From the Lab that Brought You Siri, It’s Trapit—A Personalized Discovery Engine
There are two kinds of people: Those who already own an iPhone 4S, and those who don’t but have seen Apple’s Siri ads and wish they did. Siri, of course, is the voice-operated personal assistant that can read your text messages, schedule appointments, check on the weather, make waffles, and babysit your toddler (just kidding about those last two). It’s the coolest feature of the latest Apple smartphone, which went on sale last week. Virtually overnight, it has brought state-of-the-art artificial intelligence technology into the consumer mainstream.
Well, it turns out that there’s more where that came from. The same Silicon Valley defense project that gave birth to Siri—called CALO, for Cognitive Assistant that Learns and Organizes (more on this below)—has another, lesser-known spinoff, a Palo Alto news personalization startup called Trapit. The company’s web-based service uses AI to organize the welter of new content that appears online every day into tailored collections called “traps.” And while the technology is still a bit raw, there’s a chance that it could have the same kind of impact in the world of Web search and online news that Siri is beginning to have on mobile interfaces.
I’ve been playing with TrapIt for about three months now. It hasn’t become a part of my daily news-browsing routine, but I can definitely see that happening if the startup continues to refine the interface, improve its search algorithms, and make the site more tablet-friendly. (Trapit took the lid off its service in June, but it remains in closed beta testing, which means you have to request an invitation to get an account. The wait was short when I registered. The company says it’s going to open the beta version of its service to the whole public later this fall.)
The first thing to try when you go to Trapit is either to browse one of the existing, featured traps—which are often related to breaking news, such as yesterday’s killing of Muammar Qaddafi—or start one of your own by entering a phrase or keyword into the “Discover” bar. After a short wait, you’ll be presented with recent news stories and blog posts on your topic, culled from across the Web.
At first the selection may seem pretty random. The neat part is that as you peruse various articles, which pop up in lightbox-style windows, Trapit observes what you’re reading, how long you spend with each article, and what you’re sharing with others. It uses these cues and others to beef up its profile of your personal tastes, so that over time it’s able to surface more articles that fit your interests and fewer that don’t.
You can also train Trapit manually by clicking on the thumbs-up or thumbs-down buttons—and the more you do this, the faster the software will learn your preferences. As you create traps on new topics and train your existing traps, you can end up with a whole gallery of mini-magazines, exclusively tuned to the mix of subjects that you, and you alone, are passionate about. It’s a pretty unique service—the closest comparison I can think of is Google Alerts, which are like standing search queries with the results e-mailed to your inbox every day. But Trapit is more like regular Web surfing. It’s just that you’re surfing the Web you want.
Trapit’s AI-driven approach goes completely counter to the dominant trend in news curation today, which emphasizes the power of social networking and collaborative filtering. News aggregation apps like Flipboard, Pulse, AOL’s Editions, CNN’s Zite, Yahoo’s Livestand, and Google’s forthcoming Propeller platform may seem to provide personalized news feeds, but … Next Page »