CIO’s Avoid Defining A.I.
Chief Information Officers concentrate on getting hands-on with artificial intelligence and machine learning, not the ‘semantics’.
For many heads of technology, quantifying the definition of Artificial Intelligence is largely an unnecessary exercise. It is more useful to consider: Will the current methods of machine learning and artificial intelligence present a new advent in problem solving and enabling the architecture for new products and services. At the core, technology leaders are focussed on evolution and improvement through iteration, enabled by AI and ML, rather than defining the process that covers manipulating statistical analysis, algorithms and predictive modelling for business gains.
The wider question is also posed: Are we incorrectly amassing all of the data, or is the misguided amassing and interpreting of data the fundamental nature of what AI and machine learning will always present with.
Many chief technology officers balk at defining the term. Also, an ontological debate will divert you from the macro view, which is the real business value that new and progressive technologies, such as artificial intelligence and machine learning can create.
Day-to-day you use your technology toolbox, which includes artificial intelligence technologies, to solve the business problems directly in front of you. You’ve got a set of tools and a set of algorithms that you can apply to problems and result in the creation of solutions. Whether they’re described under the term AI and machine learning is not worth pondering.
Is a 'data lake' an optimum solution? Unlikely, as queries will be high cost on untransformed data in lakes. For ef… https://t.co/oudBNX3aRj