GeoSpock: making extreme data easy
Steve Marsh, founder and CTO of GeoSpock, talks to Sam Fenwick about how extreme-scale data platforms can be used to allow humans and AI to make sense of smart city sensors and improve our society
February’s big interview briefly discussed the lessons we can learn from biology and apply to smart city projects. Here we explore another link between the two as Steve Marsh, founder and CTO of GeoSpock, began his career in academia where he worked to develop a custom supercomputer to carry out real-time simulation of brain-scale neural networks. As he and his team were up against heavyweights like IBM, whose resources permitted a brute force approach, Marsh chose a different strategy, seeing the challenge as a communication problem. Eventually they were able to simulate one second of neural activity in one second of computer time, compared with two weeks for the competition.
Marsh then tweaked the algorithms to allow the simulation to run on commodity hardware, but then hit a brick wall. Enamoured by the rise of smartphones and their GPS functionality, Marsh expected that the world would make a “monumental shift” to machine-generated extreme-scale data, the majority of which would come from physical sensors, and if all this data could be understood, we might use it to change the physical world for the better.
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