‘Point, Click & Learn’
Visual search and augmented reality experiences seemed poised to evolve as early adopter platforms for learning based on images, objects and places that exist in the physical world.

Google, Nokia, Ricoh, Intel, and Microsoft have all demonstrated or released beta and 1.0 version services that layer digital information over images and video captured by the camera holder or person looking at the screen.

The vision (pun intended) for visual and augmented reality platforms is to use cameras, screens and projection systems for uncovering and layering digital information about objects (including text)  and places.   So you can learn about a particular flower or building while standing in front of it, and not when you are at home sitting in front of your computer.  The hope is to move beyond photo/video capture and bring new functionality to the lens as a learning device.  No keyboard or mouse needed- just point, click and learn.

Camera + Web-based Software = Augmented Visual Learning
We can already see demonstrations of first generation personal learning experiences based on visual augmented reality (digital layers over real world images) and software services that tap the power of scalable  cloud computing architectures:

• A student learning biology is able to point, click & learn about a tree leaf, an insect or a bird whether the object exists in real life or as an image inside a book  (e.g. Bobcat tracking app; IdentityTree)
• A tourist uses their mobile camera to identify the name and history of a landmark building; or to help them learn about the local mass transit options (e.g. ‘Nearest Subway’ app; BART)
• A museum visitor sees an art piece and wants to learn more about the artist (e.g. museum app)
• An architecture student want to see a time-lapsed reply of a building’s construction, or an ‘x-ray’ layer image of the structural beams below the exterior skin
• An aspiring wine connoisseur wants to learn more about a vineyard or ideal food pairing by snapping an image of the bottle while inside the retail store (e.g.  Tesco Wine app YouTube video; demo)
• Someone reading a newspaper sees a compelling image – points, clicks and learns more about the topic (e.g. Ricoh iCandy app1; demo2)
• A star gazer visiting the Southern hemisphere looks up at an unfamiliar sky – points, clicks and learns via an augmented layer explaining the night sky (e.g. Google Sky demo)

This is quite an impressive list for 2010!  And yet these are only examples based on first generation software, hardware and a tiny catalog of images.  The most exciting learning applications of visual search are ahead of us!

Visual Search 2011-2020
It is important not to confuse today’s beta and 1.0 version visual search and augmented reality apps with those likely to image in the next decade.   Both platforms are likely to evolve alongside other applications based on 2D-3D modeling, location based services, robotic vision, tagging, visual mashups, personal assistants (e.g. Siri) and personal learning systems.

But in order to have a ‘real-time‘ experience in which we capture an image and have it immediately identified (from a catalog) and layered with relevant digital background information – we must think beyond the phone or camera itself and see the potential of software as service models.

Visual search catalogs and services will ‘live in the cloud‘ and not on our devices.  In other words, we will not have to rely on the memory or processing power inside of our phones.  The phone will access image catalogs stored on the internet (or ‘in the cloud’).

This software-as-service architecture of cloud computing (e.g. networked & virtualized) offers users tremendous storage and processing power.  It is a low cost, scalable platform for  individuals and companies to store, access and collectively learn about physical objects captured by camera lenses.  This will allow us to access billions of images, tags and related content by tapping this massive cloud catalog of object shapes and textures.

My wish list for advanced visual search and learning by 2020?
Making the invisible, visible
I am most interested in real-time augmented reality experiences that allow users to test alternative assumptions and scenarios with real-world systems.  I’d like to see visual interfaces that reveal layers about the molecular structure of our natural and synthetic worlds.  And if all goes well, it might be micro-projectors which layer images directly onto objects and surfaces that really change the game by the end of the decade.

Imagine an engineering student standing on a highway overpass to study traffic flow patterns and then changing the parameters of vehicle speed and driver behavior to test alternative results.  Or imagine a 5th grade student zooming in on any material to see the nanostructured reality that defines the material’s properties.

Alas, that is my vision of the next decade!  For now, I am comforted and enthusiastic about the Beta and Version 1.0 experiences already on the marketplace!

