Superintelligent digital brains: distinct activation functions implying distinct artificial neurons

Jamilu Auwalu Adamu

doi:10.1117/12.2566289

20 August 2020 Superintelligent digital brains: distinct activation functions implying distinct artificial neurons

Jamilu Auwalu Adamu

Proceedings Volume 11469, Emerging Topics in Artificial Intelligence 2020; 114691L (2020) https://doi.org/10.1117/12.2566289
Event: SPIE Nanoscience + Engineering, 2020, Online Only

Conference Poster

Abstract

Currently, we are dealing with a very limited set of activation functions such as Sigmoid, ReLu, Leaky ReLu among others. These activation functions used in the existing digital brain neural network systems are chosen using assumption with the help of “trial and error” approach. However, they do not ethically and appropriately establish any relationship with the referenced AI datasets. Jamilu (2019) proposed that a digital brain should have at least 2000 to 100 billion distinct activation functions implying distinct artificial neurons satisfies Jameel’s criterion(s) for it to normally mimic the human brain. The objectives of this paper are to propose a theorem called “Digital Brain Completeness Theorem”, “superintelligent digital brain neural network systems” and why it is tremendously important to have an extremely huge distinct activation functions implying distinct artificial neurons in a digital brain just like in the case of its counterpart for it to function rationally.

Conference Presentation

Citation Download Citation

Jamilu Auwalu Adamu "Superintelligent digital brains: distinct activation functions implying distinct artificial neurons", Proc. SPIE 11469, Emerging Topics in Artificial Intelligence 2020, 114691L (20 August 2020); https://doi.org/10.1117/12.2566289

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