A unit of Chinese internet giant Baidu Inc. has developed an algorithm that can predict crowd formation. They published results in this amazing paper http://arxiv.org/abs/1603.06780 .
This piece of news also reported at the end of March by The Wall Street Journal: Crowd Control ?
Machine-Deep Learning and algorithms capable of using crowd (and in general network) big-data to make predictions have a clear strategic value (for example for optimising service provisioning, for anticipating new trends). Big Data should be made "actionable".
Commoditization of Telecoms is opening up a new era for the A.I. applications: ambients that learn, self-driving cars, high frequency trading bots, I4.0 robotics, emulating/creating new drugs, developing contents and even music (e.g., Magenta), any sort of Avatars (e.g., Cortana)...
Indeed we are witnessing the rise of a "Networked Artificial Intelligence" with the humans-in-the-loop. In fact, see also this analyst-in-the-loop security system, which combines analyst intuition with machine learning to build an end-to-end active learning system for security.
According to Jeff Bezos (CEO of Amazon): “A.I. is going to become gigantic and it's probably difficult to overstate the impact it will have on society over the next 20 years“
So we can argue that, current socio-economic drivers and IT trends are bringing to a convergence Computer Science, Telecommunications and A.I.. Mathematics will be the language, computation will be about running that language (coded in software), storage will be about saving this encoded information and, eventually, future networks (e.g., 5G) will be creating relationships –at almost zero latency - between these sets of functions.
I believe that the design, development and exploitation of this “Networked A.I. with humans-in-the-loop” will be one of the most exciting and impactful directions of research and innovation, requiring multi-disciplinary approaches and offering far reaching opportunities for our society and economy.