Nova Spivack founded an internet company in 1998 that had a successful IPO. However, instead of retiring, he wanted to build something bigger - a web of knowledge. He founded Lucid Ventures to do research and eventually built Personal Radar, a semantic desktop. It was later spun out as Radar Networks. Personal Radar was later selected to join the DARPA CALO project. Twine was then founded to build a web-scale knowledge network for consumers but faced challenges from the economic downturn. Twine is now focusing on a new approach called T2 that indexes semantics on the web automatically to provide semantic search and tools for developers.

1. Semantic Search 3.0 A Yarn about Twine ISWC 2009 Keynote Nova Spivack Founder, CEO Twine.com nova@twine.com

2. In 1998 my first Internet companyEarthWebMakers of Developer.com & Dice.comhad a ginormous IPO w00t!!! 2 1.11.2008 | Product Positioning

3. At 29 years old, I was set for life**On paper…. 3 1.11.2008 | Product Positioning

4. But instead of retiring Youth and idealism won out 4 1.11.2008 | Product Positioning

5. I wanted to build something REALLY big…A Web of knowledge 5 1.11.2008 | Product Positioning

6. So I self-funded my own mini R&D lab, Lucid Ventures 6 1.11.2008 | Product Positioning

7. Kris Thorisson (PhD) Jim Wissner (Java whiz)And a bunch of others… 7 1.11.2008 | Product Positioning

8. Lucid grew to a few PhD’s And a bunch of engineers We did lots of exploring. In Java. 8 1.11.2008 | Product Positioning

10. Cross-platform, Pure Java

11. Fully semantic, RDF and OWL based

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18. Screenshots 16 1.11.2008 | Product Positioning

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24. Oh yeah,And I also angel invested in a bunch of startupsAnd bought up more EarthWeb stock. w00t! 22 1.11.2008 | Product Positioning

25. Then the Bubble burst…* *WTF??? 23 1.11.2008 | Product Positioning

26. Nuclear winter for IT and Web venturesBegan… 24 1.11.2008 | Product Positioning

27. DON’T TRY THIS AT HOME 25 1.11.2008 | Product Positioning

28. Despite the Economy, We Continued to Press ForwardWith our product plan 26 1.11.2008 | Product Positioning

29. But there was no venture fundingAvailable anywhere**VC’s are scaredy cats 27 1.11.2008 | Product Positioning

30. Luckily,a few days before we ran out of money… 28 1.11.2008 | Product Positioning

31. SRI selected us to join the DARPA CALO project 29 1.11.2008 | Product Positioning

32. Personal Radar became part of OpenIRIS* See: OpenIRIS.org *Cool project 30 1.11.2008 | Product Positioning

33. 2004 - 2005We worked on DARPA CALO & IRIS2006Series A venture roundFinished our work on CALO & IRISStarted to work on our own products 31 1.11.2008 | Product Positioning

34. Our GoalWeb-Scale Knowledge Networking For Consumers 32 1.11.2008 | Product Positioning

35. ObstacleThere was no platform that met our needs at the time. Not even our own.So from 2006 – 2007 we built one**Insane 33 1.11.2008 | Product Positioning

36. To accomplish this,using RDF and OWLOn a triplestorewe really had to push the envelope 34 1.11.2008 | Product Positioning

37. We built a big federated tuplestoreSupport up to 100 billion tuples Full ACL permissions on the data Capable of serving millions of consumers 35 1.11.2008 | Product Positioning

38. In 2008 the platform was ready We started building apps on it 36 1.11.2008 | Product Positioning

39. October 2008 Twine went Beta 37 1.11.2008 | Product Positioning

40. A Slightly Ambitious Project*Semantic WebNatural language processingEntity detectionGraph theoryClusteringRecommendationsSemantic filteringCollaborative authoringAuto-taggingSummarizationVisualizationPersonalization*What the (bleep) were we thinking? 38 1.11.2008 | Product Positioning

41. March 2009 We raised a $14mm Series B round A total of $24mm raised so far…**Ok, that’s what we were thinking… 39 1.11.2008 | Product Positioning

42. Twine grew faster than expectedConsumers actually were using it**Hey, this #$%@ works 40 1.11.2008 | Product Positioning

