Biology-inspired algorithm design and non-obvious news discovery
There is a new Science article which seems really cool, although I haven’t had time to get past the paywall yet. The title is “A Biological Solution to a Fundamental Distributed Computing Problem” and the gist of it is pretty simple: a research group has found that an important procedure in distributed computing, “maximal independent set selection”, has been solved in a simple and efficient way in a kind of fly’s nervous system development. An algorithm based on the process that occurs in the fly’s immature nervous system can be directly applied to a network of sensors, for example.
In other news, Bradford Cross, who started the data-driven flight-delay prediction company FlightCaster, is starting a new company called Woven. It will be about discovering news you are interested in, and the platform will explicitly consider a conundrum that I’ve often been thinking about, which is the following (and possibly mentioned in some earlier blog post): Do you really want to read news that are always perfectly tailored to your interests? Wouldn’t this cause you to miss a lot of interesting information that you get from e.g. browsing the newspaper and “accidentally” reading about things you didn’t know about but which are actually kind of interesting? Bradford Cross mentions this in a recent interview and says that he started to “miss the serendipity that a newspaper provides”. So far so good, but how to actually implement this kind of quasi-random content exposure (I tend to think of it as a kind of beneficial noise) into a news discovery service? I guess we will soon see what Woven has in mind.
Finally, the PayPal Developer Network (!) has a pretty nice tutorial about analyzing and visualizing the recently released World Bank data using tools like Java servlets, Google Charts and MySQL. The World Bank data would easily deserve a verbose blog post of its own (and I was planning one several months ago) but that will have to wait until I’ve taken a proper look at it.