Then, too, you might want to read Persai, a new filtering program that aims to cure the Web's information overload by Paul Boutin of Slate Magazine:
"I've got two main beefs with RSS. The first is information overload. If I don't check in every few hours, my RSS reader fills with unread blog posts. Rather than feel relieved that I can catch up on my missed surfing, that long list of bold headlines gives me the sensation that I'm hopelessly behind and won't ever catch up. I've got enough to do at home and at work that I don't need Web surfing to seem like a chore."
***I'm down on RSS at the moment, but I'm not ready to abandon it just yet. That's why I'm excited about Persai, a new service that promises to solve my two big problems. The application, which is now in private beta test, bills itself as a smart filter, a way both to tame and to improve your RSS content.
Persai (pronounced per-SIGH) is a system for reading RSS-fed content, but it doesn't focus on individual feeds. Instead, it throws everything it can find into one big hopper, then asks about what you like so it can dole out suitable articles. You start by creating one or more "interests" based on keywords of your choice—say, "American Idol" or "astrophysics discovery." Once you've punched in your interests, Persai turns each one into a custom page. These pages look a lot like Google News search results—a collection of news articles and blog posts from the past day that match your interest. The matches aren't based on exact keywords, but rather on a more complex word-math algorithm that can figure out that a post about Carly Smithson matches my American Idol interest.
Information overload affects all of us. Is too much worse than too little? I am thinking only if the too little is not the best information we can get.