Authors : Dr. Alhakimou Diallo

Volume/Issue : Volume 11 - 2026, Issue 1 - January

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Google Scholar : https://tinyurl.com/42yhx3nn

Scribd : https://tinyurl.com/35frubrw

DOI : https://doi.org/10.38124/ijisrt/26jan640

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

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Abstract : The question of whether machines can surpass human intelligence has long intrigued scientists. Linear algorithms on single-processor systems have inherent limitations that constrain performance. Inspired by the human brain, parallel algorithms and neuronal network architectures offer a promising path toward next-generation artificial intelligence (AI). This article explores the theoretical foundations, biological inspiration, and algorithmic parallelism of AI, outlining practical applications, ethical considerations, and future prospects. The integration of parallel computation with bio-inspired architectures may enable machines to achieve unprecedented levels of efficiency, intelligence, and adaptability.

Keywords : Artificial Intelligence, Parallelism ; Neuron Networking.

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