Automatic generation of interesting thing to read?<p>While I believe in the tech of statistical NLP, I question whether the quality of news articles automatically generated from other news and social media will be all that interesting.<p>I spend about 3 to 4 hours a week reading through Twitter, HN, and Reddit: half is to waste time in an enjoyable way and half is to find interesting articles to read, new useful projects, etc.<p>For me, Twitter is the most targeted because I follow people into the same tech that I am into. I also have several blogs I follow closely. A big part of it is enjoying authors' online personalities and having occasional email dialogs.<p>Can an automated system replace part of this experience? I don't think so.<p>What automated systems can do is cluster reading material and make good recommendations - but this is different than what (it sounds like) Wavii is trying to do.
The real power of an application like this would be aggregating real-time news events as they unfold and creating news stories from real-time tweets, blog posts, and other social media. Instead of just clustering together topics, being able to "read" a large amount of sources and generate a summary would actually be very useful. Unfortunately, I think that it ignores a lot of very difficult problems in natural language processing and computational linguistics. It will likely have a few homeruns, but peter out as it hits an accuracy wall.