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Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
Intelligentcontent2009
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Intelligentcontent2009

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What is Intelligent Content …

What is Intelligent Content
How has content on the internet evolved
Some examples of intelligent content, both online and offline
What do we see on the internet going forward?

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  • Transcript

    • 1. Opening Keynote Address Salim Ismail January 29, 2009
    • 2. Objectives for today <ul><li>Intelligent Content is… a definition </li></ul><ul><li>Content on the web… an evolution </li></ul><ul><ul><li>evolution of data/infrastructure on the internet </li></ul></ul><ul><ul><li>Social Media </li></ul></ul><ul><ul><li>Examples of intelligent applications </li></ul></ul><ul><li>Where else is content intelligent? (off-web) </li></ul><ul><li>Back to the Web – what’s next? </li></ul><ul><li>Q&A </li></ul>
    • 3. Who Am I? <ul><li>India/Canada/Europe/U.S (a decade each) </li></ul><ul><li>Degree in theoretical physics </li></ul><ul><li>Five years large scale database design </li></ul><ul><li>Five years restructuring large European orgs </li></ul><ul><li>Seven early stage companies </li></ul><ul><ul><li>Six years of internet startups </li></ul></ul><ul><ul><li>Five of my own (PubSub, Confabb, Ångströ…) </li></ul></ul><ul><li>One year as VP Yahoo!, Head of Brickhouse </li></ul><ul><ul><li>Internal VC fund, analyzed 3000 ideas </li></ul></ul><ul><ul><li>Sponsored four </li></ul></ul><ul><ul><ul><li>Yahoo Pipes (prototype), BravoNation, Y!Live, Fire Eagle </li></ul></ul></ul>Next gig to be announced in four days
    • 4. What is ‘Intelligent Content ’ <ul><li>Content </li></ul><ul><ul><ul><li>Data of some kind </li></ul></ul></ul><ul><ul><ul><li>Wrapper </li></ul></ul></ul><ul><ul><ul><li>Associated metadata </li></ul></ul></ul><ul><li>The dream of the Semantic Web </li></ul><ul><ul><li>“ the semantics of information and services on the web is defined, making it possible for the web to understand and satisfy the requests of people and machines to use the web content . It derives from World Wide Web Consortium director Sir Tim Berners-Lee 's vision of the Web as a universal medium for data , information , and knowledge exchange.” </li></ul></ul><ul><ul><li>All data, fully self-described for whatever purpose is required (slightly utopian… rather difficult) </li></ul></ul>
    • 5. What is ‘ Intelligent Content’ <ul><li>Many types of intelligence: </li></ul><ul><li>Gardner: logical , linguistic , spatial , musical , kinesthetic , naturalist , intrapersonal , interpersonal and social intelligence </li></ul><ul><li>Sternberg: </li></ul><ul><ul><li>Practical / Contextual - deals with the mental activity involved in attaining fit to context ” </li></ul></ul><ul><ul><ul><li>Uses adaptation, shaping, and selection </li></ul></ul></ul><ul><ul><li>Experiental / Creative </li></ul></ul><ul><ul><ul><li>Experience breaks down into novel/automated </li></ul></ul></ul><ul><ul><li>Componential / Analytical </li></ul></ul><ul><ul><ul><li>Break down problems and intuit solutions </li></ul></ul></ul>
    • 6. For our purposes… <ul><li>Intelligence: </li></ul><ul><ul><li>The ability to take a pattern from one frame of reference an apply it to another </li></ul></ul><ul><li>Chess program </li></ul><ul><li>Pagerank </li></ul><ul><li>Cross data sets </li></ul><ul><li>Conditional </li></ul><ul><li>Intuitive (emotional) </li></ul><ul><li>Sophisticated/complex </li></ul>Sophisticated (intuitive) PM Contextual/Conditional Pattern Matching Basic (Numerical) Pattern Matching
