19 June 2014

"The Second Machine Age": Where is "intelligence" computed ?

In the book “The Second Machine Age”, the Authors Brynjolfsson’s and McAfee’s have argued that the exponential growth in the computing power , in the amount of digital information and in the number of the interconnected devices will bring soon the “machines” to do things that we usually do, as humans. Imagine simply the evolution of the Google “self-driving car”, or drones and robots providing services in doing tasks or jobs, which are carried out only by humans, today.

Well, I believe that this is again another expression of the Edge Softwarization. As a matter of fact, today collected data are reaching (almost immediately) any corner of the world (with high bandwidth networks), huge amount of computing (Cloud) is available to transform these data in knowledge, for deciding actions (then done by pervasive actuators). This is the definition of “intelligence”: i.e., the capability of processing and exchanging information to understand what’s happening in the environment, to adapt to changes and to learn. This is also like saying that the “machine intelligence”, if properly computed (where?) and distributed with highly flexible networks (what latency?) will be really game changer,  capable of creating new service models, such as “Anything as a Service”.

Google “self-driving car” could be an example where an Intelligent Machine is replacing (partly?) the car driver. Another example: let’s consider the use agricultural drones. Even today drones are being adopted, just like terminals or any other consumer electronic device! In fact, the availability of cheap and easy to use drones is largely due to the remarkable advances in technology: tiny sensors (accelerometers, gyros, magnetometers, and often pressure sensors), small GPS modules, powerful processors, radio communications. In agriculture, these devices will transform in an unprecedented way the job and working skills. Tomorrow, drones and robots (made intelligent and controlled through a low latency network) may provide farmers with a lot of customized services, e.g. detailed views revealing patterns from irrigation problems to soil variation, pest and fungal infestations, differences between healthy and distressed plants, etc. And this at any time the farmer may want, even every hour. Agricultural production and distribution processes will be mapped in huge data sets, employing big data analytics to make optimal decisions.
So, the availability of huge amount of processing and storage (e.g. in Cloud and at the Edge), interconnected by flexible and low-latency networks (i.e., Net Softwarization) will be able to morph the space-time dimensions of life, as the physical direct presence of humans will be less and less required to perform certain jobs or tasks. A transformation of economy.
My take is that when “intelligent machines" will become that pervasive (exploiting Anything as a Service) there will be a number of socio-economic impacts: reduction of human efforts in jobs subjected to computerization, robotization …; increase of local production; reduction of long distance transportation; “optimization” of socio-economic processes; and industries will not need relocating, as today. But a question remains: where is this (artificial) intelligence computed ?