, album, and song names. Larry Page and Sergey Brin realized that a link is a vote. Marc Hedlund at Wesabe realized that every credit card swipe is also a vote, that there is hidden meaning in repeated visits to the same merchant. Mark Zuckerberg at Facebook realized that friend relationships online actually constitute a generalized social graph. They thus turn what at first appeared to be unstructured into structured data. And all of them used both machines and humans to do it.
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Key takeaway: A key competency of the Web 2.0 era is discovering implied metadata, and then building a database to capture that metadata and/or foster an ecosystem around it.
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Think of sensor-based applications as giving you superpowers. Darkslide gives you super eyesight, showing you photos near you. iPhone Twitter apps can "find recent tweets near you" so you can get super hearing and pick up the conversations going on around you.
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There’s a fascinating fact noted by Jeff Jonas in his work on identity resolution. Jonas’ work included building a database of known US persons from various sources. His database grew to about 630 million "identities" before the system had enough information to identify all the variations. But at a certain point, his database began to learn, and then to shrink. Each new load of data made the database smaller, not bigger. 630 million plus 30 million became 600 million, as the subtle calculus of recognition by "context accumulation" worked its magic.
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As the information shadows become thicker, more substantial, the need for explicit metadata diminishes. Our cameras, our microphones, are becoming the eyes and ears of the Web, our motion sensors, proximity sensors its proprioception, GPS its sense of location. Indeed, the baby is growing up. We are meeting the Internet, and it is us.
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But as is so often the case, the future isn’t clearest in the pronouncements of big companies but in the clever optimizations of early adopters and "alpha geeks." Radar blogger Nat Torkington tells the story of a taxi driver he met in Wellington, NZ, who kept logs of six weeks of pickups (GPS, weather, passenger, and three other variables), fed them into his computer, and did some analysis to figure out where he should be at any given point in the day to maximize his take. As a result, he’s making a very nice living with much less work than other taxi drivers. Instrumenting the world pays off.
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Data analysis, visualization, and other techniques for seeing patterns in data are going to be an increasingly valuable skillset. Employers take notice.
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Projects to systematically categorize raw sensor data may be created, along the lines of the Astrometry project, whose founders claim, "We are building an ‘astrometry engine’ to create correct, standards-compliant astrometric meta data for every useful astronomical image ever taken, past and future, in any state of archival disarray." Using this engine, the Flickr astrotagger bot trolls Flickr for images of astronomical objects and gives them proper metadata, which then allows them to be included in astronomical image search by name. This is a service directly analogous to CDDB: a lookup service that maps messy sensor data to a regularized lookup database.
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As is often the case, the early examples are often the work of enthusiasts. But they herald a world in which entrepreneurs apply the same principles to new business opportunities. As more and more of our world is sensor-enabled, there will be surprising revelations in how much meaning – and value — can be extracted from their data streams.
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Mapping from unstructured data to structured data sets will be a key Web Squared competency.
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Real-time search encourages real-time response. Retweeted "information cascades" spread breaking news across Twitter in moments, making it the earliest source for many people to learn about what’s just happened. And again, this is just the beginning. With services like Twitter and Facebook’s status updates, a new data source has been added to the Web – realtime indications of what is on our collective mind.
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the very limits of Twitter have led to an outpouring of innovation.
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As a result, there’s a new information layer being built around Twitter that could grow up to rival the services that have become so central to the Web: search, analytics, and social networks. Twitter also provides an object lesson to mobile providers about what can happen when you provide APIs. Lessons from the Twitter application ecosystem could show opportunities for SMS and other mobile services, or it could grow up to replace them.
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Real-time is not limited to social media or mobile. Much as Google realized that a link is a vote, WalMart realized that a customer purchasing an item is a vote, and the cash register is a sensor counting that vote. Real-time feedback loops drive inventory. WalMart may not be a Web 2.0 company, but they are without doubt a Web Squared company: one whose operations are so infused with IT, so innately driven by data from their customers, that it provides them immense competitive advantage. One of the great Web Squared opportunities is providing this kind of real-time intelligence to smaller retailers without monolithic supply chains.
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"Everything in the world is now real time. So when a certain type of shoe isn’t selling at your corner shop, it’s not six months before the guy in China finds out. It’s almost instantaneous, thanks to my software."
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Another striking story we’ve recently heard about a real-time feedback loop is the Houdini system used by the Obama campaign to remove voters from the Get Out the Vote calling list as soon as they had actually voted. Poll watchers in key districts reported in as they saw names crossed off the voter lists; these were then made to "disappear" from the calling lists that were being provided to volunteers. (Hence the name Houdini.)
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Businesses must learn to harness real-time data as key signals that inform a far more efficient feedback loop for product development, customer service, and resource allocation.
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But 2009 marks a pivot point in the history of the Web. It’s time to leverage the true power of the platform we’ve built. The Web is no longer an industry unto itself – the Web is now the world.
