Online ISSN 2653-4983
JOURNAL of MULTISCALE NEUROSCIENCE
How to Cite This article
Shantipriya Parida (2024). Multiscalar brain adaptability in AI systems. Journal of Multiscale Neuroscience, 3(4): 246
DOI: https://doi.org/10.56280/1663524979
Multiscalar brain adaptability in AI systems
Publication: Journal of Multiscale Neuroscience DOI: https://doi.org/10.56280/1663524979
EDITORIAL to SPECIAL ISSUE
Abstract
The advent of Generative AI has transformed creative and analytical landscapes, leveraging vast datasets to produce sophisticated outputs with remarkable efficiency. Despite these advancements, human judgment and adaptability remain indispensable for navigating complex, dynamic, and context-sensitive environments. This editorial explores the interplay between human cognition, AI, and quantum biological consciousness, emphasizing how the brain’s multiscalar adaptability can inform the development of conscious AI systems.
At the core of this exploration is Artificial General Intelligence (AGI), which seeks to emulate human cognitive flexibility, reasoning, and learning within computational paradigms. While AGI excels in predefined tasks, it falters in managing uncertainty and unpredictability. Strong Artificial Intelligence (SAI), by contrast, envisions systems capable of mind-like processes—managing uncertainty and anticipating unexpected events. Achieving SAI requires a deeper understanding of the brain’s adaptability, spanning multiple scales from synaptic plasticity to precognitive consciousness ...
Keywords: Conscious AI, Generative AI, Strong AI, Deep Learning, Brain Adaptability, Multiscale Brain
Conflict of Interest
The author declares no conflict of interest
Copyright: © 2024 The Author(s). Published by Neural Press.
This is an open access article distributed under the terms and conditions of the CC BY 4.0 license.
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, Neural Press™ or the editors, and the reviewers. Any product that may be evaluated in this article, or claim that made by its manufacturer, is not guaranteed or endorsed by the publisher.