43. Within 6 months of launch…Up to 2.2mm unique visitors monthly 4mm pieces of content added 25K interest groups 100’s of articles about it Twine grew faster than Twitter**Our VCs were happy 41 1.11.2008 | Product Positioning

44. But Twine was not finished A lot more work was needed And we were gearing up Hiring, designing, coding, spending… 42 1.11.2008 | Product Positioning

45. We grew to over 30 people.Mostly engineers. But we really needed more like 70. 43 1.11.2008 | Product Positioning

46. But we were optimistic and focused onDesigning the next version of Twine 44 1.11.2008 | Product Positioning

47. Then the economy tankedAgain….. 45 1.11.2008 | Product Positioning

48. Silicon Valley became a lot less happyAll venture funding dried up 46 1.11.2008 | Product Positioning

49. So, like many other venturesWe had to cut back drasticallyon spending, hiring, and our product goals 47 1.11.2008 | Product Positioning

50. Lessons LearnedTwine 1.0 tried to solve too many problemsToo many featuresToo hard to figure outOur data revealed that Twine users mainly just want to search and track interests 48 1.11.2008 | Product Positioning

51. Lessons LearnedWe should not have relied on a tuplestore so centrally in the Twine 1.0 architectureWe haven’t yet seen a tuplestore that fully meets the needs of a major consumer online web site like Twine 49 1.11.2008 | Product Positioning

52. The Web 2.0 party was over.Where to go from here?… A Radical Rethink 50 1.11.2008 | Product Positioning

53. Continuing on the path we were onwould be too expensive to scaleMust change the architecture, or change the product,or both**We chose “or both” 51 1.11.2008 | Product Positioning

54. The Future of Search Confidential

55. Where Search is Headed Semantic Personalized Real-time Social Sharing Tracking KM Reasoning 53 1.11.2008 | Product Positioning

56. But the Semantic Web Hasn’tHappened Yet… At least not for consumers And most Web developers… 54 1.11.2008 | Product Positioning

57. Why hasn’t the Semantic Web taken off yet? 55 1.11.2008 | Product Positioning

58. How can we demonstrate the value of the Semantic Web to consumers?And make it easily useful to Web developers?In the near-term? 56 1.11.2008 | Product Positioning

59. Let’s Get Real Consumer are not going to add semantic metadata Webmasters are too lazy, or don’t know how Humans are bad at generating good metadata anyway Automated metadata generation is the only practical solution 57 1.11.2008 | Product Positioning

60. Index the Semantics of the Web Create the Semantic Web From the non-Semantic Web Automatically Provide it back as a Web service 58 1.11.2008 | Product Positioning

61. Provide faceted semantic search and navigation against the indexAt Web-scale 59 1.11.2008 | Product Positioning

62. Kind of a Semantic Google IBM.com Web Site Joe Person IBM Company Palo Alto City Lives in Publisher of Fan of Lives in Subscriber to Employee of Sue Person Jane Person Dave.com RSS Feed Coldplay Band Fan of Friend of Member of Design Team Group Depiction of Married to Source of 123.JPG Photo Member of Bob Person Dave.com Weblog Depiction of Member of Dave Person Stanford Alumnae Group Member of Author of Member of Person Application

63. But not on anything close to Google’s budget 61 1.11.2008 | Product Positioning

64. What were we smoking?**We were not Freebasing 62 1.11.2008 | Product Positioning

65. Well it turns out, it’s not impossible… 63 1.11.2008 | Product Positioning

66. T2 64 1.11.2008 | Product Positioning

67. The T2 Approach… 65 1.11.2008 | Product Positioning Focus on search Keep it simple Broad appeal Scale cheaply Connect with ecosystem

68. T2 ArchitectureHigh-performanceOpen-ended scalingMore semantic (RDF, OWL)Not built directly on a triplestoreNot built directly on a databaseHeavy use of SOLR (from Lucene) 66 1.11.2008 | Product Positioning

69. T2 Stack 67 1.11.2008 | Product Positioning Twine Properties Partners/3rd Parties WebApp Framework APIs Application Services Resource Service Web Corpus (e.g., BOSS, etc) Semantic Metadata Service Tuple Service SOLR Farm RDBMS