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If we are going to solve the world’s most pressing problems, we must put the power of the Web to work – its technologies, its business models, and perhaps most importantly, its philosophies of openness, collective intelligence, and transparency. And to do that, we must take the Web to another level. We can’t afford incremental evolution anymore.
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The US Federal government has made a major commitment to transparency and open data. Data.gov now hosts more than 100,000 data feeds from US government sources, and the White House blog is considering a commitment to the 8 Open Data Principles articulated by a group of open data activists in late 2007. There’s a celebration of the successes that many are now calling "Government 2.0." We’d love to hear about Government 2.0 success stories from around the world.
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But in his advice on the direction of the Government 2.0 Summit Federal CTO Aneesh Chopra has urged us not to focus on the successes of Web 2.0 in government, but rather on the unsolved problems. How can the technology community help with such problems as tracking the progress of the economic stimulus package in creating new jobs? How can it speed our progress towards energy independence and a reduction in CO2 emissions? How can it help us remake our education system to produce a more competitive workforce? How can it help us reduce the ballooning costs of healthcare?
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- Companies like 23andMe and PatientsLikeMe are applying crowdsourcing to build databases of use to the personalized medicine community. 23andMe provides genetic testing for personal use, but their long term goal is to provide a database of genetic information that members could voluntarily provide to researchers. PatientsLikeMe has created a social network for people with various life-changing diseases; by sharing details of treatment – what’s working and what’s not – they are in effect providing a basis for the world’s largest longitudinal medical outcome testing service. What other creative applications of Web 2.0 technology are you seeing to advance the state of the art in healthcare?
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- Forward looking companies are adopting real-time monitoring and management to build smarter supply chains, manage remote resources, and in general, improve their return on investment using what Doug Standley at Deloitte calls "Asset Intelligence." We’d love to hear examples from people who are deploying these technologies.
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- Real-time traffic monitoring systems like Microsoft Clearflow reduce wasted time and energy commuting. Web services reporting progress of buses and trains against their scheduled times make public transit more effective and enjoyable. These are tangible consumer benefits from instrumenting the world. Sensor-driven congestion pricing schemes like the one IBM built for the city of Stockholm create economic incentives to reduce traffic at peak times. These initiatives also raise privacy issues. We’re interested in hearing about success stories – and scare stories – about the way that instrumenting the world changes the way we live.
- Smart Grid initiatives will reduce our energy usage by increasing the intelligence of the system used to deliver it. As hinted at above, though, they will also open a whole new front in the war on privacy. The data that will be revealed by smart grid applications will not only make our utilities smarter, it will likely make marketers a lot smarter too. It is unlikely, though, to make them more humane and less intrusive!
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25 Jun 09
Taryn .With more users and sensors feeding more applications and platforms, developers are able to tackle serious real-world problems. As a result, the Web opportunity is no longer growing arithmetically
software collaboration crowd_sourcing data social_network twitter flickr cell_phone search Google augmented_reality pay_attention!
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"the network as platform" means far more than just offering old applications via the network ("software as a service"); it means building applications that literally get better the more people use them, harnessing network effects not only to acquire users, but also to learn from them and build on their contributions.
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Google Mobile Application for the iPhone. The application detects the movement of the phone to your ear, and automatically goes into speech recognition mode. It uses its microphone to listen to your voice, and decodes what you are saying by referencing not only its speech recognition database and algorithms, but also the correlation to the most frequent search terms in its search database. The phone uses GPS or cell-tower triangulation to detect its location, and uses that information as well. A search for "pizza" returns the result you most likely want: the name, location, and contact information for the three nearest pizza restaurants.
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The Wikitude travel guide application for Android takes image recognition even further. Point the phone’s camera at a monument or other point of interest, and the application looks up what it sees in its online database (answering the question "what looks like that somewhere around here?") The screen shows you what the camera sees, so it’s like a window but with a heads-up display of additional information about what you’re looking at. It’s the first taste of an "augmented reality" future. It superimposes distances to points of interest, using the compass to keep track of where you’re looking. You can sweep the phone around and scan the area for nearby interesting things.
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Microsoft’s Photosynth demonstrates the power of the computer to synthesize 3D images from crowdsourced photographs. Gigapixel photography reveals details that were invisible even to people on the scene. Adobe’s Infinite Images reveals something even more startling: the ability of the computer to synthesize imaginary worlds that never existed, extrapolating a complete 3D experience from a set of photos. The video demonstration needs to be seen to be believed.
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evidence shows that formal systems for adding a priori meaning to digital data are actually less powerful than informal systems that extract that meaning by feature recognition. An ISBN provides a unique identifier for a book, but a title + author gets you close enough.
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in his advice on the direction of the Government 2.0 Summit Federal CTO Aneesh Chopra has urged us not to focus on the successes of Web 2.0 in government, but rather on the unsolved problems. How can the technology community help with such problems as tracking the progress of the economic stimulus package in creating new jobs? How can it speed our progress towards energy independence and a reduction in CO2 emissions? How can it help us remake our education system to produce a more competitive workforce? How can it help us reduce the ballooning costs of healthcare?
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