Sometimes it's difficult to catch every story that hits tech media in a day, so we thought it might be helpful to wrap up some of the most talked about stories. Assuming this goes over well, we're going to give you a daily recap of what you missed in the ReadWriteWeb Community, including a link to some of the most popular discussions in our offsite communities on Twitter, Facebook, LinkedIn and Google Plus as well. This is a new feature at ReadWriteWeb so we covet your feedback. If you have suggestions, please leave them in the comments below or reach out to me directly at robyn at readwriteweb.com.

Official Google+ plugins released today add a +1 to your browser and a red notification alert. The same functionality was released for IE users in the Google toolbar. No love for Firefox though.

From the comments:

Here are a few more must read posts, chosen by your fellow community members.

• Google Chrome Will Sync Multiple Browser Profiles

• Learn AI in Largest Google+ Hangout Tomorrow

• When Developers Can Build Once For All Devices, Users Win

• Smartphone Sweet Spot: Adults 25 - 44 Have Highest Adoption

• Embedded Audio Gets the HTML5 Treatment Thanks to SoundCloud

• Despite The Hype, Few Enterprise Workers Embrace Social Software

• UCSD Study: Not Enough Bandwidth for an 'Internet of Things'

• Manage Your Online Social Life All In One Place With MyLife

• It's Apple's Sandbox, Developers Just Play In It

ReadWriteWeb Worldwide Meetup

Make plans to be at the ReadWriteWeb Worldwide Meetup on November 15. Reach out to our community manager, Robyn Tippins, at robyn at readwriteweb.com if you have any questions.

Since they have tens of thousands of followers, it "would be hard to fit everyone into their actual offices," says the intro video. It is an intriguing use of the Hangout feature. You don't have to be a Stanford student, or even enrolled in the class, or even know something about AI. All you have to do is add Norvig to your Google+ circle, ask your question on their YouTube channel now and tune in tomorrow.

Stanford has been offering many online classes, like other universities around the world. The class is more fully described here in this post on IEEE Spectrum.

A few weeks ago, I predicted that Jennings would win, Watson would place a close second and Rutter would place third in the overall contest, and I'm sticking with that prediction in spite of Watson's first-place finish in the practice round last week. When I put on my handicapper's hat, the scores of the practice round - $4,400 for Watson, $3,400 for Jennings and $1,200 for Rutter - are consistent with my assessment that Jennings and Watson are evenly matched and that Rutter is unlikely to win.

In 1950, computing pioneer Alan Turing, while pondering the question, "Can A Machine Think?", devised what has become known as the Turing Test. The original paper, "Computing Machinery and Intelligence," can be found here. While there's much philosophical debate about the exact nature of the Turing Test, in my mind, it is simply this: Can a human, communicating with a both machine and a human purely electronically, achieve in the long run a score better than average in distinguishing machine intelligence from human intelligence? If not, then we say that "the machine has passed the Turing Test."

In the years since Turing's paper, numerous challenges, both theoretical and practical, have been set forth for machine intelligence and numerous technological responses have resulted. Machine intelligence engineers have created practical economic value and machines now perform tasks once thought to require human intelligence. The essence of the question, "Can A Machine Think?" and Turing's proposed test is this: once you abstract away the physical implementation details of electronic circuitry and software vs. a human body, nervous system and human thought processes, can a machine perform as well or better than a human at solving symbolic problems?

We saw human-competitive performance from machines in checkers in the 1960s and an unbeatable checkers program in 2007. We've seen musicians unfamiliar with Chopin's entire body of work unable to distinguish between a mazurka by Chopin and a mazurka written in Chopin's style by David Cope's EMI software. In 1997, we saw a computer defeat the human world champion at chess. We have seen machines compete successfully with humans in patentable innovation. And last year, we saw machines successfully navigate public roads operating motor vehicles in traffic.

In short, every challenge we have thrown at the machine intelligence community to produce human-competitive intelligence has been met. A series of increasingly difficult symbolic problems has been solved by electronic circuitry and software. And on February 16, 2011, I claim we will be finally able to say the Turing Test has been passed - that if the three contestants were placed behind a screen and we could see only their responses in text form and their scores, we would not be able to tell which one was Watson.