I’ve included videos from Google and Nokia below:

Nokia’s Point & Find application that uses a video camera to recognize real world objects (e.g. solar panel, buildings, products, et al)

Google has released Google Goggles as its own platform for camera based search

Here we see Goggles being used to translate a menu text (in German) into a captured image into English

Google Goggles Demo

Another Goggles 1.0 real world demo

Using Google Goggles to identify photos taken in Europe

Additional clips

Origional Point and Find demo from Nokia’s Beta Labs

Tesco wine visual search

Nearest Subway Search

Ricoh iCandy Apps

Additional Resources

• Microsoft Bing Visual Search (see this as a database of future)
• html 5 (<canvas>) demo at Google I/O event (Youtube)
• Augmented Reality companies (e.g. Metaio)
• [For those readers who are more technically oriented- I believe visual search (pictures and images) will be greatly enhanced through html 5 based applications (e.g. <canvas>), 3D simulation environment, and NoSQL based personal learning management systems.]

Image Source:
Creative Commons Attribution License

Professional Futurists who work with clients are familiar with the perception pitfalls associated with forecasts and scenarios that deal with the impact of technology.

This is why framing forecasts and scenarios around demographics (life stage), cultural (lifestyle) and market structure transitions are more digestible frameworks for getting clients to challenge their assumptions about transformational changes to their business models.

Why is technology a hard pill to swallow?  A combination of reasons: risks of early adoption, costs associated with implementation and support, lack of  pull demand from existing consumers, accepting small market share profits even with fast growth prospects (et al).   And let’s not forget that technology solutions are sold by deeply embedded vendors who have their own varying self-interests in transitioning old vs new platforms.

A less eloquently stated reason is that the theme of technology (especially ‘digital’ and ‘web’ technology) just scares most people.  Even if we all agree that technology on its own is never a solution, and that there is always a tendency of over-hype it in the short-term, many people struggle to overcome strong negative emotional/gut responses to new technology platforms.

For most audiences technology seems too gimmicky…  too young and hip… too transparent and invasive… or too time consuming.   These are legitimate barriers for getting audiences to see real world applications for customers.

Technology should always be placed in the context of culture, market and regulatory structures.  Without this broader context it will always be easier to roll our eyes than to probe, explore and seek to understand.

To get us to this place of understanding the broader social context of technology we need framers like Kevin Kelly to bring context to the story of technology – past, present and future.

Kevin Kelly:Technology & Foresight Foundations of Social Change & Systems Thinking
Kevin Kelly has spent decades preparing a script to tell  the epic story of technology’s past, present and future.  As a Former Editor of the Whole Earth Review and past Editor of Wired he holds a very unique perspective that spans our recent historical era where technology has become a widely perceived mechanism (and ‘agent’) of change.

I prefer to see Kelly as an informed observer as much as he is arguably a techno-optimist.  And I believe his passion for understanding technology is rooted in the two pillars of foresight/futures studies: social change and systems thinking.

Social Change frameworks (e.g. Progress, Power & Conflict, Evo-Devo, et al) help us understand change and develop the right models for forecasting possible outcomes.  Systems thinking forces us to understand structure and relationships that shape feedback loops (e.g. vicious vs. virtuous) often associated with non-linear change.  Kelly is quick to point out the non-linear aspects of change shaped by emerging technology platforms.

Here are a few of Kevin Kelly’s public lectures on technology.  Each is a variation of his central exploration in understanding the fundamental nature of technology and life in the universe:

TEDxAmsterdam, 2010

Kevin Kelly: Predicting the next 5,000 days of the web
2007 EG conference

Let’s go back further… before TED had exploded in the mainstream world– and we see many of the same messages (and one-liners) that continue to shape Kevin Kelly’s investigation into the human and universal relationship with technology.

Kevin Kelly: How does technology evolve? Like we did

And finally a recent interview on historical foundations of Wired:

Kelly’s current blog Technium

Image Source: Porfolium Flickr Creative Commons

The good news is that the perceived value of ‘games-based learning‘ and ‘social learning‘ is starting to gain mainstream traction as a way of reconciling and bridging the worlds of formal (institutional) and informal learning that stretches from learner experiences within schools and workplaces – to our activities at home and while we are within the physical world.

The bad news is that most conversations about ‘the future‘ simply extend present day notions of ‘games’ and ’social web’ experiences into the future – rather than explore new assumptions about how both might evolve in the years ahead.

In other words, the future of learning management systems is NOT World or Warcraft or Facebook!!  Learning inputs and outcomes will not be based on what we do on computers or game consoles (device orientation), it will be based on things we do inside a world where most things and places are networked and sensing (learner orientation).

