Opening Keynote Address Salim Ismail January 29, 2009

Objectives for today Intelligent Content is… a definition Content on the web… an evolution evolution of data/infrastructure on the internet Social Media Examples of intelligent applications Where else is content intelligent? (off-web) Back to the Web – what’s next? Q&A

Intelligent Content is… a definition

Content on the web… an evolution

evolution of data/infrastructure on the internet

Social Media

Examples of intelligent applications

Where else is content intelligent? (off-web)

Back to the Web – what’s next?

Q&A

Who Am I? India/Canada/Europe/U.S (a decade each) Degree in theoretical physics Five years large scale database design Five years restructuring large European orgs Seven early stage companies Six years of internet startups Five of my own (PubSub, Confabb, Ångströ…) One year as VP Yahoo!, Head of Brickhouse Internal VC fund, analyzed 3000 ideas Sponsored four Yahoo Pipes (prototype), BravoNation, Y!Live, Fire Eagle Next gig to be announced in four days

India/Canada/Europe/U.S (a decade each)

Degree in theoretical physics

Five years large scale database design

Five years restructuring large European orgs

Seven early stage companies

Six years of internet startups

Five of my own (PubSub, Confabb, Ångströ…)

One year as VP Yahoo!, Head of Brickhouse

Internal VC fund, analyzed 3000 ideas

Sponsored four

Yahoo Pipes (prototype), BravoNation, Y!Live, Fire Eagle

What is ‘Intelligent Content ’ Content Data of some kind Wrapper Associated metadata The dream of the Semantic Web “ 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.” All data, fully self-described for whatever purpose is required (slightly utopian… rather difficult)

Content

Data of some kind

Wrapper

Associated metadata

The dream of the Semantic Web

“ 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.”

All data, fully self-described for whatever purpose is required (slightly utopian… rather difficult)

What is ‘ Intelligent Content’ Many types of intelligence: Gardner: logical , linguistic , spatial , musical , kinesthetic , naturalist , intrapersonal , interpersonal and social intelligence Sternberg: Practical / Contextual - deals with the mental activity involved in attaining fit to context ” Uses adaptation, shaping, and selection Experiental / Creative Experience breaks down into novel/automated Componential / Analytical Break down problems and intuit solutions

Many types of intelligence:

Gardner: logical , linguistic , spatial , musical , kinesthetic , naturalist , intrapersonal , interpersonal and social intelligence

Sternberg:

Practical / Contextual - deals with the mental activity involved in attaining fit to context ”

Uses adaptation, shaping, and selection

Experiental / Creative

Experience breaks down into novel/automated

Componential / Analytical

Break down problems and intuit solutions

For our purposes… Intelligence: The ability to take a pattern from one frame of reference an apply it to another Chess program Pagerank Cross data sets Conditional Intuitive (emotional) Sophisticated/complex Sophisticated (intuitive) PM Contextual/Conditional Pattern Matching Basic (Numerical) Pattern Matching

Intelligence:

The ability to take a pattern from one frame of reference an apply it to another

Chess program

Pagerank

Cross data sets

Conditional

Intuitive (emotional)

Sophisticated/complex

Two definitions of “Intelligent Content” 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 Structurally rich and semantically aware, and is therefore automatically discoverable, reusable, reconfigurable and adaptable - Ann Rockley

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

Structurally rich and semantically aware, and is therefore automatically discoverable, reusable, reconfigurable and adaptable - Ann Rockley

More on intelligence Pattern Recognition is a key aspect of intelligence, but you also have Pattern creation? Patterns interacting with other patterns create new patterns (in other words, mashups : ) Stephen Wolfram – “A New Kind of Science” Class 1 Automata

Pattern Recognition is a key aspect of intelligence, but you also have Pattern creation?

