Our guess is that personalized content will become a more popular paradigm in about 1 to 2 years.The article mostly talks about Reddit. I found this a bit odd, since Reddit strikes me as closer to Digg than a personalized news site, but Reddit does have a "recommended articles" page off their front page.
Personalized news has a couple of main attractions. Theoretically, if your news is personalized then it's not as vulnerable to gaming as [Digg's] power of masses approach. Plus people are getting busier everyday, so personalized news has a strong appeal as a potential solution for information overload.
As the article explains, Reddit appears to use a keyword-based approach like the Bayesian filter Paul Graham developed for spam filtering. I doubt that this simple content-based approach can be made to work well, And, unfortunately, as Emre said, "many [Reddit] users still complain about not receiving relevant news recommendations."
I went back to try Reddit's recommendations again -- I hadn't looked at it in a while -- and, after rating a few articles, it still put up a message that "no links have been recommended for you yet. keep telling reddit what you like and dislike by voting on links, and check back here later for recommended links." I never got to the point where I actually received recommendations. That is a problem. Recommender systems need to work from sparse data in real-time. They need to react immediately and instantly to new data.
Emre suggests that all personalized news sites are like Reddit. Findory does not use Bayesian analysis over keywords. Instead, Findory uses a form of social filtering where Findory readers anonymously and implicitly share the articles they find and enjoy with other Findory readers.
Oversimplifying a little, Findory works a bit like Digg except that rather than seeing a front page of the generally most popular articles, you see a front page of the articles that are most popular for readers like you. As Emre said, different lists for different people reduces the incentive to game the system by eliminating the winner-takes-all effect.
In general, the power of the masses approach, epitomized by Digg, has two problems with relevance. First, a most popular list is generic and untargeted; it is only relevant as long as your interests match those of the entire community. Second, as power of masses sites reach a mainstream audience, the incentive to spam grows and relevance drops. Personalized news has neither of these issues.
Finally, it is worth noting that personalized news is not limited to crazy little startups. Both Google News and Microsoft's MSN NewsBot have a small widget on their front pages that recommend news stories based on the articles you read.