Focusing on Grades vs The Journey’s Experience
In the following talk Jesse Schell explores the future of game based learning in a future world shaped by objects (products) and environments with embedded sensors, ubiquitous access to scalable cloud-based web services, and unified interfaces via voice/video/virtual agent-based experiences.

Schell explores how these emerging platforms mgiht build upon current day trends around games that integrate reality (not allow us to escape from it!) – fantasy football, hiking/geo-caching for treasures, and Weight Watcher ‘point systems’.   He imagines at the center of these games that engage us in the layers of our reality, will be a learner who can see all relevant data, understand system structure, and become more self reflective and accountable based on their actions!

He argues (or at least, my interpretation!!)  that we need to design games as life long learning systems centered on feedback loops of privately managed data sets that connect what we do with our outcomes (e.g. overweight because what I ate; ill-informed about a world issue because of what I have/haven’t read; I have bad teeth because I don’t brush long enough).   This notion builds upon the often cited work related to  ’Quant Self‘ or Quantified Self. [See resources below]

Schell’s vision (that I share!!) is that games and experience design supports the emergence of a culture of learning and a desire to genuinely improve ourselves!

How do we get there?  The learning system design shows you the path and tracks your progress – pointing out where you did well and where you need to improve your outcomes by changing your behavior!

One of my favorite paraphrased lines from Schell’s talk… ‘instead of giving out grades we should hand out experience points‘!

Absolutely!! Replacing snapshot static grades with pathway and apprenticeship style experience points?  Brilliant!

If we expect to teach people how to become life long learners, we must not give out snapshot grades and graduate them based on age, rather use apprenticeship style progress reports that show there is still much more to learn ahead!!!!

Moving forward?
First, we need to recognize the infancy stage of learning management systems and personal learning platforms that bridge informal and formal learning via games or social learner paradigms!  We are not there yet!  In fact, I’m not sure we even have an inspiring vision?!!

Second, we need to proactively address all the fear oriented assumptions related to the management of transparent lives in this ‘quantified self’ future scenario.

Leaders in the learning space might apply foresight and engage all stakeholders in discussions about emerging assumptions regarding identity management, transparency, and the value of personal data and feedback loops that connect our behavior with outcomes.  Otherwise, fear and confusion will shut down otherwise open minds.

Stepping off my soapbox… watch Schell’s video!!

(video via Kevin Fox’s blog, thanks!)

Other people to follow in this ‘quant’ self space:

• Kevin Kelley’s Quant Self Resource List is a great place to start;
• Alvis Brigis (Blog; Twitter)
• I have written on a similar evolution of learning systems based on the principles of situational awareness based learning via perception, comprehensive and projection – and the role media might play in learning!

Cisco CEO John Chambers is selling a very powerful vision of future growth based on innovation timed to major market transitions occurring in business, government, education and infrastructure.  His current ‘network-based collaboration’ stump speech offers lessons on building an organizational culture based on foresight and innovation:

• Innovate across Market Transitions - The secret to company longevity is the appropriate application of strategic foresight that allows companies to innovate ‘across market transitions’ instead of fighting for market share during economic downturns or mature phases of industry growth.
• The Network is the Platform – The web is evolving as a platform for unified communication systems and business services.  Business model innovation and operational execution are the foundations for tapping the power of network-based delivery of high value services.
• Social Enterprise – The way to unleash productivity is to replace rigid org chart based communication channels with social enterprise structures that allow any individual to identify internal expertise, and directly share knowledge and experience across the organization.
• Video-based Collaboration – Forget about ‘virtual teams’ based on email exchanges!!!   The game-changer in web collaboration is visually connected workers, partners and customers. Video (real-time and recorded) is likely to emerge as the preferred mode of collaboration in the years ahead.

Here are five videos featuring John Chambers exploring the dynamics of the ‘next generation’ organization:
(My favorites include the MIT talk and India Holographic presentation):

2008 Keynote at World Business Forum

MIT Video: Building the Next Generation Company

Recorded: October 15, 2008   Running Time: 1:07:45

A sneak peak at future holographic versions of telepresence [India 2008]

Video
Harvard Business Review Interview [Recorded February 06, 2009]

Cisco Collaboration Products Demo – 2009

The 2010 World Economic Forum (”Davos”) has released a set of 5 minute video presentations from its IdeasLab program. Presentations are limited to 5 minutes (20 slides) so there is no ‘death by powerpoint‘, just good old fashioned ideas sharing from some of the world’s brightest minds.