And what of the future? There's no shortage of challenges for the supercomputers we can design and build and the software we can write for them. As IBM VP John E. Kelly III put it, "We really believe -- I don't want to be overly dramatic -- but we could save lives with this." Early diagnosis of diseases and design of effective treatments early in the cycle is one of the more obvious ones. Earthquake prediction is another one. As we approach the centenary of Turing's birth, I say it is high time we accepted that the answer to Turing's question, "Can A Machine Think?" is, "Yes, of course!"

We are today with virtual personal assistants (VPAs) where Facebook was in 2004 - simultaneously on the verge of something very big, and yet only at the very beginning of a decades-long trajectory.

In 1975, almost 35 years ago, at the National Computer Conference, Danny Hillis made a prediction that soon there would be more microprocessors than people, drawing laughter from the audience. As Danny has recounted, audience members remarked to him afterwards: "Danny, what could you possibly do with them all?"

Virtual personal assistants can be seen through the same lens. It's difficult to think today that I could and would entrust intelligent software agents enough to allow them to transact on my behalf in a variety of contexts and functions. But the vision is clear - as Siri's CEO Dag Kittlaus said from the outset of that SRI venture:

"We believe that in the next five years almost everyone who lives a connected lifestyle will delegate the details of their everyday tasks to intelligent assistants to coordinate, execute and simplify the details of their life. I believe we will look back on these days and ask ourselves how we ever got by without our trusted assistant in the same way my kids ask in amazement about how I ever got by without laptops and the Internet."

Today, artificial intelligence (AI) is still largely something we see in Hollywood movies more than we experience in daily life. But in the same way that "social" has matured and changed the world forever, so too will intelligence - it will become a constituent part of much of what we do and how we do it. We will expect, even demand, intelligence wherever we go, at the very point of the interface itself. Siri is the tip of the iceberg.

And we likely won't have just one assistant - we'll have two or three or maybe even 10, a scalable, distributed cadre, an army, even - of VPAs at our service. We will quite literally command the Web to rise up and proactively meet our needs, much like a concierge would - hospitable, knowledgeable, and very capable.

But to hearken back to Hillis so many years ago, what can we possibly do with them all?

The First VPA Distributed at Scale

Recently acquired by Apple, Siri's success validates the idea of a "do engine" rather than a search engine - an AI cortex that manages a complex services ecosystem on the iPhone, a platform that has already exploded the idea of what it is to have a smart phone.

As assistants grow in popularity, they will become our primary UI for the web - as John Battelle has said, "The future of search is a conversation with someone you trust."

Siri already uses some of the sites and services you know and love, things like OpenTable, Yelp and Rotten Tomatoes. But you may not be aware of TaxiMagic, TrueKnowledge or FlightStats.com where Siri introduces you to entirely new capabilities in the course of getting things done.

Assistants will leverage the best of the Web, not just to help you with the tasks you already have on your plate, but also to fundamentally extend your ability to get things done. They are digital prostheses that know what the Web can do for you (and who is good at doing what) and bring distributed intelligence to bear at the local level.

The vision of the assistant - indeed, many assistants - is possible today, an intricate orchestration of an array of sites and services on the fly, resulting in ultimate companionship for mobile lifestyles.

Hype and Reality

To the more jaded among you, this may sound nice, but unrealistic - perhaps even so far, unimportant. And you may be right. The AI dream has been long on promise and short on delivery.

Apple knows this better than anyone. Its Knowledge Navigator, a concept envisioned as early as 1987, was a gesture-based interface resembling the multitouch interface later used on the iPhone, and an equally powerful natural language understanding system, allowing the user to converse with the system via an animated butler.

Bill Gates himself saw the same value, remarking to a group of MIT students seven years later, in 2004: "If you invent a breakthrough in artificial intelligence, so machines can learn, that is worth 10 Microsofts."

It is even rumored that Gates' original vision for Longhorn/Vista focused on a concierge UI metaphor that adapted to user behavior over time.

AI as a marketing concept has a long and messy history - from Microsoft's Clippy (and less famously, Ms. Dewey), straight through to IBM's recent Watson project, and even AI wannabe's like PageOnce, which is actually a great app but a "personal assistant" in name only.

This is all the result of a technology vision whose value proposition is so very clear (indeed, decades old) but has nonetheless seen little in terms of implementation.

So will we see other Siris? And how realistic is it to think of assistant-ness as a reliable, and moreover profitable, theme for new businesses in the years to come?

