Despite some massive strides over the past few years where machine learning (ML) even assisted and enhanced the core search engine algorithm of Google, we have witnessed its use to just a limited variety of applications. In 2017, machine learning and AI is set to encompass more domains. With technologies such as neural networks, deep learning and natural-language processing, experts predict that more advanced systems will come into play that comprehend, learn, forecast, adapt and potentially function autonomously. As the systems learn, forecast and adapt, they can bring a change in future behavior, which in turn would pave the way for more intelligent programs and devices being created. Such a change can be attributed to the blend of advanced algorithms and programs, huge data sets that feed them, and all-embracing parallel processing power.
By leveraging AI and machine learning, the banking sector can create replica of real-time transactions as well as predictive models of operations based on how likely they are to be fraudulent. For businesses trying to get ahead in the race of digital innovation, AI and machine learning could help examine various business scenarios (including even one or two high-impact scenarios) by driving precise and specific business value.
Even consumer applications can benefit from this technology by considering prior purchase history to offer better recommended products, which would improve the app’s user experience with time.