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14 SMT007 MAGAZINE I SEPTEMBER 2018 Platform AI is expected to intake data through ML to analyze data, create a model, and make deci- sions based on that data. AI is also expected to create model-based learning and modify it with new data. It should be a system that is driven by data and will offer the ability to learn and react based on a generalized strategy-for- learning by using algorithmic models. By so doing, new insights are beneficially generated without relying on rules-based computing pro- grams. The ability to incessantly chew through any amount of data and unlimited combinations of variables and parse data, capture knowledge, and make a deterministic or predictive mod- el makes ML surpass human capacity. Being unconstrained by preset assumptions of sta- tistics can also allow ML to surpass human analysts by making predictions with higher degrees of accuracy. As a result, wherever there are too many potential combinations and too much com- plexity, ML can be a potent tool. And an AI system, whether it emulates human perfor- mance or replaces humans on the execution of routine or non-routine tasks, can facilitate decision-making and process automation. Another beauty is that the machine is sleep- less and works 24/7. Machines are free of time zones and independent of geographical terri- tories in performing data collection, aggrega- tion, algorithms, and processing power, which has enabled AI and will continue to make breakthroughs. A variety of applications have employed AI to different extents, ranging from financial services to business operations and military prowess. In business, AI and ML can apply to every function of doing business. They are going to play an impactful role in business intelligence and analytic solutions by creating the expertise to rapidly transform learned data into action to create competitive advantages. AI will also help IoT data analyses in data preparation and discovery, predictive analytics, and geo-

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