“Sometimes a picture really is worth a thousand words” – Shailesh Nalawadi, Product Manager for Google Goggles.

Google’s new Goggles project allows users to gain access to information about an item or location simply by pointing their phone at it. So the phone can connect to reviews of a restaurant, the history of a landmark, or price comparisons for a book – all without any text having been inputted.

The technology works in conjunction with a mobile phone camera; the user takes a photograph of an object and the application scans it, comparing elements of that digital image against its database of images. When it finds a match, Google tells the user the name of what they’re looking at, and provides a list of results linking through to the relevant web pages and news stories.

The results can then be saved as a history, allowing the user to refer back to these links of interest. As the results are programmed to be relevant and are adjusted to each object: if the user takes a photo of an artwork, the results include the artist’’s biography; whereas for a landmark, the phone provides historical background information.

Google Goggles also uses optical character recognition to identify text, allowing items such as business cards to be snapped and scanned to make phone calls and to add as a contact in your phone directory. Some results don’t even require a photo to be taken due to integration of GPS, augmented reality and digital compass technology. Simply pointing the phone at a location (a business or shop for example) allows the app to place a button with the company name at the bottom of the screen. This can then be touched to load information from a web search.

Google Goggles demonstrates the potential for computer vision technology, but it is not at its full strength yet (hence it is being released by Google Labs). At the moment users will be able to lookup things like CD, DVD and book covers, wines, barcodes, businesses, artworks, logos and landmarks with great success but other objects will not work so well. Cars, animals and food are still in need of development to be photographically understood. Despite the immaturity of the technology, Google states that Goggles can recognise tens of millions of objects and places.

Google also claims that the technology has the potential for face recognition. So in theory a mobile phone could provide personal information on anyone in its viewfinder. Clearly this raises some pretty major privacy issues – and there are currently no plans to release this feature of Goggles. As Vic Gundotra, Google’s Vice-President of Engineering, has said, “We still want to work on the issues of user opt-in and control. We have the technology to do the underlying face recognition, but we decided to delay that until safeguards are in place.”

With this new technology comes exciting prospects for education. Visual search allows for a more interactive and creative form of learning; education can be taken outside the classroom without the need to carry text books for reference. And the fact that these searches can be stored in a history allows for retaining and referring back to this knowledge later.

For example, a class could visit an art gallery on a school trip and simply take photos of the exhibits without having to make a note of the artist. This allows for a liberated experience not tied to pens and paper. Web links generated by these photos would allow a student to purchase a(n e-)book about the artist before they have even left the gallery.

This mobile learning style could engender a sense of adventure and exploration while still linking learners to reference material. Classes could strolls around a new city, capturing images to discover the history of buildings and landmarks. Google Labs state in their accompanying video that they envisage Google Goggles being able to discover the species of plant from a leaf. An added bonus to this visual search ensures that the students need not worry about spelling mistakes and the phrasing of searches in order to gain the results that they require.

Neither the technology behind the application nor the concept is entirely new. Quick Response (QR) codes are two-dimensional barcodes which link to online content when the user takes a photo of one on their camera phone. A simple piece of software enables the phone read the URL encoded within the QR code, and the user is taken directly to that site in the mobile browser.

Image-based searching isn”t completely new either. Prior attempts at the technology include Nokia’’s Point and Find and Amazon’s image recognition search released in October. The most similar product on the market is an application called IQ Engines. But this has a much more commercial focus – connecting mobile users with reviews, prices and purchase links. It remains to be seen whether Google can bring the technology into the mainstream.

Culture, digital, Education, future, google, learning, qr codes, search, technology

The real-time environment of the internet has evolved a concerning dichotomy for fact and fiction. When Michael Jackson died in June, word spread too fast for Google to cope, and the site began blocking any search for “Michael Jackson”. But the lust for up-to-the-minute news could not be kept at bay – word spread through tweets and other micro-blogs regardless. Real time reporting had the edge.

Or did it? On the very same day, Jeff Goldblum was also reported dead, provoking a similar unstoppable surge of rumours and gossip

Real-time internet may be powerful in keeping up-to-date with news, but it most certainly lacks reliability – Jeff Goldblum, as it turns out, is not dead after all. Therein lies the problem. In the explosion of information surrounding extremely recent events, how can we distinguish fact from fiction when we don’t know how the fuse was lit?

Real time is the talk of the internet search town at the moment. Twitter, the biggest contributor to real-time data, continues to grow in popularity and Twitter Search, the only real-time search engine with access to all tweets, is in a powerful position. But a wave of search engines which pull together data from across the web have sprung up recently. Sites like Collecta, OneRiot, and Scoopler broaden real-time search to include blogs, articles, photos, and videos as well as tweets. And in recent months the big players have shown that they want a piece of the action too: Google, Bing and Facebook have all taken steps to keep up with the real-time crowd.

But what exactly is real-time search and why is everyone so excited about it? Traditionally, search engines like Google have organised their results based on authority. Sites have authority if they have grown slowly and organically over time. Real-time search engines, on the other hand, sort their results by how recent they are. Through these search engines, users can access a river of the latest information on whatever topic they choose.

Increasingly people are turning to the web to find out what is happening right now – the recent protests in Iran are a perfect example (and a frequently mentioned one). But when you search for a term in a traditional search engine the results look very similar day after day. If a volcano is erupting, followers on the web do not want to read an old article about the properties of lava, however authoritative it may be. With the real-time web your results will be different every time, and often refresh before your eyes. So no out-of-date articles, and no need to wait for news; users have access to up-to-the-minute comments and images. They can find out what is happening at the heart of a demonstration or at the site of a volcanic eruption as the event is taking place.

The real-time web also tells you what topics everyone’s talking about.  Most real-time search engines display trending topics, the most popular at that moment, and many can sort results by categories such as sport or entertainment. Want to know what your colleagues will be talking about at work tomorrow? A real-time search will probably tell you.

But a real-time search will probably also tell you all the information you didn’t want to know, or didn’t care about. Aside from rumours becoming gospel faster than you think possible, the current main disadvantage of real-time search engines is their inability to filter unwanted messages or irrelevant noise from results. The river just keeps on flowing regardless of what it has picked up along the way.

Collecta have openly stated they are currently paying no regard to relevancy in their results. Oneriot, however, have begun to experiment with reliability by introducing Pulserank, a toolbar which not only takes into account the freshness of the information, but also the authority of the website and person posting the information, alongside the velocity of the information passing around the whole web. The potential for the tool is huge, but although this seems like a reasonable approach, it may not catch something important as fast as simply watching the unadulterated stream.

Although far from fully effective, the Pulserank toolbar does pave the way for the necessary filters which real-time searching will require as the phenomenon grows. More users will undoubtedly lead to more spam and more noise being generated, increasing the need for an effective filter barrier. The challenge for real-time search engines is to combine recency, relevancy and reliability in their results without becoming elitist and losing the organic chatter of the online crowd.

Problems aside, the current animation surrounding the technology should lead to exciting developments. One such possibility being the use of real-time internet searching as an alert system – by signaling variations in the stream of mentions for a particular query, any abnormal rise in the quantity of chatter would trigger a notification. So the future of real-time search is bright, if hazy. Entrepreneur Edo Segal believes that old-school search will never vanish, but real-time news will create a society where we have an omnipresent sense of the moment.

Culture, future, google, news, real-time, search, technology