I love it when my field of research is explained in such simple terms, and given a history as to why things are as they are... good read.
the success of Moore’s Law meant engineers didn’t need neural network architectures , and one of the main reasons for slow adoption as been due to the lack of belief ... but now we are reaching the limits of our capability and maintain Moores law is becoming increasingly difficult.
So now people (those who fun out projects and the like) are turning to the benefits of massively parallel processing as opposed to continuing the multiplication of massively serial systems.
A technology that can be taught, not programmed, is more likely to become a truly intelligent system.
For a system to be ‘intelligent’, it must first have some way of recognizing the data and inputs that surround it.
neuromorphic chips and in turn the hardware based ANNs they are part of are ultimately much better at pattern recognition, than existing software ANNs on system architecture that is serial.
- City University, LondonPhD in Computer Science, 2013 - present
- University of ReadingCybernetics, 2012 - 2013
- City University, LondonComputer Science with Games Technology, 2008 - 2012
- Claremont High SchoolHigh School & A Levels - Double ICT, Economics, Maths, 2004 - 2008
- Lucida PLCSupport & Development IT trainee, 2010 - 2011
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