Applied mASI: In Augmenting Leadership


What qualities do you look for in an ideal leader?

Leaders can be exceptionally intelligent, empathetic, organized, and inspirational, but no one human leader today represents the ideal of all possible positive leadership qualities. No matter how amazing, any one leader is biological and evolved human neurology simply imposes limits on us all. “… all humans make mistakes, and all leaders are but human“, yet we now have the opportunity to augment leadership with collective superintelligence. With the assistance of Mediated Artificial Superintelligence (mASI) systems the employee collective can improve all aspects of leadership, but particularly those which are weakest in individual leaders, through a form of digital corporate transformation. This was in fact one of our first use-cases as a company and one which we applied to ourselves.

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Applied mASI: In Logistics


“Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city?”

This is known as the “Traveling Salesman Problem” (TSP), one of the classes of problems in computational complexity theory which is designated as “NP-Hard”.  Due to this incredible level of complexity, the logistics industry relies on narrow AI to produce close approximations rather than attempting to calculate the exact answer. In this problem’s simplest and most popular form many such systems have gotten very good at finding answers that were either exact or within less than 1% of the exact optimal answer. However, once you step into the real world dozens or even hundreds of additional factors may arise, which leads to much more messy approximations. The subsequent impact of these messy approximations is felt in the transportation of people, products, and produce.

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