A Golden Age for R&D

Siri as some of you will know, was commercialized by SRI and born from SRI's CALO project (Cognitive Assistant That Learn and Organizes) - a DARPA-funded initiative that saw some $200 million of investment over a five year period. Farecast (acquired by Microsoft), Radar Networks/Twine (acquired by Evri) and Adapx also have their roots in CALO.

This is serious technology. Evidence: Siri had 6 patents hanging on the wall on day one, and raised nearly $24 million in venture funding from SRI, Morgenthaler, Menlo, and Horizons Ventures to architect the system and eventually launch their service on the iPhone.

I remember sitting with our then entrepreneur-in-residence (who became a Siri co-founder and CEO) Dag Kittlaus and thinking about our idea of a do engine and how disruptive that concept could be. We were ebullient, but also humbled by the fact that CALO wasn't nearly the beginning of our work in this area - it was only made possible by many earlier, pioneering efforts and many decades of foundational AI research at SRI.

The age of assistants will see a pendulum swing back to back-end engineering and serious R&D and long-term entrepreneurship. Every decade or so we see this kind of shift, a move to fundamentally upgrade the Web with focused, infrastructure-level innovation.

And with a strong set of venture exits and a demonstrable thirst for innovation that goes beyond so many opportunistic, trivial apps, the conditions are ripe.

Siri has proven that real VPAs are not only possible, they fill a need in the market (the company had 250,000 users within a month of launching).

Siri is a beginning, one that will spur further investment of time, money and brainpower. Be assured that developing virtual personal assistants is a capital-intensive undertaking. The potential reward is great - "10 Microsofts", as it were. That's a promise that will help further catalyze interest in AI from companies large and small.

SRI too will continue to spin out ventures from the CALO project and other SRI research projects consistent with this theme, starting with Chattertrap, currently in stealth but soon to emerge.

The Convergence of Many AI-Enabling Trends

Groundbreaking R&D, it should be emphasized, is never merely the product of a sizable chunk of money and a certain concentration of engineering talent.

Innovation processes are as much an indicator and guarantor of success as any other variable in the lifecycle. Indeed,when it comes to an expanse as wide as AI, reliable and replicable innovation processes really start to take center stage.

Breakthrough ventures, I can speak from experience, are the result of a disciplined innovation process for creating ventures to meet market needs, something that companies and innovation centers in the Valley and beyond should be reminded of from time to time; pushing out mere technology never works.

SRI is famous for things such as Doug Engelbart's "Mother of All Demos" of interactive computing and the mouse - foundational breakthroughs that have stood the test of time. But what SRI does best is innovation. We combine research plus teaming plus venture creation plus commercialization to change the world. We address real needs with real technologies. Our secret sauce is, if anything, in our innovation processes, which help reduce the risk of our entrepreneurial activities.

Zooming out, it is fair to say that the state of the union of AI is quite healthy, and that Siri is indeed only the beginning. The revolution is not going to happen overnight, but the pace will start to accelerate from here.

We sit at the convergence of many AI-enabling trends - ubiquitous mobile access (increasingly, via smart phones), a programmable web of services with robust API access, a new paradigm of access and scalability in cloud computing, the maturation of the semantic Web and linked data, vast improvements in personalization, geo-awareness and now a demonstrable hunger by venture capitalists and giants like Apple in funding and acquiring new forms of intelligent software.

I'll close by revealing a roadmap progression we put together at Siri in the early days that I hope you get a kick out of:

• Siri Beta: Periodically Human
• Siri 1.0: Practically Human
• Siri 2.0: Positively Human
• Siri 3.0: Who are you calling Human?
• Siri 4.0: Human, book me dinner and a movie.

The future is here, and it just got distributed pretty widely.

]]> Discuss]]> http://www.readwriteweb.com/archives/the_age_of_assistants_the_view_from_inside_sri.php http://www.readwriteweb.com/archives/the_age_of_assistants_the_view_from_inside_sri.php Digital Lifestyle Tue, 24 Aug 2010 13:00:00 -0800 Guest Author iLink, a social network analytics technology from SRI International has recently been integrated into three online communities used by the military: Platoon Leader, Company Command, and the Family Readiness Group. The iLink technology improves the way the military community members share critical information across several different interest areas - from battlefield problem solving to supporting military families. Here, we take a look at the technology the military is using and how it can impact the future of social networking.

