Everyone is now a publisher. Blogs, tweets, videos, podcasts, wall updates, broadcasts, forums, magazines, movies, ebooks, reviews, comments, aggregations. Long-form to 140-character form. All goodness but lots of Noise.
Signal? Google. Google can get the first page of results “right” most of the time. PageRank has been brilliant but even today falls short and in the future it too will be a dinosaur.
David Segal did a nice job showing one example of a kink in the armor in his Bully Finds a Pulpit on the Web article. Google showed that they can act quickly like a small company while leveraging long-term signal to noise R&D efforts that their large company resources funds by adding some signal to noise algorithms for this specific use case as described by Amit Singhal in this blog post.
This is just one use case. The more general signal to noise development will be fascinating. More on that another time except to list few variables that need to be better developed in the signal to noise algorithms:
+ individual-level, granular, portable reputation
+ the interesection of algorithmic curation, human curation and crowdsourcing
+ social graph intelligence
+ use of presence and location to add metadata automatically
+ feedback loops amongst these