Patterns interacting with other patterns create new patterns (in other words, mashups : )

Stephen Wolfram – “A New Kind of Science”

Class 1 Automata

Digressing to ‘Repetition’ Class 1 Class 2 Class 3

Class 1

Class 2

Class 3

More on Repetition (recursive PM) Class 4 Reflections on Stephen Wolfram's "A New Kind of Science" http :// www. kurzweilai.net/meme/frame.html?main =/articles/art0464.html

Class 4

Reflections on Stephen Wolfram's "A New Kind of Science"

http :// www. kurzweilai.net/meme/frame.html?main =/articles/art0464.html

Intelligent Content – Summary Context is key Who, what, where, when… (why) Pattern management across frames of reference In documents, SGML > XML > DITA > ?? Eventually, pattern management (intelligence) will be embedded in the content (document) W- ar- goin- on ho-iday w-th som- f-iends n-x- we-k Se- -ou wh-n w- ge- ba-k 25% of letters missing, yet meaning is conveyed

Context is key

Who, what, where, when… (why)

Pattern management across frames of reference

In documents, SGML > XML > DITA > ??

Eventually, pattern management (intelligence) will be embedded in the content (document)

W- ar- goin- on ho-iday w-th som- f-iends n-x- we-k

Se- -ou wh-n w- ge- ba-k

25% of letters missing, yet meaning is conveyed

More pattern matching

Next topic… Intelligent Content is… a definition Content on the web… an evolution evolution of data/infrastructure on the internet Social Media Examples of intelligent applications Where else is content intelligent? (off-web) Back to the Web – what’s next? Q&A

Intelligent Content is… a definition

Content on the web… an evolution

evolution of data/infrastructure on the internet

Social Media

Examples of intelligent applications

Where else is content intelligent? (off-web)

Back to the Web – what’s next?

Q&A

Content on the Web What’s going on ?? What is the 50,000 foot view? (15,240 m ) How we got here – some history/context Information flows Technology Framework Internet 3.0 The Social Media wave Examples Image: Kevin Kelly

What’s going on ??

What is the 50,000 foot view? (15,240 m )

How we got here – some history/context

Information flows

Technology Framework

Internet 3.0

The Social Media wave

Examples

There’s lots going on today… ! Yahoo/Google/Microsoft/AOL/Facebook Blogs/feeds/RSS/ATOM//microblogging/lifestreaming Friendster/LinkedIn/Myspace/Bebo/Facebook Facebook Feed/FriendFeed/FriendFeedFilter/FeedaFriend Adsense/Panama/Beacon/adCenter Twitter/Twhirl/Tweetdeck/Twitterfone/Twitscan/TwitSnooze OpenID/IdentityCommons/IdentityGang/IdentityWoman Dataportability/Data Availability/OpenSocial… nottoosocialyet/FriendConnect/FacebookConnect/everybodybloodyconnect Icannotakeanymoreofthispleasestop

Yahoo/Google/Microsoft/AOL/Facebook

Blogs/feeds/RSS/ATOM//microblogging/lifestreaming

Friendster/LinkedIn/Myspace/Bebo/Facebook

Facebook Feed/FriendFeed/FriendFeedFilter/FeedaFriend

Adsense/Panama/Beacon/adCenter

Twitter/Twhirl/Tweetdeck/Twitterfone/Twitscan/TwitSnooze

OpenID/IdentityCommons/IdentityGang/IdentityWoman

Dataportability/Data Availability/OpenSocial… nottoosocialyet/FriendConnect/FacebookConnect/everybodybloodyconnect

Icannotakeanymoreofthispleasestop

And a few companies…

Some call it Web 2.0 According to Tim O’Reilly…. Fundamentally: user participation (UGC) + Syndication

According to Tim O’Reilly….