Here are five presentations from a group of MIT Professors and Researchers on the nature of intelligence via social brain, reverse engineering the brain, collective wisdom, and web scale change:

MIT’s Rebecca Saxe: Social Brain

MIT’s Josh Tenenbaum: Reverse Engineering Brain

MIT’s  Sebastian Seung

“… your conectome is the totality of your brains connections”

Tim Berners-Lee – Intelligence at Web scale

MIT – Thomas Malone
How can computers and human groups be connected to be intelligent and wise?

Creating a Culture of Little Brother Surveillance or Systems Thinking?

Forecast & Outlook:  The principles of ‘situational awareness’ based on perception, comprehensive and projection might soon support a wide range of applications that reach far beyond military operations and crisis response.   It is a user and outcomes-centric systems approach that could integrate anticipated advances in mobility, ‘smart’ infrastructure, learning systems, policy-making and business intelligence.

Situational Awareness systems might have what it takes to create demand for integrating a wide range of emerging disruptive technologies that include: low cost sensors, IT architecture (network/virtualization), video, robotic vision, gaming, 3D/geospatial modeling, physical and virtual augmentation, autonomous systems, simulation software, location based service, social web lifestreams (by activity/sentiment), and expert software learning systems.  Yes, this is a grab bag of buzzwords (forgive me!) but Situational Awareness (’dashboard’) platforms will require significant integration to make it useful for users in a networked world.

Managing Expectations & Changing Assumptions:
From Pilots to Drivers to Politicians to Businesses to Learners
Situational awareness will certainly raise red flags of ‘Big & Little Brother‘ by professional and part time conspiracy theorists, but as it becomes more understood and applied by individuals, I believe it will cultivate our capacity for increased awareness, mindfulness, and focus in an age of information distraction.  It will force learners to expand their collection of inputs, selectively identify their filters used in synthesizing and sense-making.  And help to mainstream systems thinking and the imperative of understanding structure, relationships and feedback loops in a globally interdependent world.

Yes, this is my wishful thinking!!  But we are in fact seeing a mainstream cultural transition between the ‘anonymous web‘ (Nobody knows I’m a dog!) and a more ‘social web‘ (’Most people know I’m a dog)!   Why shouldn’t web users continue to evolve alongside the web as it enters its next phase of being embedded inside the physical world?

To become as mainstream as today’s ‘social web‘ behavior and expectations, situational awareness (SA) systems will have to stretch beyond historical and current day applications that lead to potential confusion that it might be just a code word for advanced ’surveillance’.  And I am certain that more accessible concepts like ‘dashboards’ will emerge to properly frame and engage mainstream world!

Situational awareness is most commonly divided into three stages of awareness and behavior that allow us to see wider, deeper and further:

• Level 1 – perception of elements, relationships and structure in a given environment
• Level 2 – comprehension of the real-time situation
• Level 3 – projection and anticipation of possible outcomes into the future

The historical SA paradigm of perception, comprehension and projection is most familiar to military pilots (”lose sight, lose fight“) engaged in training and combat based situations.  In the recent years military leaders have extended SA approaches from pilot training to field troops navigating a combat theater of small networks distributed across remote rural regions and embedded inside challenging urban environments.   SA principles have also been embraced by crisis response teams seeking to create an information architecture for relaying real-time information across a temporarily disabled system.

Situational Awareness is the ultimate user-focused experience layer for infrastructure assessment and utilization.  Now what happens when we expand our definition of infrastructure to engage users and where  might SA principles be applied?  How might we imagine the positive decentralized benefits of situational awareness in non-military applications?

Six Areas to Explore:

1. Driving/’Connected Cars’
2. Political Transparency / ‘Civicware’
3. Geospatial / Real-time for Policy-making and Public Safety
4. Infrastructure Management
5. Learning Systems
6. Business Intelligence

#1 ‘Connected Cars’, Smarter Drivers
The most likely near-term application of situation awareness systems will experienced inside our cars! Instead of engaging military pilots, we will engage civilian drivers to increase the safety and flow of our roadways!

