Exponential productivity through optimization of knowledge yield

AI systems create value by converting human knowledge to digital form that can then be converted to other forms of energy, including kinetic. At the atomic level knowledge created by human intelligence and augmented by machine learning can be viewed and expressed as an extension of relativity discovered by Einstein more than a century ago. 

“Our concepts and laws of space and time can only claim validity insofar as they stand in a clear relation to our experiences; and that experience could very well lead to the alteration of these concepts and laws. By a revision of the concept of simultaneity into a more malleable form, I thus arrived at the special theory of relativity."- Albert Einstein[i]

When knowledge is converted from neurons in the brain to digital form to be processed and exchanged over computer networks the energy can then be measured in many ways. For example, we can express the net amount of work within a system that equals the change in the quantity. We can also measure the total energy and time-evolution of a distributed network and apply equations to describe the changes in the system over time from quantum effects.[ii]

The importance of relativity becomes apparent when considering knowledge converted to AI is a form of focused energy that offers potential to be harnessed for any endeavor, which can be measured in BTU, joule, and other SI units.[iii]  A similar process can be used to measure quality, performance, productivity, financial and other values in systems that have the capacity to collect the information necessary to assign accurate values.... go to Cognitive World to view entire article.

[i]A. Einstein,Princeton Press Volume 2: “The Swiss Years: Writings, 1900-1909” #264https://einsteinpapers.press.princeton.edu/vol2-doc/300

[ii]M. Montgomery, “Yield Management of Knowledge” 15 March, 2018 (unpublished)

[iii]A. Einstein, “Does the Inertia of a Body Depend on its Energy-Content?” 27 September, 1905

 https://www.fourmilab.ch/etexts/einstein/E_mc2/e_mc2.pdf