    • 7. Two definitions of “Intelligent Content” <ul><li>Content can be considered intelligent when it expresses, in an open way, the full meaning underlying a communication such that the data, information and knowledge being expressed can be easily accessed and effectively leveraged by both people and the software applications that support them. - Joe Gollner </li></ul><ul><li>Structurally rich and semantically aware, and is therefore automatically discoverable, reusable, reconfigurable and adaptable - Ann Rockley </li></ul>
    • 8. More on intelligence <ul><li>Pattern Recognition is a key aspect of intelligence, but you also have Pattern creation? </li></ul><ul><li>Patterns interacting with other patterns create new patterns (in other words, mashups : ) </li></ul><ul><li>Stephen Wolfram – “A New Kind of Science” </li></ul><ul><li>Class 1 Automata </li></ul>
    • 9. Digressing to ‘Repetition’ <ul><li>Class 1 </li></ul><ul><li>Class 2 </li></ul><ul><li>Class 3 </li></ul>
    • 10. More on Repetition (recursive PM) <ul><li>Class 4 </li></ul><ul><li>Reflections on Stephen Wolfram's &quot;A New Kind of Science&quot; </li></ul><ul><ul><li>http :// www. kurzweilai.net/meme/frame.html?main =/articles/art0464.html </li></ul></ul>
    • 11. Intelligent Content – Summary <ul><li>Context is key </li></ul><ul><ul><li>Who, what, where, when… (why) </li></ul></ul><ul><li>Pattern management across frames of reference </li></ul><ul><ul><li>In documents, SGML > XML > DITA > ?? </li></ul></ul><ul><li>Eventually, pattern management (intelligence) will be embedded in the content (document) </li></ul><ul><li>W- ar- goin- on ho-iday w-th som- f-iends n-x- we-k </li></ul><ul><li>Se- -ou wh-n w- ge- ba-k </li></ul><ul><ul><li>25% of letters missing, yet meaning is conveyed </li></ul></ul>
    • 12. More pattern matching
    • 13. Next topic… <ul><li>Intelligent Content is… a definition </li></ul><ul><li>Content on the web… an evolution </li></ul><ul><ul><li>evolution of data/infrastructure on the internet </li></ul></ul><ul><ul><li>Social Media </li></ul></ul><ul><ul><li>Examples of intelligent applications </li></ul></ul><ul><li>Where else is content intelligent? (off-web) </li></ul><ul><li>Back to the Web – what’s next? </li></ul><ul><li>Q&A </li></ul>
    • 14. Content on the Web <ul><li>What’s going on ?? </li></ul><ul><ul><li>What is the 50,000 foot view? (15,240 m ) </li></ul></ul><ul><li>How we got here – some history/context </li></ul><ul><ul><li>Information flows </li></ul></ul><ul><ul><li>Technology Framework </li></ul></ul><ul><ul><li>Internet 3.0 </li></ul></ul><ul><li>The Social Media wave </li></ul><ul><li>Examples </li></ul>Image: Kevin Kelly
    • 15. There’s lots going on today… ! <ul><li>Yahoo/Google/Microsoft/AOL/Facebook </li></ul><ul><li>Blogs/feeds/RSS/ATOM//microblogging/lifestreaming </li></ul><ul><li>Friendster/LinkedIn/Myspace/Bebo/Facebook </li></ul><ul><li>Facebook Feed/FriendFeed/FriendFeedFilter/FeedaFriend </li></ul><ul><li>Adsense/Panama/Beacon/adCenter </li></ul><ul><li>Twitter/Twhirl/Tweetdeck/Twitterfone/Twitscan/TwitSnooze </li></ul><ul><li>OpenID/IdentityCommons/IdentityGang/IdentityWoman </li></ul><ul><li>Dataportability/Data Availability/OpenSocial… nottoosocialyet/FriendConnect/FacebookConnect/everybodybloodyconnect </li></ul><ul><li>Icannotakeanymoreofthispleasestop </li></ul>
    • 16. And a few companies…
    • 17. Some call it Web 2.0 <ul><li>According to Tim O’Reilly…. </li></ul>Fundamentally: user participation (UGC) + Syndication