Situational awareness software is likely to play a major role in the changing driver experience.  Automakers are already beginning to integrate ‘sensing’ systems inside and outside vehicles based on sensors, radar, and video recognition that relay information to drivers and to other cars.  In this future our cars are collecting data and relaying information that will help drivers make better decisions on congested roadways.    This era of ‘connected cars’ is likely to make roads safer for drivers and pedestrians, and increase the flow of traffic on our highways. [Telematics examples: Ford Sync; GM OnStar; Kia UVO]

#2 Political Transparency / Civicware
Political transparency is a major driver of change in emerging economies and fledgling democracies.  Civicware systems based on situational awareness allow us to gather real-time, onsite information based on a distributed network that is resilient to attack or centralized control.  In this light, we can view the situational awareness role that Twitter played in Iran during political protests in 2009 as adding an SA layer of new inputs and on the scene conditions that could never had existed prior to the age of mobile social networks.

Another widely cited example of SA systems in political transparency is Ushahidi – an effort to build a mobile phone based infrastructure for ‘crowd-sourcing’ information that could prevent post election violence based on misinformation (e.g. groups rioting when in reality they are not!)   The Ushahidi Engine allows anyone with a cell phone to gather and distribute real time situation information via SMS, email or web or view aggregated data on a map or timeline.

#3 Policy Making / Public Safety
Geospatial visualizations are an emerging platform for communicating information based on place.  We can imagine a future in which social support services are based on a greater understanding of data sensed, synthesized, visualized and anticipated in communities afflicted by a wide range of events or socio-economic conditions.

In 2004 Christian Nold released an innovative map-based platform for gathering real-time information on emotional states.  His ‘biomapping’ projects can reveal where people are happy, hungry, angry, fearful or sad.    Imagine the public policy implications for supporting decision-making, policy analysis, and responses based on this bottom up data collection that can be conveyed on maps!

And let’s not forget about policies that support public safety and enforcement against violent crimes!

In recent years police agencies around the world have implemented gun location directional systems to help them gain real-time situational awareness in an area with detected gunfire.  These stories are widely reported in the media, but what happens when there are ubiquitious sensors and mobile phone ‘apps’ that can create an open distributed infrastructure for safety.  What happens when community members build their own layers of situational awareness?

What are the implications of lowering the cost of community safety oriented situational awareness systems?

#4 Smart Infrastructure Management
Situational Awareness is at the heart of emerging ‘smart’ infrastructure models that attempt to reveal real-time data and conditions within major infrastructure components for energy, transportation and water.  This allows infrastructure operators and users to make better decisions in managing resources and anticipating potentially disruptive events.  (e.g. electrical grid failures, peak demand, rush hour) [See PNNL Laboratory Situational Awarness for ’smart grid’)

#5 Lifelong Formal and Informal Learning
Situational Awareness systems go beyond mere ‘sensing and anticipating’—and can be applied as a tool for learning how to improve our performance in responding to complex systems.  SA systems that are user and outcomes centric might find a home in formal and informal learning applications!

Pilots will often train in mock environments to improve their ability to sense.  Field troops will train in mock situations that teach them how to protect themselves in hostile environments.

But how might we apply staged-learning and/or scenario based learning to improve learners’ ability to reveal their mental models that guide their responses.  How might SA layers expand our desire for more sensing inputs based on real-time information and a stronger understanding of structure, relationships and feedback loops within the environment?

#6 Business Intelligence and Capital Markets
What about the world of business?  Both small and large companies are operating inside increasingly complex market environments that are fragmented and shaped by events and rapidly changing conditions (many of which are not currently measurable).

We can already see growth in enterprise solution markets for situational awareness  systems such as ‘complex event processing’ and business intelligence ‘dashboards’ and decision support systems.  Real-time market situational awareness might indeed offer the biggest return on investment for SA systems.

What is Beyond?
Situational Awareness principles will likely have to be re-framed and re-packaged before mainstream audiences are likely to embrace and adapt systems designed to increase our ability to perceive, comprehend and anticipate.

We are probably a 5-10 years away from mainstream market users understanding and demanding early stage SA capabilities in their everyday world.   And 15-20 years away from more advanced systems and wider spread institutional adoption.

And I suspect transportation will be the first market followed by enterprise business intelligence applications.

