Founded in 2009 by Adrian Aoun, an entrepreneur and former employee of Microsoft and Fox Media Interactive, Wavii provides users with news feeds culled from across the Web that can be accessed via Wavii's website or mobile app. Unlike Google Alerts, these feeds are composed from content beyond Google News. Wavii gathers its information from all over the Web--news, videos, tweets, and beyond--and then attempts to make sense of what it has found using machine learning techniques.
Wavii is not just a pattern-matching system. It recognizes linguistic concepts and that understanding makes its assistance more valuable: Not only is Wavii good at finding information that matches a user's expressed interests but it also concisely summarizes that information. The company has succeeded at a task that other companies haven't managed to do quite as well.
Aoun says that what everyone else has tried to do is model the linguistics using natural language processing technology. "We teach our system the way humans learn," he said in a phone interview.
Aoun describes the processes as similar to the way a child learns, hearing words, attempting to discern patterns, attempting to apply those patterns, and incorporating corrections.
"Our system reads a lot of the Web, then deciphers patterns via machine learning," he said.
Humans play a part in the process of teaching Wavii. They guide the machine learning. During early testing of Wavii, a user who had chosen to receive a feed with information about wedding engagements might have seen a Wavii-generated summary that read "Obama engaged to Ahmadinejad" because Wavii had scanned an article reporting that the U.S. president had been engaged in a heated debate with the Iranian president. The error would have arisen because Wavii hadn't yet figured out, or been instructed to distinguish, the different ways the word "engaged" can be used.
Wavii's capacity to understand, limited though it may be compared to the human brain, may help original reporting stand out from the sea of re-reporting in online news. The service automatically summaries online stories (making it easier to scan headlines) and simultaneously emphasizes original stories over duplicates. According to the company, a single story on average is re-purposed into 126 different articles or blogs. Such dilution may siphon visitor traffic away from the original publisher's website rather than drive traffic to it.
Wavii is also notable for its backers, a number of Silicon Valley venture capitalists with track records and technologists who understand the difficulty of machine learning. Investors include Ron Conway, Aydin Senkut, Mitch Kapor, Mike Arrington, Dave Morin, Shawn Fanning, Keith Rabois, Joshua Schachter, Paul Buchheit, Rick Marini, Max Levchin, and others.