The iLink technology was developed as a part of the SRI-led CALO (Cognitive Agent that Learns and Organizes) program and was funded and managed under DARPA's PAL (Personalized Assistant that Learns) program. That project was designed to create cognitive software systems that can reason, learn from experience, be told what to do, explain what they are doing, reflect on their experience, and respond robustly to surprise: in other words, A.I.

iLink specifically was the part of the overall CALO project that focused on social search and message routing within social networks. It was also used to develop a system for FAQ generation within a network - they call this technology "FAQtory". With this technology implemented on a social network, FAQs are continuously generated and revised by the community using a Wikipedia-like model, as opposed to being static creations made by the site's authors. But it's not basic as a simple user-generated FAQ system - instead, iLink's FAQtory technology allows for incremental bits of information - even those that don't qualify as answers to the question. As the members contribute these bits of information, the learning system in iLink monitors how users are attempt to resolve queries and is then capable of drafting off of the social network's learning. Essentially, the technology actually enables the social network to discover and amplify its own capabilities

Other aspects of the overall iLink system involve not just incremental learning capabilities, but also the use of prior knowledge to solve problems, message-matching technologies for finding related information, algorithms for gathering data from multiple sources and compiling it together, and the ability to differentiate private information from that which is safe to share.

The Research Behind iLink's Creation

For those that helped create the iLink technology, such as the researchers at SRI's Artificial Intelligence Center, they see social networking as a much more valuable tool than, arguably, even some members of our own tech community do today. In a research paper on iLink (filled with details math nerds will eat up), they state:

"The social web provides much more than an opportunity for people to interact and exchange general information. It is a new medium for powerful models of organizing purposeful social activities. This is compellingly illustrated in the growth of open source efforts (e.g., LAMP,2 Wikipedia), which some authors [8, 14, 20, 27, 29] argue represent an alternate mode of social and economic production."

The authors of the paper state that much of the research in social networks has not formally modeled how these networks accomplish tasks. Most of the current work focuses on other areas like structural representation, analysis, and interpretation of social network data. Their work instead introduces a general approach to modeling how real-time, dynamic social networks communicate and cooperate to solve problems because an understanding of this could enhance the development of potential future applications...applications like expertise identification, FAQ generation, and smart RSS filtering.

iLink Model

iLink in the Military

Today, iLink is being used in the military communities to help recognize "who knows what" within a community, connect members to each other, and point members to valuable content, discussions, and others who share their same interests. Those connections between members and resources are made with iLink's machine-based learning to model the users and the content in order to facilitate the information sharing.

Currently, three military sites are using the technology: Platoon Leader, Company Command, and the Family Readiness Group. In Platoon Leader, current and former U.S. Army Lieutenants worldwide discuss and exchange information with each other. Company Command does the same for Army Captains while also allowing them to pose questions in order to solve problems together (crowdsourcing the military!). The Family Readiness Group helps coordinators nationwide share information and best practices with each other in order to point military families to resources they can use.

Platoon Leader

Where The Military Goes...Civilian Businesses May Follow

It was only a year ago that the military shut down access to several social networking web sites, including MySpace and YouTube, to users of the military networks. However, that shutdown was not so much a criticism of the social networking technology itself - only the public nature of those "civilian" networks. Concerned that users would share secure information like schedules or locations (for example: "Hi Mom! We're sailing into Dubai tomorrow!"), the military opted for a "better safe than sorry" policy. They also cited bandwidth concerns - sharing videos and photos can use a lot of bandwidth and not all areas of the world have much to spare.

Yet, social networking itself can be a valuable tool for businesses, and the military has realized that. In an organization, even one the size of the U.S. armed forces, connecting people to information and resources has been a challenge that I.T. has struggled for some time to achieve, and never mastered quite as well as the social networks do. In the past, businesses used impersonal, intranet-based web sites to provide files and documentation, but they miss out on one of the most critical sources of information - the knowledge that is stored in users' own minds. That knowledge that comes from both experience as well as information surrounding the undocumented processes that exist in any organization.

Now that the military is implementing more social networking technologies into their online networks - in addition to the three communities today, it's being evaluated for inclusion in several others - we'll likely see big business soon following suit. For those enterprise organizations that have been slower to pick up on Web 2.0 trends, seeing how the military uses a particular technology will be a big influence that may change their course of thinking. Social networks may just be fun for us as personal activities, but in workplace, they can be valuable tools for getting the job done...or even helping craft military strategy.

iLink's technology has been made commercially available. More information can be found at SRI International's web site.

military photo by: Randy Son of Robert; building by bourget_82

Accoona's new focus is on business search and news search. More from Zuula here:

Although it never reached the search engine “major leagues”, Accoona was a serious minor-league player for several years.  The service was launched almost four years ago at a major PR event attended by former president Bill Clinton, who reportedly carried out the first public search on the service.  Investments totaling as much as $100 million apparently were made to ensure that the service was backed by the best technology (and, of course, marketing).  And, if memory serves, the site even managed to garner a decent — if not earth shattering - amount of traffic in its first year or two.

