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Fascinating insight into the question of how networks learn.

Paper at http://www.nature.com/nature/journal/v548/n7669/full/nature23463.html?foxtrotcallback=true

The generated inputs are quite strange, I wonder where else something like this occurs.

Doesn't really sound sexy, but this is of utmost importance for next generation grids for renewable energy.

I agree on the significance indeed - a small boost also for my favourite Desertec project ... Though their language is a bit too "grandiose": "ABB has successfully designed and developed a hybrid DC breaker after years of research, functional testing and simulation in the R&D laboratories. This breaker is a breakthrough that solves a technical challenge that has been unresolved for over a hundred years and was perhaps one the main influencers in the 'war of currents' outcome. The 'hybrid' breaker combines mechanical and power electronics switching that enables it to interrupt power flows equivalent to the output of a nuclear power station within 5 milliseconds - that's as fast as a honey bee takes per flap of its wing - and more than 30 times faster than the reaction time of an Olympic 100-meter medalist to react to the starter's gun! But its not just about speed. The challenge was to do it 'ultra-fast' with minimal operational losses and this has been achieved by combining advanced ultrafast mechanical actuators with our inhouse semiconductor IGBT valve technologies or power electronics (watch video: Hybrid HVDC Breaker - How does it work). In terms of significance, this breaker is a 'game changer'. It removes a significant stumbling block in the development of HVDC transmission grids where planning can start now. These grids will enable interconnection and load balancing between HVDC power superhighways integrating renewables and transporting bulk power across long distances with minimal losses. DC grids will enable sharing of resources like lines and converter stations that provides reliability and redundancy in a power network in an economically viable manner with minimal losses. ABB's new Hybrid HVDC breaker, in simple terms will enable the transmission system to maintain power flow even if there is a fault on one of the lines. This is a major achievement for the global R&D team in ABB who have worked for years on the challeng

source of inspiration for visualization of complex networks

Oh, I like this one. One more point for swarm intelligence! :)

We could have come up with an inspiration like this !!! As creative as the roots :-) "These male amphibians use their calls to attract the female, who can recognise where it comes from and then locate the suitor. The problem arises when two males are too close to one another and they use their call at the same time. The females become confused and are unable to determine the location of the call. Therefore, the males have had to learn how to 'desynchronise' their calls or, in other words, not call at the same time in order for a distinction to be made."

Memristor-Based Artificial Neural Networks, huge potential for true, high-power AI

Memristors (for memory purposes - RRAM type) on the pipeline to be launched in orbit on a cubesat http://thewhitonline.com/2016/03/news/nasa-initiative-chooses-rowan-to-launch-satellite/

Implementation of the deep learning-based image classifier (online). Try making a picture with your phone and upload it there. Pretty impressive results. EDIT: Okay, it works the best with well exposed simple objects (pen, mug).

A TED talk about Google X way of working and some closer look at the project loon (stratospheric balloon network for internet connection) by the 'moonshot captain' Astro Teller.

After graphene and blue brain, the European Commission has quietly announced plans to launch a €1-billion Euro project to boost a raft of quantum technologies - from secure communication networks to ultra-precise gravity sensors and clocks.

Researchers at Tohoku University have, for the first time, successfully demonstrated the basic operation of spintronics-based artificial neural network.

It is typically considered that brain's process of learning is highly energy efficient. While investigating how efficiently the brain can learn new information, physicists have found that, at the neuronal level, learning efficiency is ultimately limited by the laws of thermodynamics.

http://arxiv.org/abs/1104.4141

any of the geeks tried this already? Francesco?

nobody ... you are not as geeky as I thought ...

wow impressive. Could be super useful for astronauts !

Google subsidiary Google Fiber, Inc. is seeking permission to place satellite antennas on land near its data center in Council Bluffs, Iowa. The antennas could be used to receive content feeds from broadcast networks that could be bundled with a high-speed fiber service.

an oddly similar story http://venturebeat.com/2012/02/20/apple-is-solar-friendly/ apple to build largest solar array in US

According to the company's data team, in 2008 the average amount of separation between any two given people on the network was 5.28 steps. Just three years later, it's 4.74.

Gephi is an interactive visualization and exploration platform for all kinds of networks and complex systems, dynamic and hierarchical graphs. Runs on Windows, Linux and Mac OS X. Gephi is open-source and free. Learn More on Gephi Platform " Gephi 0.8.1-beta has been released! Discover a new Timeline, dynamic ranking and weighted community detection.

trajectory calculations by no-brainers ... Newton known to primitive fishes? (can we use it for space? :-)