We are discovering new information sources every day and in our attempt to keep up with the news we are trying to cover everything. Sooner or later, we are realizing that it is just way too much.
We were visiting tones of sites to fetch our news and then we've got the RSS feeds. We were reading tones of feeds and then we've got feed aggregators. We were using different IM protocols and clients and then we've got Meebo. We have been using various emails and then we've got GMail. We have joined social networks and started to microblog and then we've got FriendFeed.
So far we have solved one side of the content flood problem: aggregation. But this is definitely not the end of the game. The next step will be indexing all this information and the search giant is not yet doing much in this direction. And finally we will need smart AI-based content filtering.
Regarding too many feeds, I think there is an untapped market for very intelligent filtering and recommendation tools.
The future is not FriendFeed. The future is for aggregators plus smart/AI filters. Those that will figure it out will lead the content market.
FilterMyRss is a simple feed filter that uses keywords to identify only the posts that may be interesting.
Matoumba uses a Digg-like approach for learning from your behavior. By voting up or down the stories in your feeds, you teach Matoumba what are your fields of interests and prefered feeds and in time Matoumba will be able to tell you which information should be important to you within all the feeds you suscribed to, or even within the feeds from users who share the same interests as you.
The approach taken by FilterMyRss is simple and resembles the way we are using search engines. Probably its best use is for tracking the apparition of the terms of interest on various I can think of how marketers can be using it while searching for feedback about their products.
On the other side Matoumba seems to have learned from others (Digg, Reddit, etc.) and is using a smarted approach that aligns with the current social media filtering approaches.