At some point, though, Accoona’s fortunes took a wrong turn.  The quality of its search results didn’t meet expectations.  There were accusations of inappropriate marketing tactics on behalf of the search engine and inappropriate sales techniques by affiliated websites.  All of this — and more — ended up in a New York Times article last August that was far from flattering.

It wasn’t much of a surprise, then, when the Accoona announced late last year that it was halting its plans for an IPO.

It also wasn’t a surprise to most search industry veterans when word started leaking out over the past few months that Accoona was downsizing and considering alternative strategies for its business. [...] Today, Accoona quietly unveiled its new strategy, and web search apparently is not part of that strategy.  Instead, the new focus is on business search and news search.

Nicholas Carr blogged about Gwap a couple of days after its launch, noting that "one thing the Internet enables, which wasn't possible before, at least not on anywhere near the same scale, is the transfer of human intelligence into machine intelligence." In Gwap, which stands for "Games With a Purpose," that transfer of intelligence is done by getting people to do the routine chores that computers don't know how to do - chores like tagging photos, describing songs, and outlining objects, as well as transferring a good bit of human common sense to the machine. The trick to getting people to do these things is to make the work fun. Hence the games.

The creator of these games is Luis von Ahn, winner of a 2006 MacArthur Foundation "genius grant" and a pioneer in the field of human computation. Ahn is most notable for helping to develop CAPTCHAs (Completely Automated Public Turing Test to Tell Computers and Humans Apart), those somewhat annoying but rather effective distorted letter puzzles used millions of times each day. Last year, he also introduced the "reCAPTCHA," where CAPTCHAs were used to gain access to a web site while also helping digitize old books.

Gwap homepage

The Games

Gwap currently features five games, one of which is an old classic called the ESP Game. In the ESP game, two players view the same image and try to guess words that the other player would use to describe it. Google licensed this technology and launched Google Image Labeler to help improve the quality of their image search results.

• Matchin, a game in which players judge which of two images is more appealing, is designed to eventually enable image searches to rank images based on which ones look the best.
• Tag a Tune, in which players describe songs so that computers can search for music other than by title - such as happy songs or love songs.
• Verbosity, a test of common sense knowledge that will amass facts for use by artificial intelligence programs.
• Squigl, a game in which players trace the outlines of objects in photographs to help teach computers to more readily recognize objects.

According to the Carnegie Mellon announcement, von Ahn plans to add a lot of games to the site, saying "we have three more that we'll be launching in the coming months." He hopes that by having all the games on the same site it will encourage players to try several different ones. Players also have a single sign-on and password, Top Player rankings, and online chats, said von Ahn.

The Human Processor

In his whitepaper entitled "Invisible Computing," von Ahn compared game design to to algorithm creation, saying:

"...it must be proven correct, its efficiency can be analyzed, a more efficient version can supersede a less efficient one, and so on. Instead of using a silicon processor, these "algorithms" run on a processor consisting of ordinary humans interacting with computers over the Internet."

In other words, we're the processor. The machine is us.

This concept isn't entirely new - Amazon's Mechanical Turk, for example, pays people to contribute their time to work on small, simple tasks called "Human Intelligence Tasks," or HITs. However, unlike HITs, which can sometimes be boring or tedious, the games on Gawp are actually fun - and they don't feel like work.

Some believe that human powered processing is the next big wave for computing. You could argue that Mahalo, the human-powered search engine is an example of this. (Though others call it a human-powered link farm.) Perhaps a better example is ChaCha, the mobile Q&A service that uses human guides to respond to questions called or texted in from your cell phone. We've also covered other human-powered services on RWW in the past, like the Galaxy Zoo and Stardust@Home project, among other (our coverage here). Many of these efforts have tried to incorporate an element of "fun" into what is actually work.

Whether Gwap will actually gain momentum and get a large number of people involved is yet to be seen, but it is definitely has potential to help teach computers the things they can't do for themselves....yet.