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Today, Artificial Intelligence (AI) is being employed by financial companies around the world to advise customers on financial decisions that they should make; digital assistants are finding their ways onto our smartphones. Another important area where AI can be successfully implemented is in data analysis of specifically big data. The biggest barrier to this in the past has been the requirement of computational capacity, and until recently, large-scale cluster computing has always been termed as being too costly and time-consuming. At a time when Nanoseconds are the bar quick processing, today’s CPUs and GPUs are able to process huge amounts of data at capacity in real-time significantly faster than what was previously thought possible.