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The idea that computers (and hence computing) can be provided as a utility, like electricity or telephony, dates back to the late 1970s [28].
It can be expected that all extensions will require expensive computation, but this computing can be made possible if combinatorial mathematics, graphical models, and machine learning are incorporated into closed forms of parameter estimation.
Whether for pay or play, distributed computing can be found in computer labs or family dens.
Recently, various works have highlighted that reservoir computing can be a candidate computational approach to describe the nature of cortical encoding (Wang 2008; Rigotti et al. 2010; Dominey 2013; Hoerzer et al. 2014).
This "blind quantum computing" can be carried out without a cloud computer ever knowing what the data is.
In particular, the utilization of approximate computing can be utilized to reduce the amount of computation required for the calculus of the (auto) correlation value.
The number of scientific publications presenting methods, processes and tools for the cloud is constantly increasing as researchers investigate how cloud computing can be used to promote advances in several areas of computer science (da Silva and Lucredio 2012).
Computing can be a hard road for small businesses.
Once a definition of cloud has been decided upon, the real arguments for and against cloud computing can be addressed.
Using special "partitioning" software, these workhorses of computing can be turned into a virtual collection of thousands of Linux servers.
Other relics of computing can be found in the building, an hour's drive north of New York City.
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