Algorithms and Sensors – web 3.0 services abound

Its been a while since my last post – I’ve been consumed at my work ( which I have been really enjoying) . However, I felt compelled today to write a bit about algorithms and sensors, which are creating some GREAT services now and even better in the near future. We are watching web 3.0 ‘blossom’ right now. Here is what I mean.

Ever since I’ve gotten my hands on Apple’s new iPhone 4Gs and Siri, my mind has never been the same. Not that Siri is the end all and be all. It has its drawbacks and in fairness, Apple has always and still does call it a ‘beta’.

But the mere presence and interaction I’ve had with Siri signaled something new to me on the internet was really happening – and in a very subtle but meaningful way.

Siri is learning – yes, she really does learn. “Artificial Intelligence” – no one seems to think that the machines are actually intelligent, but they can certainly do a lot of things that used to be hard for computers. Clearly Siri is an ‘AI’ that is programmed to adapt in certain ways and modify its behavior according to how I or what I would request of Siri. Fascinating really.

The real thing to keep your eye on here is that sensors plus big data algorithms are leading us from today’s world where content considered king to one where content is simply one component of a service. Content is becoming secondary and the service and platform primary. There never used to be 13 different ways to rent’ the same movie before. Content is becoming commoditized.   When Siri was first introduced, its creators called it a “do engine.” that is, rather than retrieving a web page (media) that you consume to make a decision, it just does things for you. “Find me a restaurant near here.” “Make me a reservation.” Media will become part of a database back end rather than a media front end.

Some examples of sensory algorithms that in effect build a network-mediated global mind are (this is really us, just augmented):

–          Mobile cell devices -we are augmented with cellphone cameras (electronic sensors again), the ability of events to become a shared experience is has become vastly increased and more so now with social media connects.

–          Smart Parking Meters – In the city of San Francisco, you’re seeing something similar, where all the parking meters are equipped with sensors, and pricing varies by time of day, and ultimately by demand. In effect an “algorithmic regulation” – they regulate in the same way our body regulates itself, autonomically and unconsciously.

–          Predictive AdWords -Google’s Adwords were always more effective than competitors because Google was better at learning from human input – instead of selling ads to the highest bidder as competitors such as Yahoo did, they used machine learning algorithms to predict which ads were more likely to be clicked on. They might choose an advertiser who only wanted to pay half as much if their ad was 3 times as likely to be clicked. Google was the first to harness the collective intelligence of their users to improve ad results. Just like the social media platforms we use to disseminate events and other digerati it’s important to understand just how much this is man-machine symbiosis.

–          Large connected networks – it could be Facebook, Twitter, LinkedIn or G+, but any one of them connects to most of us somewhere at some point. The massive sharing of data and thoughts, the crowd-sourcing of opinion and the collective conclusions we draw are all kept and logged, improved upon and progressively mature and evolve. Here and on these massive giants, nothing stays the same for very long. The mere platforms themselves have spawned other interconnected platforms like Zynga.

The Internet as a whole is a mirror image of us  – a thriving interconnected network. It improves with knowledge and data and learns 24/7. It’s the community that creates content. Its about how you engage people and who you engage, not the number of followers.  It’s about the collective impact we make together. The Internet is an architecture of participation, interconnected, open source and open protocols. It really is our global brain. Look at the ‘picture’ of the network. It is no coincidence that it looks the way it does.

the internet

Google also thinks about this. Their key business model depends on the success of others – driving traffic to their sites, and producing ad results. Google only does well if their partners do well.

Contrast this with how the dwindling and toxic financial firms, who once positioned themselves as the enabler of the economy, creating liquidity and trading on behalf of clients, began to trade against them, and increasingly created products – from the mortgage backed loans that brought down the global economy to even more reprehensible trading practices that have driven up the cost of food for starving millions and was directly responsible for not only our economic collapse, but the ripple effects that are being felt worldwide. This is capitalism gone wrong. Occupy Wall Street’s fundamentals are not incorrect.

In the end, a company is most successful when it makes all of its stakeholders successful, not just its shareholders – a good example of this is Apple.

