It's as if the world's celebrities, politicians, and companies were your Facebook friends. News aggregation website Wavii, launched today, distills current affairs into a feed of the kind of pithy, easily digested updates seen on the social network.

Users of Wavii (pronounced "wavy") who logged in yesterday would have been informed of the biggest technology news of the day with a short update similar to those that Facebook produces when two people enter a relationship: "Acquisition: Facebook acquires Instagram for $1 billion." Clicking on the update yields more information and a link to online articles about the event; clicking on a company name calls up a profile page showing all recent updates about it.

Wavii creates its newsfeed by digesting information from online news sources and turning them into short summaries. It adds photos, charts, and maps as appropriate. Users choose a set of interests, companies, or people that they want to see updates about in their newsfeed.

Wavii's founder and CEO, Adrian Aoun, says Facebook's approach to summarizing social news was a direct inspiration. "It's so efficient that in three minutes I can stay up-to-date with a thousand friends. I get everything in context, with maps and photos, and I can click on people's names," he says. "But I only get these updates on my friends, not the world."

Giving the news a Facebook-style makeover is not straightforward, though, because unlike Facebook, Wavii cannot rely on its users to neatly classify world events into defined categories. Nor are news articles easily digested by software. "We have to do it by crawling the real-time Web and teaching the computer how to read," says Aoun.

Aoun and his colleagues used machine-learning techniques to teach their software how to categorize the events described in news articles: for example, that two people got married, or a company released a new product. The news can then be succinctly summarized in the most appropriate way, including the addition of relevant photos or quotes.

Wavii's system was trained using data sets that provided basic knowledge needed to identify public figures and companies, and how events are described. Then it was set free on live data from the Web and tasked with identifying new events worth reporting. The things it came up with were reviewed by humans. That process, over time, taught Wavii's software to accurately recognize over a thousand different types of event, says Aoun, so it can constantly feed on online news sources and summarize the most important news of the moment.