If you’re feeling a quickening every time you look at the web. If you sense new opportunities but can’t quite put your finger on what they are. If there is a feeling that things are changing but you’re not yet 100% how then you’re not the only one.
It appears that the web we know is undergoing a massive transition that’s becoming ever faster. The companies we used to do business with are doing things that appear to not make much sense and the products and services coming out appear to be a little fragmented in their approach.
If this is what you’re experiencing, don’t worry. It is normal. You’re in the grip of the semantic web. If you’re not yet sure what this think of Web 3.0 the moment when the data that’s on the web begins to accumulate to the point where in order for it to make sense you really need to contextualize it, personalize it and make it responsive to the individual.
In a way this is exactly what semantic search does. The semantic web is characterised by the introduction of products and services that take a dumb task and make it intelligent. Think of cash machines for instance. Unchanged since they were first introduced in 1967 they are now becoming more intelligent by looking at the way the individual uses them and presenting, each time, a tailor-made experience.
To achieve this it doesn’t take much. The data, as in every Big Data instance, has already existed, accumulating through the years. Your bank, for instance, knows when you use the ATM whether you usually take out a twenty or a fifty, whether you prefer tens or go for large notes (when that option is present), yet still, you have today to go through the same dumb, multi-step menu as everyone else before you get it to do what you want it to do. And that is just one easy example of personalisation of a service at the end user interface that’s possible.
The trend is taking shape and form across the entire industry. Its characteristics are simple:
1. Making Use of Big Data: Companies have been mindlessly collecting data for years that’s now too much for them to sift through and make much sense of. This is where a Big Data approach really helps bring out patterns that can improve services and help save money.
2. Employing algorithms: Whether it’s Google using algorithms on YouTube to predict videos we like and preload them on our profiles or Audi, using algorithms to create driver-friendly headlights that dip automatically the moment they sense oncoming traffic, the end result is the same: a smart program goes through large amounts of data and produces an action that changes the end-user experience.
3. Providing a personalised experience: Personalisation is not going to go away. By getting rid of the “one size fits all” approach that the Industrial Revolution saddled us with we are finally getting into the era of customized products and services that closely meet our needs and more than adequately predict our demands.
4. Capturing data from sensors and interfaces: The moment you start to capture data and provide personalization the pressure is on to continue to do so on an on-going, ever more refined basis. Data that comes in from smart sensors, mobile device and end end-user interfaces is used to further, automatically customize the service. One of the most classic examples of this is Google’s Voice Search that was trained through the use of 370 billion real-life, natural language end user search queries and which, once activated, uses clever programming to further improve the end-user experience through better understanding the user’s speech patterns and accent.
Everything that happens then, from Google’s acquisition of Waze for $1.2 billion to Yahoo paying an equally enormous crazy amount for Tumblr to Apple bidding to acquire Primesense, the company behind Micrososft’s Kinect technology, is driven by the semantic web and the need to finally provide context-sensitive, personalized products and services.
From a certain perspective we could say that the future, suddenly, has already happened. We’re just not completely aware of it, just yet.