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{{Short description|Field of study in computer science and biology}} |
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{{Orphan|date=January 2024}} |
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'''Organoid intelligence''' ('''OI''') is an emerging [[field of study]] in [[computer science]] and [[biology]] that develops and studies [[biological computing]] using 3D cultures of human brain cells (or brain organoids) and brain-machine interface technologies.<ref>{{Cite journal |last1=Smirnova |first1=Lena |last2=Caffo |first2=Brian S. |last3=Gracias |first3=David H. |last4=Huang |first4=Qi |last5=Morales Pantoja |first5=Itzy E. |last6=Tang |first6=Bohao |last7=Zack |first7=Donald J. |last8=Berlinicke |first8=Cynthia A. |last9=Boyd |first9=J. Lomax |last10=Harris |first10=Timothy D. |last11=Johnson |first11=Erik C. |last12=Kagan |first12=Brett J. |last13=Kahn |first13=Jeffrey |last14=Muotri |first14=Alysson R. |last15=Paulhamus |first15=Barton L. |date=2023-02-28 |title=Organoid intelligence (OI): the new frontier in biocomputing and intelligence-in-a-dish |journal=Frontiers in Science |volume=1 |doi=10.3389/fsci.2023.1017235 |issn=2813-6330 |doi-access=free}}</ref> Such technologies may be referred to as OIs. |
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{{Cleanup bare URLs|date=January 2024}} |
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'''Organoid Intelligence (OI)''' is an emerging [[field of study]] in [[computer science]] and [[biology]] that develops and studies [[biological computing]] using 3D cultures of human brain cells (or brain organoids) and brain-machine interface technologies.<ref>https://www.frontiersin.org/journals/science/articles/10.3389/fsci.2023.1017235/full</ref> Such technologies may be referred to as OIs. |
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==Differences with non-organic computing== |
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As opposed to traditional non-organic silicon-based approaches, OI seeks to use lab-grown [[cerebral organoids]] to serve as "biological hardware." Scientists hope that such organoids can provide faster, more efficient, and more powerful computing power than regular silicon-based computing and AI while requiring only a fraction of the energy. However, while these structures are still far from being able to think like a regular human [[brain]] and do not yet possess strong computing capabilities, OI research currently offers the potential to improve the understanding of brain development, learning and memory, potentially finding treatments for [[neurological disorders]] such as [[dementia]].<ref>https://www.frontiersin.org/journals/science/article-hubs/organoid-intelligence-a-new-biocomputing-frontier</ref> |
As opposed to traditional non-organic silicon-based approaches, OI seeks to use lab-grown [[cerebral organoids]] to serve as "biological hardware." Scientists hope that such organoids can provide faster, more efficient, and more powerful computing power than regular silicon-based computing and AI while requiring only a fraction of the energy. However, while these structures are still far from being able to think like a regular human [[brain]] and do not yet possess strong computing capabilities, OI research currently offers the potential to improve the understanding of brain development, learning and memory, potentially finding treatments for [[neurological disorders]] such as [[dementia]].<ref>{{Cite web |title=Organoid intelligence: a new biocomputing frontier |url=https://www.frontiersin.org/journals/science/article-hubs/organoid-intelligence-a-new-biocomputing-frontier |url-status=live |archive-url=https://web.archive.org/web/20230623121539/https://www.frontiersin.org/journals/science/article-hubs/organoid-intelligence-a-new-biocomputing-frontier |archive-date=2023-06-23 |access-date=2024-01-11 |website=Frontiers |language=en}}</ref> |
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Thomas Hartung,<ref>{{Cite web |title=Thomas Hartung {{!}} Johns Hopkins {{!}} Bloomberg School of Public Health |url=https://publichealth.jhu.edu/faculty/2308/thomas-hartung |access-date=2024-03-04 |website=publichealth.jhu.edu |language=en}}</ref> a professor from [[Johns Hopkins University]], argues that "while silicon-based computers are certainly better with numbers, brains are better at learning." Furthermore, he claimed that with "superior learning and storing" capabilities than [[Artificial Intelligence|AIs]], being more energy efficient, and that in the future, it might not be possible to add more [[transistors]] to a single [[computer chip]], while brains are wired differently and have more potential for storage and computing power, OIs can potentially harness more power than current computers.<ref>{{Cite web |last=Hollender |first=Liad |title=Scientists unveil plan to create biocomputers powered by human brain cells |url=https://www.frontiersin.org/news/2023/02/28/brain-organoids-intelligence-biocomoputing-hartung |url-status=live |archive-url=https://web.archive.org/web/20240110193007/https://www.frontiersin.org/news/2023/02/28/brain-organoids-intelligence-biocomoputing-hartung |archive-date=2024-01-10 |access-date=2024-01-11 |website=Frontiers}}</ref> |
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== Bioinformatics in OI == |
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| ⚫ | Brain-inspired computing hardware aims to emulate the structure and working principles of the brain and could be used to address current limitations in artificial intelligence technologies. However, brain-inspired silicon chips are still limited in their ability to fully mimic brain function, as most examples are built on digital electronic principles. One study performed OI computation (which they termed |