So I suspect ’situational awareness’ might be the next big thing for Tweeting web geeks and industry pundits… in 2018?!!

I suspect life in a world of ‘smart, connected’ devices will push SA to the forefront as a way of managing life in this ultra-connected landscape.

In the meantime, I will be looking for the positive applications of SA systems and the potential of a learning culture of systems thinking based on awareness, focus and foresight.

Image Credit: Eyes at Williams College by dbking (Thank you!)
Flickr Creative Commons License Attribution 2.0 Generic

Situational Awareness Resources to Explore: Notable Projects:

• Global Incident Map https://www.globalincidentmap.com/
• BioWatch – http://en.wikipedia.org/wiki/BioWatch
• UK SA Driving Program –  http://www.2pass.co.uk/awareness.htm
• Global Seismic Monitoring - http://www.iris.edu/seismon/bigmap/index.phtml
• Cisco-NASA Planetary Skin
• HP Central Nervous System for the Earth (CeNSE) (Thanks @wendyinfutures)
• IBM Smart Planet

Papers / Academic

• Knowledge Structures for Situational Awareness (Learner) http://www.dodccrp.org/events/2006_CCRTS/html/papers/220.pdf
• Situation(al) Awareness (SA) in Effective Command and Control  by Derek J. Smith http://www.smithsrisca.demon.co.uk/ http://www.smithsrisca.demon.co.uk/situational-awareness.html
• An Approach to Collaborative Sensemaking Process http://www.dodccrp.org/events/11th_ICCRTS/html/papers/101.pdf
• Inferring High-Level Behavior from Low-Level Sensors http://www.cs.rochester.edu/~kautz/papers/High-Level-140.pdf
• The Knowledge Structure of the Commander in Asymmetric Battlefield: The Six Sights and Sensemaking Process http://www.dodccrp.org/events/2006_CCRTS/html/papers/220.pdf
• USE OF TESTABLE RESPONSES FOR PERFORMANCE-BASED MEASUREMENT OF SITUATION AWARENESS http://web.mit.edu/aeroastro/www/labs/ASL/SA/sa.html

Companies

• SA Technologies – http://www.satechnologies.com/
• EchoStorm – http://www.echostorm.net/index.html
• Logos Technologies – http://www.logostech.net/index.htm
• Swarm Micro Aerial Vehicles  – http://www.swarmsys.com/index.html
• Raytheon Intelligence and Information Systems – http://www.raytheon.com/businesses/riis/

I’m looking for non-military situation awareness companies?!!! Any thoughts?

Forecast: Our enterprise tools for searching, synthesizing, manipulating and transforming data into knowledge and skills will soon move beyond short keyword text searches into an era of more interactive, personalized and software-guided experiences.  The next wave of enterprise search, collaboration and learning tools will be built around: voice (natural language/conversation), video, location, social relationships, real-time activities and sentiments, agent-based applications, decision-making support, workflow support, and meaning applied to unstructured data.

A Disruptive Innovation Opportunity: ‘Searching/Sharing to Learning’
The web and web user experience seems ripe for disruptive innovation.  We have reached a point of diminishing returns of our search paradigm as we drown in too much information, and not enough context.  The tools for more effective searching, knowledge discovery and creation are absent from most consumer and enterprise web experiences.

Today, our expectations for building our search skills are shockingly low as most people just type in a keyword and click the first search result without any critical thought. Today’s web is an easy target for critics who believe easy searching has created a disincentive for building more challenging critical thinking skills. (I agree, but am optimistic that new tools and expectations are on the horizon!)

The mainstreaming of the social web has obvious upsides for ease of sharing ideas, but what about tools and platforms for more robust learning and evolution of our skill sets?

The disruptive opportunity of taking us from an Era of Searching to Learning is enormous, and it is exciting to see real movement among incumbents, startups and research institutions in evolving our tools and expectations for learning in a world where information is abundant, but the skills to build knowledge are lacking.