Led by Blogs Last few years - blogs exploded in use With the rise of the web in the 90s, we had millions of readers, but relatively few publishers (e.g. CNN, CNet) Now, due to the ease of publishing with blogs and other tools, we now also have millions of publishers 1m in 01/04, 10m in 01/05, 50m in 2006 and over 100m today Blogs now ‘overtaken’ Top Bloggers: stratifying into self-publishing journalists/pundits Flickr, MySpace, FaceBook, Bebo et al covering the rest User Generated Content splashing about everywhere Morphing into micro-blogging/lifestreaming

Last few years - blogs exploded in use

With the rise of the web in the 90s, we had millions of readers, but relatively few publishers (e.g. CNN, CNet)

Now, due to the ease of publishing with blogs and other tools, we now also have millions of publishers

1m in 01/04, 10m in 01/05, 50m in 2006 and over 100m today

Blogs now ‘overtaken’

Top Bloggers: stratifying into self-publishing journalists/pundits

Flickr, MySpace, FaceBook, Bebo et al covering the rest

User Generated Content splashing about everywhere

Morphing into micro-blogging/lifestreaming

Other Web 2.0 Descriptors Services (as opposed to data) UGC (User Generated Content).. e.g. blogs Manipulate and ‘use’ data, not just presentation Low latency (real time) Data aggregation Social Networking Examples Flickr, Buzznet, Dabble Wordpress, Typepad, Drupal Eventful, Upcoming, Edgeio YouTube, MySpace, FaceBook Web 2.0: Facilitate Consumer to Consumer

Services (as opposed to data)

UGC (User Generated Content).. e.g. blogs

Manipulate and ‘use’ data, not just presentation

Low latency (real time)

Data aggregation

Social Networking

Examples

Flickr, Buzznet, Dabble

Wordpress, Typepad, Drupal

Eventful, Upcoming, Edgeio

YouTube, MySpace, FaceBook

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

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

Four key drivers… Syndication XML Low Latency Great UX

Web 2.0 = Internet 3.0 Web 2.0 = Internet 3.0 Structured Data (XML) Syndication is starting to take hold Event-based (Publish/Subscribe) Participatory UX = consumer to consumer Latest wave in internet companies (Facebook, YouTube)

Web 2.0 = Internet 3.0

Structured Data (XML) Syndication is starting to take hold

Event-based (Publish/Subscribe)

Participatory UX = consumer to consumer

Latest wave in internet companies (Facebook, YouTube)

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

Social Media Arrives Web – started as documents with linking Documents with links became nodes XML added metadata Lots of arbitrary data (about you) can now be added to the web Location Identity Friends Preferences Assets Purchases

Web – started as documents with linking

Documents with links became nodes

XML added metadata

Lots of arbitrary data (about you) can now be added to the web

Location

Identity

Friends

Preferences

Assets

Purchases

Why is Social Media big? We are biological creatures Driven by social constructs “Who you know” drives a lot of what we do Context drives 80% of information value Who speaks gives a lot of context

We are biological creatures

Driven by social constructs

“Who you know” drives a lot of what we do

Context drives 80% of information value

Who speaks gives a lot of context

Social Contexts Who do I know (Social Networks) : Flickr, Upcoming, MySpace, Bebo, FaceBook What am I doing (status updaters) : Twitter, Identi.ca, Skype, FB, Plaxo Where am I (location brokers) Fire Eagle, Plazes, Loopt, Brightkite 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)

Who do I know (Social Networks) :

Flickr, Upcoming, MySpace, Bebo, FaceBook

What am I doing (status updaters) :

Twitter, Identi.ca, Skype, FB, Plaxo

Where am I (location brokers)

Fire Eagle, Plazes, Loopt,

Brightkite

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

A web of data – Tom Coates http://www.plasticbag.org/files/native/native_to_a_web_of_data.pdf

http://www.plasticbag.org/files/native/native_to_a_web_of_data.pdf

Web Architecture – Dion Hinchcliffe

Thoughts on Social Media SM has become the starting point for consumers But, computers are binary, relationships aren’t 80/20 rule SNs will hold who’s connected to whom, but not more Leverage with other types of information

SM has become the starting point for consumers

But, computers are binary, relationships aren’t

80/20 rule

SNs will hold who’s connected to whom, but not more

Leverage with other types of information

Evolution of a Platform New paradigm appears Some companies launch One gets traction and quickly dominates Walled Gardens take hold The competition fights back and force openness Walled Gardens collapse kicking and screaming Saturation New Paradigm appears (go to step 1) Social Media