    • 18. Led by Blogs <ul><li>Last few years - blogs exploded in use </li></ul><ul><ul><li>With the rise of the web in the 90s, we had millions of readers, but relatively few publishers (e.g. CNN, CNet) </li></ul></ul><ul><ul><li>Now, due to the ease of publishing with blogs and other tools, we now also have millions of publishers </li></ul></ul><ul><ul><ul><li>1m in 01/04, 10m in 01/05, 50m in 2006 and over 100m today </li></ul></ul></ul><ul><li>Blogs now ‘overtaken’ </li></ul><ul><ul><li>Top Bloggers: stratifying into self-publishing journalists/pundits </li></ul></ul><ul><ul><li>Flickr, MySpace, FaceBook, Bebo et al covering the rest </li></ul></ul><ul><ul><li>User Generated Content splashing about everywhere </li></ul></ul><ul><ul><li>Morphing into micro-blogging/lifestreaming </li></ul></ul>
    • 19. Other Web 2.0 Descriptors <ul><li>Services (as opposed to data) </li></ul><ul><li>UGC (User Generated Content).. e.g. blogs </li></ul><ul><li>Manipulate and ‘use’ data, not just presentation </li></ul><ul><li>Low latency (real time) </li></ul><ul><li>Data aggregation </li></ul><ul><li>Social Networking </li></ul><ul><li>Examples </li></ul><ul><ul><li>Flickr, Buzznet, Dabble </li></ul></ul><ul><ul><li>Wordpress, Typepad, Drupal </li></ul></ul><ul><ul><li>Eventful, Upcoming, Edgeio </li></ul></ul><ul><ul><li>YouTube, MySpace, FaceBook </li></ul></ul>Web 2.0: Facilitate Consumer to Consumer
    • 20. Aggregators Blogs RSS Readers RSS Feeds Closed Syndication or Branding Browsers Web Pages Search Engines Internet Information Flows Open Syndication or Branding Pings Create/Publish/Discover Syndicate/Aggregate Read/Consume/Process Web 2.0 Web 1.0 Walled Garden DBs
    • 21. Blogs Aggregators RSS Feeds Browsers Web Pages Search Engines Internet Information Flows Pings Open Syndication or Branding craigslist Closed Syndication or Branding Create/Publish/Discover Syndicate/Aggregate Read/Consume/Process Web 2.0 Web 1.0 Walled Gardens
    • 22. Four key drivers… Syndication XML Low Latency Great UX
    • 23. Web 2.0 = Internet 3.0 <ul><li>Web 2.0 = Internet 3.0 </li></ul><ul><li>Structured Data (XML) Syndication is starting to take hold </li></ul><ul><li>Event-based (Publish/Subscribe) </li></ul><ul><li>Participatory UX = consumer to consumer </li></ul><ul><ul><li>Latest wave in internet companies (Facebook, YouTube) </li></ul></ul>
    • 24. Internet 3.0 We are increasingly watching … Messaging Request Response Publish Subscribe What’s your email address? Sending What’s your Website? Searching What’s your Blog/FB/Tw Watching Information Exchange Patterns Evolution of the Internet 80s Email 90s Web Browser 00s RSS Aggregator
    • 25. Social Media Arrives <ul><li>Web – started as documents with linking </li></ul><ul><li>Documents with links became nodes </li></ul><ul><li>XML added metadata </li></ul><ul><li>Lots of arbitrary data (about you) can now be added to the web </li></ul><ul><ul><li>Location </li></ul></ul><ul><ul><li>Identity </li></ul></ul><ul><ul><li>Friends </li></ul></ul><ul><ul><li>Preferences </li></ul></ul><ul><ul><li>Assets </li></ul></ul><ul><ul><li>Purchases </li></ul></ul>
    • 26. Why is Social Media big? <ul><li>We are biological creatures </li></ul><ul><li>Driven by social constructs </li></ul><ul><li>“Who you know” drives a lot of what we do </li></ul><ul><li>Context drives 80% of information value </li></ul><ul><ul><li>Who speaks gives a lot of context </li></ul></ul>