Terms like ’semantic web’, ‘natural language processing’, and ‘mash up’ have become stale to geek web culture, but they are just now finding an audience in mainstream enterprise and consumer markets.  The following lists includes [Updated: January 12, 2010] companies and projects to monitor as we prepare for the disruption of web learning…

Learn more below with a list of Incumbents, Startups and Projects to Watch…

Start ups Companies to Watch
[Updated: January 12, 2010]

• Altus – enterprise video search and learning platform
• Alitora – search, navigation and collaboration solutions
• Brainware
• Clarabridge – text mining
• Cognition – semantic solutions
• Collibra – enterprise data and business integration solutions
• Coveo – enterprise search and knowledge
• Exalead – enterprise search-based application (SBA) developer
• eVri – search and context engine
• Feedmil – ‘long tail’ search engine
• hunch -
• iGlue – web search and context platform
• Linguistic Agents – agent based interface platforms
• OpenAmplify – search and knowledge
• Pingar
• Rippol – a personalized, social video discovery engine
• SnapLogic – ‘ a new kind of data integration company’
• Synaptica – standardizing business vocabulary and language
• Temis – text mining and knowledge discovery
• TenForce- project ‘knowledge from data’
• Triviox – personalized job search
• Viewdle – video search
• VizSearch – supply chain and manufacturing exchange platform *
• Location based search – Google Near Me Now, Aloqua,
• Financial / Markets data – SkyGrid,
• Real-time search – OneRiot,  - more coming
• Video search – Viewdle, VideoSurf

Enterprise Solution Incumbents to Watch:
[Updated: January 12, 2010]\

• Microsoft Live Labs is pushing Pivot a new way to interact with data
  [Also see 'EntityCube' project; Bing Map Integration] – more to come…
• Google has released its beta version of Fusion (Fusion Tables); Living Stories; … more to come
• Oracle -project list coming soon
• IBM - Blue Pages, Bee Hive, project list coming soon
• Cisco – Cisco Pulse (Thanks, Anurag) – full project list coming soon

Projects to Watch:

• AnalogySpace (MIT)
• Paraview – is an open source
• Common Sense – open sourced project gathering common sense knowledge
• Common Sense Computing Group (MIT)
• Divisi (MIT) – a library for reasoning and semantic web applications
• *InfoChimps – open source knowledge and data marketplace platform *
• FedThread – search and interact with data from Federal Registry
• MESH – future of news and learning project
• Quora – collecting questions and answers
• Software Agents Group (MIT)
• YAGO - Max Planc Institute semantic web knowledge base project
• 2Wit (MIT) -
• List of ‘deep web’ search tools

*I’m refining my semantic web list to the most current and active projects**

Just to have on your radar

• DataDesigner – build a data platform
• GiniPic – simultaneous visual search
• GizaPage – learn more about your social graph
• Rank Em – crowdsourcing music discovery engine
• PearlTrees – visualization knowledge organization platform
• Mikojo – ‘the intelligent search engine’
• Oamos – meta search engine
• Public Database – gov 2.0 project
• Principle Global Indicators – global data
• Similar Page – discovery with searching
• SensesBot
• Spezify – search platform

Leave comments with any notable companies, projects that I miss… and I will update with credits!!

[Follow lists via  my del.icio.us tags on search]

Forecast & Outlook: Learning Systems certainly have what it takes to become a ‘next big thing’ in the world of business.  (Sarcasm intended!)  Yes, we are still years away from personal learning systems becoming functional and widespread.  But, there are signs that conversations about a learning culture are shifting from  classroom to boardroom.  Company leaders are starting to realize that their workers are more productive when they see themselves as lifelong learners (not just people who have jobs).  The lifespan of relevant skill sets and mindsets are likely to become shorter as the global economy shifts gears.  And this includes factory, service and knowledge workers.  My forecast?  Companies, Regional and National economies will soon make significant investments in emerging Learning Systems as ‘learning’ becomes the perceived driver of global economic growth and quality of life for the next century.

Creating Institutions a Marketplace for Lifelong Learning?
What if the most forward looking conversations around the Future of Learning had less to do with present day notions of school reform, teachers, test scores, graduation rates, or the merits of online learning– and instead focused on rethinking the value and role of non-institutional learning, and empowering the ‘learner’ for a lifetime of continual learning.

What if we avoided prescribing incremental strategies and saved ourselves from the painful (and often futile) political battles of fighting incumbents and the status quo?  Instead we might start to explore more transformational concepts of cultures and marketplaces of learning that move beyond the notion of traditional institutional and life-stage based education.

