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Artificial Superintelligence: Machine Consciousness Implementation Based On Computational Theory.

EasyChair Preprint no. 3662

11 pagesDate: June 22, 2020


Artificial Super Intelligence or ASI that is more potent and refined than human’s intelligence. ASI is based on the ideas that machines can imitate the human mind, their way of working to the extent that they can even supersede them. As a first step, ASI aims to improve the cognitive abilities of the machines and to achieve this, the ASI will have to become more conscious. In this paper, we define and implement machine consciousness as intelligence deduced by memory containing all information collected by sensors( or senses ) and we have taken Self-Driving Car as “Artificially” created conscious object without any “living” properties. We have implemented Obstacle Detection using deep learning and Object Prediction using Kalman Filter, both relates to environment perception, for Self-Driving Car where it would have a variety of sensory inputs and be aware of its surroundings. The test results are encouraging and Self-Driving Car is therefore “conscious” of the given order since it has obeyed. So, the results show that it is possible to build intelligent machines artificially that are conscious.

Keyphrases: artificial consciousness, artificial superintelligence, image classification, machine consciousness, object tracking

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Poondru Prithvinath Reddy},
  title = {Artificial Superintelligence: Machine Consciousness Implementation  Based  On  Computational Theory.},
  howpublished = {EasyChair Preprint no. 3662},

  year = {EasyChair, 2020}}
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