Machine Learning Evolution - #infographic
What will it take to make similar inroads in business? Quality training data, digital data processing, and data science expertise. It will also require a lot of human intelligence, such as language-savvy domain experts who refine computable, logically consistent business context to allow logical reasoning. Business leaders will have to take the time to teach machines and incorporate machine intelligence into more processes, starting with narrow domains.
Some in the statistically oriented machine learning research “tribes”—the Connectionists, the Bayesians and the Analogizers, for example —will worry that “human-in-the-loop” methods advocated by the Symbolists aren’t scalable. However, we expect these human-to-machine feedback loops, that blend methods of several tribes, will become a lot more common inside the enterprise over the next few years.