Machine learning and Artificial Intelligence brings in transformations through practically every domain and industry in an unprecedented way. Fueled by ever increasing computing resources, evolution of faster algorithms, developments in machine learning backed by vast amounts of data—AI is bringing rapid changes the existing business processes.
It is important that an AI system is engineered to interpret and demonstrate a general intelligence as humans, demonstrate a level of intelligence that is not specific to one category of tasks or at least be able to generalize those specifics, and relate those understandings in the context of real world tasks, issues and cases.
Ability to balance this interpretation in the right manner enables an AI system to deal with new situations which are very different that the ones system has encountered earlier.
The “intelligence” in the data
Companies are striving to bring transformations, areas such as operations optimization, fraud detection and prevention, and financial performance improvements are becoming more and more focused, and one of the key factors that’s drives these initiatives to success is the capability to drive them with intelligent data from trusted source of repositories. As for any other digital strategies organizations build, data is pivotal to success of artificial intelligence strategy. Said differently, AI systems can only be as intelligent as the data they deal with.