A Culture & Marketplace for Learning
Changes over the next decade might give birth to a very different conversation about education and learning  based on more relevant concepts and expectations suited to the 21st century (e.g. software facilitated learning systems, Personal Learning Environments (PLEs), workplace learning, social learning, micro-courses, et al).  Life in the future might not be transformed by efforts to ‘de-institutionalize‘ education, but instead positively disrupted by the creation of a more expansive marketplace that serves 7 billion learners.  To get there, we might explore the differences of three sets of assumptions and sources of tension ahead:

1) Blending Institutional and Informal Learning
The first assumption to challenge is this belief that real learning is something that only occurs inside a classroom or the institution of ’school’ or ‘workplace’.  This is the ‘teacher’ oriented world of education- and it needs more innovative institutions.   The alternative assumption to embrace is that learning is something that happens in the world, not inside a classroom or formal workplace.  This is the ‘learner’ oriented world – and it needs a marketplace!

Yes, we must work to improve our institutions (e.g. schools) but the biggest opportunities are developing learning experiences that permeate life outside of the classroom.

2) Shifting Expectations from Life stage to Lifelong Learning
The second assumption to challenge is this unspoken expectation that we are somehow ‘done’ with learning after we graduate high school or college (or when we get hired).    Continual learning remains an elusive idea for most people and organizations.   The alternative assumption is that learning is something that continues throughout our entire lifetime and is not bound by a ’semester’ or a ‘grade level’-  or a job title.  Instead of framing education around stage-based institutions (elementary to higher education) and degrees, how do we rethink the personalization of skills-building over a lifetime?

3) Start with the Vision of a ‘Post PC’ Web of Learning
Forget about ‘learning on a computer’.  Let go of this image of sitting in front of a computer screen reading text as the future of digital learning!  Banish these images from your head as we explore the future of learning culture.

The web has delivered on its promise of creating ‘access to information’, but we are still building systems that enable genuine learning in any environment!  We must imagine a future in which we can access and learn from the web while we are walking in a forest, or buying a bottle of wine in a store.  Mobile devices are the first step, but not the last.  New interfaces and web experiences are being developed that integrate new forms of interactions based on voice and natural language conversations… video based augmented reality and ’smart’ object experiences.

The web is being brought into the physical world…

Learning as the Economic Driver of the 21st Century
I suspect that the next decade might give birth to new cultural expectations, business models and marketplace supported learning platforms that make a cleaner break from the 20th century worldviews of ‘education’.  But before we get there, we will need leaders capable of clearly communicating a new  vision that has less  to do with test scores or ’school’ reform, and more to do with engaging people around an aspiration for continual learning and curiosity based living.

Until we have that vision communicated by national and international leaders, the best visions of continual learning and curiosity based living are promo commercials from NatGeo and Discovery Channel.  But I’m a sucker for viral videos- and they certainly capture the spirit of a culture of learning.

National Geographic: If. Live Curious video

Discovery Channel’s I Love the World song:

Original Version

My delicious tags:

http://delicious.com/garrygolden/learning

Shifting their strategy from trying to attract ‘reader’ eyeballs in  world dominated by celebrity news, to engaging ‘learners’ around the life of news stories might be just what the world of mainstream media needs to thrive in the age of web-based media.  Could the holy grail of news in the age of web media be informal learning?

Google’s new Living Stories platform is a collection of many simple web services that aims to deliver a richer, more personalized media experience on the web.  The beta-version service pulls feeds from the NYTimes and Washington Post to deliver a full spectrum of web media elements including story timelines, graphics, key people, videos, et al.   The story feeds are then personalized based on the behavior of the reader.  The vision? Readers never see the same headline twice - and follow stories based on the most relevant story lines and media  formats.   The service is classic Google ‘beta’ strategy.  It was probably realized too early for general audiences to like  it, but enticing enough to stretch our thinking of what is possible in an era of personalized learning media.

What is the innovation waiting beyond this ‘beta’ version?  Social web feeds and learning stream management.  The audience target of professional journalism might be the ‘learner’, and stop trying to compete for eyeballs of the lowest common denominator of  celebrity news that can dominate traffic. It is still early days for the future of web-based media, but I’m cautiously optimistic that personalized learning media apps could help raise the bar and lead to brighter days for professional journalism.  Google’s Living Stories might be the right skeleton of a new form of media based on learning systems.

Google Living Stories