    • 27. Social Contexts <ul><li>Who do I know (Social Networks) : </li></ul><ul><li>Flickr, Upcoming, MySpace, Bebo, FaceBook </li></ul><ul><li>What am I doing (status updaters) : </li></ul><ul><li>Twitter, Identi.ca, Skype, FB, Plaxo </li></ul><ul><li>Where am I (location brokers) </li></ul><ul><li>Fire Eagle, Plazes, Loopt, </li></ul><ul><li>Brightkite </li></ul>Gov’t Data Enterprise Data E-commerce Transactional data (reviews/ratings) (offers for sale) (events) Self-publishing (where am I) (what am I doing) SN Profiles Blogs (about me) HTML Create/Publish/Discover Syndicate/Aggregate Read/Consume/Process Web 2.0 Web 1.0 Aggregators Blogs RSS Readers RSS Feeds Closed Syndication or Branding Browsers Web Pages Search Engines Walled Garden DBs Open Syndication or Branding Pings Social Networks Mini Feeds Closed Syndication or Branding Social Networks (email)
    • 28. Create/Publish/Discover Syndicate/Aggregate Read/Consume/Process Web 2.0 Web 1.0 Aggregators Blogs RSS Readers RSS Feeds Closed Syndication or Branding Browsers Web Pages Search Engines We are just at the beginning Open Syndication or Branding Pings Social Networks Mini Feeds Closed Syndication or Branding Social Networks (email) Twhirl EMAIL !!! Walled Garden DBs craigslist
    • 29. A web of data – Tom Coates <ul><li>http://www.plasticbag.org/files/native/native_to_a_web_of_data.pdf </li></ul>
    • 30. Web Architecture – Dion Hinchcliffe
    • 31. Thoughts on Social Media <ul><li>SM has become the starting point for consumers </li></ul><ul><li>But, computers are binary, relationships aren’t </li></ul><ul><ul><li>80/20 rule </li></ul></ul><ul><ul><li>SNs will hold who’s connected to whom, but not more </li></ul></ul><ul><li>Leverage with other types of information </li></ul>
    • 32. Evolution of a Platform <ul><li>New paradigm appears </li></ul><ul><li>Some companies launch </li></ul><ul><li>One gets traction and quickly dominates </li></ul><ul><li>Walled Gardens take hold </li></ul><ul><li>The competition fights back and force openness </li></ul><ul><li>Walled Gardens collapse kicking and screaming </li></ul><ul><li>Saturation </li></ul><ul><li>New Paradigm appears (go to step 1) </li></ul>Social Media
    • 33. Problem Spaces in Social Media <ul><li>Overload </li></ul><ul><ul><li>filtering </li></ul></ul><ul><li>Underload </li></ul><ul><ul><li>discovery </li></ul></ul><ul><li>Disambiguation </li></ul><ul><ul><li>identity </li></ul></ul><ul><li>Duplication (republishing) </li></ul>
    • 34. Example: Ångströ <ul><li>News published by people on your social networks has proven to be “intriguing and addictive” </li></ul><ul><li>News published about professionals in your network is actionable and often business critical </li></ul><ul><ul><li>A board member raises a new fund </li></ul></ul><ul><ul><li>A colleague gets promoted </li></ul></ul><ul><ul><li>An investor is featured in the news </li></ul></ul><ul><li>Google Alerts is about the only tool… </li></ul>
    • 35. A Social Graph (400
    • 36. News About Your Network <ul><li>Enter LinkedIn credentials </li></ul><ul><li>Analyze bios and profiles </li></ul><ul><li>Crawl news sources </li></ul><ul><li>Apply algorithms </li></ul><ul><li>Rank stories by: </li></ul><ul><ul><li>Recency </li></ul></ul><ul><ul><li>KudoRank </li></ul></ul><ul><ul><li>NameSense </li></ul></ul><ul><ul><li>Source Quality </li></ul></ul><ul><ul><li>User Feedback </li></ul></ul><ul><li>Newspaper interface </li></ul><ul><li>User comments & votes </li></ul>Discover and share business-critical news
    • 37. The News Cycle <ul><li>Discovery is increasingly happening via SM </li></ul>Mary Meeker
    • 38. Example: Confabb
    • 39. Live Traffic
    • 40. Yelp <ul><li>Intersecting multiple data sets </li></ul><ul><li>Users </li></ul><ul><li>Review </li></ul><ul><li>Comments </li></ul><ul><li>Feedback </li></ul><ul><li>Ratings </li></ul>