Which brings me back to algorithms and sensors. Soon, Apple will release an API for Siri. Many businesses’ that can use it will use it and the revolution will progress in earnest. As Siri learns what I do the most on my mobile device, she will also begin to learn my doctor’s and dentist’s name, the nearest hospital to me and map, my grocery list and cost and what I’ve run out of in my house, the type of movies I watch and music I listen to and where to find the content. In short, Siri will make my life a little more convenient and predictive. It will combine my habits with my surfing activities on the Internet and will suggest based on location where to buy items that interest me conveniently and cost-effectively based on my location.

'Things to Come' 1936

Just think of the services that will come…H.G. Wells would have had a blast.


‘clouds’ and ‘context’ and web 3.0

Web 1.0 can be seen as embracing the ‘Commerce‘ on the web (amazon, ebay, netflix, etoys +) and a whole bunch of failed’s that went bust during the March 2000 meltdown. Web 2.0 can be viewed in terms of embracing ‘Community‘ as myspace, youtube, friendster, linkedin and facebook. Niche communities to be part of online. So what is web 3.0? It’s ‘Context and Clouds‘. With Web 3.0, the internet will act as my personal shopper through increased personalization, a built in recommendation engine through your peers in online communities and in the ‘clouds’ – whatever software and media you need will live in a ‘cloud’ (like DropBox) or (set of them) for you to tap into anytime just using a browser. webtonic.jpg

In order for the web to really become a ‘personal’ shopper and recommendation tool it has the potential to become, it needs to get my data. The enormous amount of data that is being collected by various services will over time be used to deliver specific and personal media to me. And its not just media that will be suggested. Everything from what interests me personally – clothing to household appliances will be ‘personalized’ just for me. And frankly, some call this an invasion of privacy. To me, it’s finally a tune-up of how advertising should work. If TV advertising worked this way, we’d all be happier to sit through some ads on TV. But it doesn’t. And the internet will be able to ‘perfect’ what TV has been unable to do since the 1940’s. old-tv-set.jpg Let’s take a quick look at TV.

On TV, advertisements run on certain programs based on the demographic and audience measurement data gathered by Nielsen. Nielsen operates in over 100 countries. Nielsen was founded in 1923. Nielsen conducts these tests by calling the locals and asking them what they are watching at the moment.

The system has been updated and modified extensively since it was developed in the early 1940s. It has since been the primary source of audience measurement information in the television industry around the world. Since television as a business makes money by selling audiences to advertisers ($65 billion spent on TV in 2006, Ad Age), the Nielsen Television Ratings are the single most important element in determining advertising rates, schedules, and program content.

Nielsen Television Ratings are gathered by one of two ways; by extensive use of surveys, where viewers of various demographics are asked to keep a written record (called a diary) nielsendiary.jpg of the television programming they watch throughout the day and evening, or by the use of Set Meters, which are small devices connected to every television in selected homes. These devices gather the viewing habits of the home and transmit the information nightly to Nielsen through a “Home Unit” connected to a phone line.

OK, so its 2008. Doesn’t the above sound a little ‘tired’ already?

Now switch to the internet. While some people are irked by ‘cookies’ and other’s by giving away information on forms or saving a ‘preference’ on a website or which websites are in ‘my favorites’ or ‘bookmarks’, these actions eventually will all allow advertisers to better target each of us and offer a service/goods or media that I’d really consider owning. And it’s the web services that mine this info through my interaction with them that are the best. Google being the first and best at it, is now a ‘brand’ name. And it’s the only brand name that doesn’t advertise and never has (think about it). It engages. Its very core looks to help and through its offering of great services to us, allows it to gather information about us and tailor its ads and services accordingly. I use many services offered by Google. In exchange for this, I’ve given some of my personal info to Google.

New ‘vertical’ search efforts like sidestep (travel), icerocket (blogs) imedix (medical) and other ‘niche’ search products will further help advertisers deliver specific services for each of us that are helpful and useful. Google has done a great job in a broad sense but now it appears that there are many new ‘vertical’ search engines that specialize in searching very specific ‘ niche’ subjects and categories. Drilling down where Google is not. Over the course of the next several years I think we will see several ‘vertical’ search engines giving Google a run for its money.

But that’s another post for a different day.