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OI generates complex biological data, necessitating sophisticated methods for processing and analysis.<ref>{{Cite journal |last1=Kagan |first1=Brett J |last2=Kitchen |first2=Andy C |last3=Tran |first3=Nhi T |last4=Habibollahi |first4=Forough |last5=Khajehnejad |first5=Moein |last6=Parker |first6=Bradyn J |last7=Bhat |first7=Anjali |last8=Rollo |first8=Ben |last9=Razi |first9=Adeel |last10=Friston |first10=Karl J |date=2022-12-07 |title=In vitro neurons learn and exhibit sentience when embodied in a simulated game-world |journal=Neuron |volume=110 |issue=23 |pages=3952–3969.e8 |doi=10.1016/j.neuron.2022.09.001 |issn=1097-4199 |pmc=9747182 |pmid=36228614}}</ref> [[Bioinformatics]] provides the tools and techniques to decipher raw data, uncovering the patterns and insights. |
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==Intended functions== |
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| ⚫ | While researchers are hoping to use OI and biological computing to complement traditional silicon-based computing, there are also questions about the ethics of such an approach. Examples of such ethical issues include OIs gaining consciousness and sentience as [[organoids]] and the question of the relationship between a stem cell donor (for growing the organoid) and the respective OI system.<ref> |
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| ⚫ | Brain-inspired computing hardware aims to emulate the structure and working principles of the brain and could be used to address current limitations in artificial intelligence technologies. However, brain-inspired silicon chips are still limited in their ability to fully mimic brain function, as most examples are built on digital electronic principles. One study performed OI computation (which they termed ''Brainoware'') by sending and receiving information from the brain organoid using a high-density multielectrode array. By applying spatiotemporal electrical stimulation, nonlinear dynamics, and fading memory properties, as well as unsupervised learning from training data by reshaping the organoid functional connectivity, the study showed the potential of this technology by using it for [[speech recognition]] and nonlinear equation prediction in a reservoir computing framework.<ref>{{cite journal | url=https://www.nature.com/articles/s41928-023-01069-w | doi=10.1038/s41928-023-01069-w | title=Brain organoid reservoir computing for artificial intelligence | date=2023 | last1=Cai | first1=Hongwei | last2=Ao | first2=Zheng | last3=Tian | first3=Chunhui | last4=Wu | first4=Zhuhao | last5=Liu | first5=Hongcheng | last6=Tchieu | first6=Jason | last7=Gu | first7=Mingxia | last8=MacKie | first8=Ken | last9=Guo | first9=Feng | journal=Nature Electronics | volume=6 | issue=12 | pages=1032–1039 | s2cid=266278255 }}</ref> |
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== Ethical concerns == |
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| ⚫ | While researchers are hoping to use OI and biological computing to complement traditional silicon-based computing, there are also questions about the ethics of such an approach. Examples of such ethical issues include OIs gaining consciousness and sentience as [[organoids]] and the question of the relationship between a stem cell donor (for growing the organoid) and the respective OI system.<ref>{{cite journal | pmid=37009773 | date=2023 | last1=Smirnova | first1=L. | last2=Morales Pantoja | first2=I. E. | last3=Hartung | first3=T. | title=Organoid intelligence (OI) - the ultimate functionality of a brain microphysiological system | journal=Altex | volume=40 | issue=2 | pages=191–203 | doi=10.14573/altex.2303261 | doi-access=free }}</ref> |
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Enforced amnesia and limits on duration of operation without memory reset have been proposed as a way to mitigate the potential risk of [[artificial consciousness|silent suffering]] in brain organoids.<ref name="aiamnesia">{{Cite journal| last1 = Tkachenko| first1=Yegor|year=2024|title=Position: Enforced Amnesia as a Way to Mitigate the Potential Risk of Silent Suffering in the Conscious AI|journal=Proceedings of the 41st International Conference on Machine Learning|url= https://icml.cc/virtual/2024/poster/33138 |access-date=2024-06-11|publisher=PMLR|language=en}}</ref> |
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==References== |
==References== |
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{{Reflist}} |
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{{Bioinformatics}} |
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{{Branches of biology}} |
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{{Computer science}} |
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{{Computational science}} |
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{{Evolutionary computation}} |
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[[Category:Artificial intelligence]] |
[[Category:Artificial intelligence]] |
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Latest revision as of 19:42, 24 June 2024
Organoid intelligence (OI) is an emerging field of study in computer science and biology that develops and studies biological computing using 3D cultures of human brain cells (or brain organoids) and brain-machine interface technologies.[1] Such technologies may be referred to as OIs.
