Overview of Emerging Biological Computational Framework for Olfactory Studies Utilizing Contextual Technobiomedical Engineering

Organoid intelligence (OI), the next paradigm of intelligence, draws inspiration from the biological learning of organs. On the other hand, artificial intelligence (AI) draws its inspiration only from the cognitive processes of the brain. While taking ethical and technological limitations into account, biological learning helps to conceptualize, accept, and apply them. Just as AI helped to make supercomputers possible, OI may help create biocomputers. Even though AI has increased the capabilities of technology to unimaginable heights, it still appears immature and is steadily moving toward cognitive computing to push the envelope even farther. In contrast to AI, OI is a new multidisciplinary computer area that attempts to be more approachable. OI has the ability to produce novel biocomputers, such as organoids, that use parts derived from live organisms to perform computational tasks. Organoids, such as human nasal organoids, are microscopic tissue cultures made from stem cells that mimic some of the functions of real organs. Although they have been used for many different purposes, including drug discovery and illness modeling, scientists are only now beginning to explore their potential for biological information processing.

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Publication Details

Published
2024-11-29
DOI
https://doi.org/10.1109/idicaiei61867.2024.10842781
Citations
2
Primary Topic
Advanced Chemical Sensor Technologies
Type
article
Field-Weighted Citation Impact
0.37
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article

Overview of Emerging Biological Computational Framework for Olfactory Studies Utilizing Contextual Technobiomedical Engineering

Shiv Nath Chaudhri
2 citations
Advanced Chemical Sensor Technologies
0.37
article

Overview of Emerging Biological Computational Framework for Olfactory Studies Utilizing Contextual Technobiomedical Engineering

Shiv Nath Chaudhri
article en
2 citations

Abstract

Organoid intelligence (OI), the next paradigm of intelligence, draws inspiration from the biological learning of organs. On the other hand, artificial intelligence (AI) draws its inspiration only from the cognitive processes of the brain. While taking ethical and technological limitations into account, biological learning helps to conceptualize, accept, and apply them. Just as AI helped to make supercomputers possible, OI may help create biocomputers. Even though AI has increased the capabilities of technology to unimaginable heights, it still appears immature and is steadily moving toward cognitive computing to push the envelope even farther. In contrast to AI, OI is a new multidisciplinary computer area that attempts to be more approachable. OI has the ability to produce novel biocomputers, such as organoids, that use parts derived from live organisms to perform computational tasks. Organoids, such as human nasal organoids, are microscopic tissue cultures made from stem cells that mimic some of the functions of real organs. Although they have been used for many different purposes, including drug discovery and illness modeling, scientists are only now beginning to explore their potential for biological information processing.

Datta Meghe Institute of Higher Education and Research (IN)
Openalex Percentile: Top 41%
Advanced Chemical Sensor Technologies
0.37
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Overview of Emerging Biological Computational Framework for Olfactory Studies Utilizing Contextual Technobiomedical Engineering — Shiv Nath Chaudhri · (2024) | TGRS Research Map | TGRS