70. T1 Approach Human Tagging AI Semantic Web Make the Data Smarter Machine Tagging Linguistics Extraction Statistics Make the software smarter

71. T2 Approach Semantic Web Make the Data Smarter Linguistics Extraction Statistics Make the software smarter

72. A Tactical Shift Freebase DBpedia Make the Data Smarter Twine T1 EVRI Wolfram Alpha Wikipedia Open Calais Endeca Expert System Flickr Bing Siri FAST Powerset Yahoo Delicious Autonomy Inxight Hakia Google Make the software smarter

73. To a More Mainstream App Freebase Twine T2 DBpedia Make the Data Smarter Twine T1 EVRI Wolfram Alpha Wikipedia Open Calais Endeca Expert System Flickr Bing Siri FAST Powerset Yahoo Delicious Autonomy Inxight Hakia Google Make the software smarter

74. Web-Scale Semantic ExtractionAnd search 72 1.11.2008 | Product Positioning

75. T2 Semantic Index Videos Music People Reviews Games News Products Recipes Services How-To’s Classifieds Events Hotels Bars Resumes Coupons Reports Photos Help 73

76. Many Uses for this Index Search Interest tracking Recommendations Web application development 74 1.11.2008 | Product Positioning

77. 1. Do a Keyword Search 2. Filter by Type 3. Filter by Attribute Recipe Cuisine Web Page Classified Ad Difficulty Web Page Product Ingredient Prep Time News Web Page Author Web Page Hotel Type of Dish Web Page Song Dietary Option Website Game Web Page Prep Time Help Article Web Page Calories Web Page Etc… Person Etc… 75

78. Use Case: Cooking 76

79. Scenario: Family Dinner Deciding what to cook…

80. Scenario: Family Dinner

81. Scenario: Family Dinner

82. Current Scenario: Family Dinner [INSERT BING RESULTS + EXTERNAL LOGOS]

83. Current Scenario: Family Dinner [INSERT BING RESULTS + EXTERNAL LOGOS]

84. Current Scenario: Family Dinner

85. Current Scenario: Family Dinner

87. T2 – Tools for Developers API to T2 Index and services Widgets and components for 3rd party sites Web-based ontology community – like Sourceforge Browser plugin for easy site mapping to ontologies 85 1.11.2008 | Product Positioning

88. T2 Ontology Site Demo 86

95. T2 Site Mapping Tool Confidential

96. T2 Site Mapping Tool Confidential

97. T2 Site Mapping Tool Confidential

98. T2 Business Model T2 destination Advertising on the site T2 site search & ad network Provide sites with better site search Targeted ads Revshare T2 API Partners pay us, or revshare with us Monetize however they want to 96 1.11.2008 | Product Positioning

99. T2 Near-Term Vertical Focus Areas Lifestyle Entertainment Shopping Food (Complete) Health Travel People Gaming (In Dev) Sports Music TV Film Consumer Electronics Health & Beauty Classified Ads Media Products Help & Support

100. T2 Long-Term Goals Index the structured data on the Web Across all major vertical domains With help from an army of outside developers and partners Grow an ecosystem around the index 98 1.11.2008 | Product Positioning

101. Timeline T1 is in Maintenance Mode T2 is in Alpha T2 Goes Beta by Q1 99 1.11.2008 | Product Positioning

102. What Next?Find Follow Share 100 1.11.2008 | Product Positioning

103. For all types of content Web pages Data records Real-time content 101 1.11.2008 | Product Positioning

104. Find stuff (semantic search)Then follow it (interest tracking) Then share it (socialization) 102 1.11.2008 | Product Positioning

105. But this time… 103 1.11.2008 | Product Positioning

106. We’re starting with just “Find” 104 1.11.2008 | Product Positioning

107. Conclusions Web-Scale Semantic Search is the Next-Step for Search and for Twine But after 9 years of this, it’s clear It won’t happen overnight 105 1.11.2008 | Product Positioning

108. Stay Tuned… 106 1.11.2008 | Product Positioning

109. Contact Information Nova Spivack Twitter: @novaspivack nova@twine.com