New paradigm appears

Some companies launch

One gets traction and quickly dominates

Walled Gardens take hold

The competition fights back and force openness

Walled Gardens collapse kicking and screaming

Saturation

New Paradigm appears (go to step 1)

Problem Spaces in Social Media Overload filtering Underload discovery Disambiguation identity Duplication (republishing)

Overload

filtering

Underload

discovery

Disambiguation

identity

Duplication (republishing)

Example: Ångströ News published by people on your social networks has proven to be “intriguing and addictive” News published about professionals in your network is actionable and often business critical A board member raises a new fund A colleague gets promoted An investor is featured in the news Google Alerts is about the only tool…

News published by people on your social networks has proven to be “intriguing and addictive”

News published about professionals in your network is actionable and often business critical

A board member raises a new fund

A colleague gets promoted

An investor is featured in the news

Google Alerts is about the only tool…

A Social Graph (400

News About Your Network Enter LinkedIn credentials Analyze bios and profiles Crawl news sources Apply algorithms Rank stories by: Recency KudoRank NameSense Source Quality User Feedback Newspaper interface User comments & votes Discover and share business-critical news

Enter LinkedIn credentials

Analyze bios and profiles

Crawl news sources

Apply algorithms

Rank stories by:

Recency

KudoRank

NameSense

Source Quality

User Feedback

Newspaper interface

User comments & votes

The News Cycle Discovery is increasingly happening via SM Mary Meeker

Discovery is increasingly happening via SM

Example: Confabb

Live Traffic

Yelp Intersecting multiple data sets Users Review Comments Feedback Ratings

Intersecting multiple data sets

Users

Review

Comments

Feedback

Ratings

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

Next topic… Intelligent Content is… a definition Content on the web… an evolution evolution of data/infrastructure on the internet Social Media Examples of intelligent applications Where else is content intelligent? (off-web) Back to the Web – what’s next? Q&A

Intelligent Content is… a definition

Content on the web… an evolution

evolution of data/infrastructure on the internet

Social Media

Examples of intelligent applications

Where else is content intelligent? (off-web)

Back to the Web – what’s next?

Q&A

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

AI & Robotics Ubiquitous computing and more-powerful computers Huge amounts of data from the Internet and physical sensors Algorithms that learn and improve over time Software that's able to deal with uncertainty, incompleteness and surprises Software agents that can weigh costs and benefits Integration of separate fields such as speech, vision, robotics, sensors and machine learning Computerworld.com – 1/26/09 - http://bit.ly/ts5Q

Ubiquitous computing and more-powerful computers

Huge amounts of data from the Internet and physical sensors

Algorithms that learn and improve over time

Software that's able to deal with uncertainty, incompleteness and surprises

Software agents that can weigh costs and benefits

Integration of separate fields such as speech, vision, robotics, sensors and machine learning

Computerworld.com – 1/26/09 - http://bit.ly/ts5Q

Not far away… 3D printing of organs Artificial Retinas Christopher deCharms http://abcnews.go.com/Technology/story?id=1603783&page=1

3D printing of organs Artificial Retinas

Next topic… Intelligent Content is… a definition Content on the web… an evolution evolution of data/infrastructure on the internet Social Media Examples Where else is content intelligent? (off-web) Back to the Web – what’s next? Q&A

Intelligent Content is… a definition

Content on the web… an evolution

evolution of data/infrastructure on the internet

Social Media

Examples

Where else is content intelligent? (off-web)

Back to the Web – what’s next?

Q&A

Internet 3.0 – The Nervous System The internet is evolving into a complex organism Search is the memory Web 2.0 provides the basis for the nervous system The key question is: “ Whenever…”

The internet is evolving into a complex organism

Search is the memory

Web 2.0 provides the basis for the nervous system

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

CONTENT ON THE WEB Crowd-sourcing ideas Artist: Aaron Koblin

The next 5000 days on the web http://splicd.com/yDYCf4ONh5M/137/354 Today…

http://splicd.com/yDYCf4ONh5M/137/354

Today…

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

Thanks…. http://salimismail.com ww.twitter.com/salimismail