Superhuman Intelligence: Mathematical Representation of a System As It Rises Through the Ranks of Intelligence.

EasyChair Preprint 4499

Abstract

Superhuman Intelligence ( SI ) is a stage of intelligence where machines will not only have superhuman strength and speed but also will have superhuman intelligence. SI is based on the idea that machines can imitate the human mind, their way of working to the extent that they can even supersede them. There are different paths of development for achieving Superhuman Intelligence and we have chosen mathematical approach from the first principles of the first seed AI system that will eventually grow up to be superintelligence and analyze how it will behave as it rises through the ranks of intelligence. In this paper, we implement object detection CNN-(R-SVM) combination where an AI algorithm (CNN) passes ‘Spatial Intelligence’ to fast machine learning (SVM) algorithm recursively which is a combination of ‘Spatial and Logical Intelligence’ for solving multiclass problems from large data sets that implements object detection for designing a better AI machine. The test results are encouraging with high accuracy and the model is therefore shown that a Spatial Intelligence is making a better AI when combined with intelligent vector algorithm recursively resulting in very high level of intelligence and if exposed to large data sets on a continuous basis then CNN-(R-SVM) can learn and develop cognitive abilities that will enable to grow up to be superintelligence.

Keyphrases: Recursive SVM, Spatial Intelligence, Superhuman Intelligence, artificial superintelligence, logical intelligence

@booklet{EasyChair:4499,
  author    = {Poondru Prithvinath Reddy},
  title     = {Superhuman Intelligence: Mathematical Representation of a System As It Rises Through the Ranks of Intelligence.},
  howpublished = {EasyChair Preprint 4499},
  year      = {EasyChair, 2020}}