Differences with non-organic computing
[edit]As opposed to traditional non-organic silicon-based approaches, OI seeks to use lab-grown cerebral organoids to serve as "biological hardware." Scientists hope that such organoids can provide faster, more efficient, and more powerful computing power than regular silicon-based computing and AI while requiring only a fraction of the energy. However, while these structures are still far from being able to think like a regular human brain and do not yet possess strong computing capabilities, OI research currently offers the potential to improve the understanding of brain development, learning and memory, potentially finding treatments for neurological disorders such as dementia.[2]
Thomas Hartung,[3] a professor from Johns Hopkins University, argues that "while silicon-based computers are certainly better with numbers, brains are better at learning." Furthermore, he claimed that with "superior learning and storing" capabilities than AIs, being more energy efficient, and that in the future, it might not be possible to add more transistors to a single computer chip, while brains are wired differently and have more potential for storage and computing power, OIs can potentially harness more power than current computers.[4]
Bioinformatics in OI
[edit]OI generates complex biological data, necessitating sophisticated methods for processing and analysis.[5] Bioinformatics provides the tools and techniques to decipher raw data, uncovering the patterns and insights.
Intended functions
[edit]Brain-inspired computing hardware aims to emulate the structure and working principles of the brain and could be used to address current limitations in artificial intelligence technologies. However, brain-inspired silicon chips are still limited in their ability to fully mimic brain function, as most examples are built on digital electronic principles. One study performed OI computation (which they termed Brainoware) by sending and receiving information from the brain organoid using a high-density multielectrode array. By applying spatiotemporal electrical stimulation, nonlinear dynamics, and fading memory properties, as well as unsupervised learning from training data by reshaping the organoid functional connectivity, the study showed the potential of this technology by using it for speech recognition and nonlinear equation prediction in a reservoir computing framework.[6]
Ethical concerns
[edit]While researchers are hoping to use OI and biological computing to complement traditional silicon-based computing, there are also questions about the ethics of such an approach. Examples of such ethical issues include OIs gaining consciousness and sentience as organoids and the question of the relationship between a stem cell donor (for growing the organoid) and the respective OI system.[7]
Enforced amnesia and limits on duration of operation without memory reset have been proposed as a way to mitigate the potential risk of silent suffering in brain organoids.[8]
References
[edit]- ^ Smirnova, Lena; Caffo, Brian S.; Gracias, David H.; Huang, Qi; Morales Pantoja, Itzy E.; Tang, Bohao; Zack, Donald J.; Berlinicke, Cynthia A.; Boyd, J. Lomax; Harris, Timothy D.; Johnson, Erik C.; Kagan, Brett J.; Kahn, Jeffrey; Muotri, Alysson R.; Paulhamus, Barton L. (2023-02-28). "Organoid intelligence (OI): the new frontier in biocomputing and intelligence-in-a-dish". Frontiers in Science. 1. doi:10.3389/fsci.2023.1017235. ISSN 2813-6330.
- ^ "Organoid intelligence: a new biocomputing frontier". Frontiers. Archived from the original on 2023-06-23. Retrieved 2024-01-11.
- ^ "Thomas Hartung | Johns Hopkins | Bloomberg School of Public Health". publichealth.jhu.edu. Retrieved 2024-03-04.
- ^ Hollender, Liad. "Scientists unveil plan to create biocomputers powered by human brain cells". Frontiers. Archived from the original on 2024-01-10. Retrieved 2024-01-11.
- ^ Kagan, Brett J; Kitchen, Andy C; Tran, Nhi T; Habibollahi, Forough; Khajehnejad, Moein; Parker, Bradyn J; Bhat, Anjali; Rollo, Ben; Razi, Adeel; Friston, Karl J (2022-12-07). "In vitro neurons learn and exhibit sentience when embodied in a simulated game-world". Neuron. 110 (23): 3952–3969.e8. doi:10.1016/j.neuron.2022.09.001. ISSN 1097-4199. PMC 9747182. PMID 36228614.
- ^ Cai, Hongwei; Ao, Zheng; Tian, Chunhui; Wu, Zhuhao; Liu, Hongcheng; Tchieu, Jason; Gu, Mingxia; MacKie, Ken; Guo, Feng (2023). "Brain organoid reservoir computing for artificial intelligence". Nature Electronics. 6 (12): 1032–1039. doi:10.1038/s41928-023-01069-w. S2CID 266278255.
- ^ Smirnova, L.; Morales Pantoja, I. E.; Hartung, T. (2023). "Organoid intelligence (OI) - the ultimate functionality of a brain microphysiological system". Altex. 40 (2): 191–203. doi:10.14573/altex.2303261. PMID 37009773.
- ^ Tkachenko, Yegor (2024). "Position: Enforced Amnesia as a Way to Mitigate the Potential Risk of Silent Suffering in the Conscious AI". Proceedings of the 41st International Conference on Machine Learning. PMLR. Retrieved 2024-06-11.