    • 41. Intelligent Yelps Doctors Service Types Bars Location Mechanical Turk Restaurants Ratings Comments Reputation Favorites Sophisticated (intuitive) PM Contextual/Conditional Pattern Matching Basic (Numerical) Pattern Matching
    • 42. Next topic… <ul><li>Intelligent Content is… a definition </li></ul><ul><li>Content on the web… an evolution </li></ul><ul><ul><li>evolution of data/infrastructure on the internet </li></ul></ul><ul><ul><li>Social Media </li></ul></ul><ul><ul><li>Examples of intelligent applications </li></ul></ul><ul><li>Where else is content intelligent? (off-web) </li></ul><ul><li>Back to the Web – what’s next? </li></ul><ul><li>Q&A </li></ul>
    • 43. Layered Intelligence GPS GPS Navigation RFID Robotics Mechanical Turk Sensors Supply Chain Mechanical Turk Crowd-Sourcing Sophisticated (intuitive) PM Contextual/Conditional Pattern Matching Basic (Numerical) Pattern Matching
    • 44. AI & Robotics <ul><li>Ubiquitous computing and more-powerful computers </li></ul><ul><li>Huge amounts of data from the Internet and physical sensors </li></ul><ul><li>Algorithms that learn and improve over time </li></ul><ul><li>Software that's able to deal with uncertainty, incompleteness and surprises </li></ul><ul><li>Software agents that can weigh costs and benefits </li></ul><ul><li>Integration of separate fields such as speech, vision, robotics, sensors and machine learning </li></ul><ul><li>Computerworld.com – 1/26/09 - http://bit.ly/ts5Q </li></ul>
    • 45. Not far away… <ul><li>3D printing of organs Artificial Retinas </li></ul>Christopher deCharms http://abcnews.go.com/Technology/story?id=1603783&page=1
    • 46. Next topic… <ul><li>Intelligent Content is… a definition </li></ul><ul><li>Content on the web… an evolution </li></ul><ul><ul><li>evolution of data/infrastructure on the internet </li></ul></ul><ul><ul><li>Social Media </li></ul></ul><ul><ul><li>Examples </li></ul></ul><ul><li>Where else is content intelligent? (off-web) </li></ul><ul><li>Back to the Web – what’s next? </li></ul><ul><li>Q&A </li></ul>
    • 47. Internet 3.0 – The Nervous System <ul><li>The internet is evolving into a complex organism </li></ul><ul><li>Search is the memory </li></ul><ul><li>Web 2.0 provides the basis for the nervous system </li></ul>The key question is: “ Whenever…”
    • 48. Types of Structured Content Gov’t Data Enterprise Data E-commerce Transactional data (reviews/ratings) (offers for sale) (events) Self-publishing (where am I) (what am I doing) SN Profiles Blogs (about me) HTML Create/Publish/Discover Syndicate/Aggregate Read/Consume/Process Web 2.0 Web 1.0 Aggregators Blogs RSS Readers RSS Feeds Closed Syndication or Branding Browsers Web Pages Search Engines Walled Garden DBs Open Syndication or Branding Pings Social Networks Mini Feeds Closed Syndication or Branding Social Networks (email) 80s Email 90s Web Browser 00s RSS Aggregator Messaging Request Response Publish Subscribe What’s your email address? Sending What’s your Website? Searching What’s your Feed/Blog? Watching Information Exchange Patterns Evolution of the Internet
    • 49. CONTENT ON THE WEB Crowd-sourcing ideas Artist: Aaron Koblin
    • 50. The next 5000 days on the web <ul><li>http://splicd.com/yDYCf4ONh5M/137/354 </li></ul><ul><li>Today… </li></ul>
    • 51. Layered Intelligence Gov’t Data Enterprise Data E-commerce Transactional data (reviews/ratings) (offers for sale) (events) Self-publishing (where am I) (what am I doing) SN Profiles Blogs (about me) HTML Sophisticated (intuitive) PM Contextual/Conditional Pattern Matching Basic (Numerical) Pattern Matching
    • 52. Thanks…. http://salimismail.com ww.twitter.com/salimismail

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