If we develop the topic of cloud and big data in a more general context, the first thing to understand is that this is not about any particular vendor. We’re talking open source here, the moment you remove lock-ins—see Flume, Hadoop, Hive, Impala, to name just the Apache stack as an example. It also is not about the pure amount of data that we can handle. It is not about Tera-, Peta- or Exabytes.

It likewise is not really about knowing where you’re shopping and what. Those are rather “mundane” applications.

It is really about generating decision relevant information from that data.

And it is then about having the possibilities to implement products based on these decisions at marginal costs. Consider 3D printing. Today, we can not only print toys. We can print houses. We can print Nylon stockings. We can even print the functional equivalent of kidneys. In the future, a very small number of experts will be required to convert the observed “templates” into mathematical models to serve to drive reproduction machines.

Since quite a while already, we can create about any gene code—only if the argument would arise that biological processes are too complicated. They are quite complicated. So are the “printers.” Three years ago, the Craig Venter Institute generated the first bacterium DNA, creating “the first species to have its parents be a computer” (see http://news.bbc.co.uk/2/hi/science/nature/8695992.stm). Read more…