The Importance of Data for Training Intelligent Devices
In the past decade there has been a big effort in implementing automatic systems that can be used in most environments and are able to decrease human work and therefore, human errors. Most of these systems are devoted to applications where the problem faced cannot be clearly described by a set of finite steps (algorithmically), and, in the cases when it can described algorithmically, the computational complexity required to perform one or more of the steps is prohibitive. Those problems, in computer science language are called NP-complete and NP-hard problems, where NP indicates that the problem has a Non Polynomial solution either in terms of computational time or in terms of memory occupancy, or both.
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