An Assessment on the Feasibility of Describing a Framework of Time for Artificial General Intelligence
There is an inherent need for the field of Artificial General Intelligence to begin incorporating principles of non-local science in their approach to knowledge representation for the pursuit towards general intelligence. Prevailing theories and concepts are unable to approach a proper implementation of Artificial General Intelligence due to the adoption of concepts that are considered outdated in current scientific terms when it comes to describing time and space. Current scientific progress has increasingly viewed the universe as whole and non-local. The Bhagavata Purana provides a robust framework to encompass various spatial and non-spatial as well as temporal features of reality required to describe non-local sciences. This research attempts to assess the extent towards which the Bhagavata Purana can reconcile the various issues in contemporary scientific theory within the context of data science. Through review of Newton’s Principia Mathematica, Immanuel Kant’s Critique of Pure Reason, various academic papers regarding topics of space and time, various reference frames used in the prevailing theories of time and space for perceiving reality is compared to the Bhagavata Purana. It aims to define a suitable methodology to describe general intelligence in the field of data science. The research concludes with a recommendation for further research through the implementation of an AGI prototype using a universal database that allows multiple domain knowledge representation in various data models. This is novel research as it aims to create a new ontological schema of time that is able to solve the prevailing issue of developing a truly dynamic time ontology for Artificial General Intelligence in Decision Support Systems by providing an internal intuition of time for machines.
This work was fully funded by Sumeru Corporation
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