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首个器官oid智能(OI)研讨会,以组建一个OI社区。

First Organoid Intelligence (OI) workshop to form an OI community.

作者信息

Morales Pantoja Itzy E, Smirnova Lena, Muotri Alysson R, Wahlin Karl J, Kahn Jeffrey, Boyd J Lomax, Gracias David H, Harris Timothy D, Cohen-Karni Tzahi, Caffo Brian S, Szalay Alexander S, Han Fang, Zack Donald J, Etienne-Cummings Ralph, Akwaboah Akwasi, Romero July Carolina, Alam El Din Dowlette-Mary, Plotkin Jesse D, Paulhamus Barton L, Johnson Erik C, Gilbert Frederic, Curley J Lowry, Cappiello Ben, Schwamborn Jens C, Hill Eric J, Roach Paul, Tornero Daniel, Krall Caroline, Parri Rheinallt, Sillé Fenna, Levchenko Andre, Jabbour Rabih E, Kagan Brett J, Berlinicke Cynthia A, Huang Qi, Maertens Alexandra, Herrmann Kathrin, Tsaioun Katya, Dastgheyb Raha, Habela Christa Whelan, Vogelstein Joshua T, Hartung Thomas

机构信息

Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States.

Department of Pediatrics and Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, San Diego, CA, United States.

出版信息

Front Artif Intell. 2023 Feb 28;6:1116870. doi: 10.3389/frai.2023.1116870. eCollection 2023.

Abstract

The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22-24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.

摘要

大脑可以说是已知最强大的计算系统。它在处理大量信息方面极其高效,能够从噪声中辨别信号、进行自适应并过滤错误信息,而其运行功率仅为20瓦。人类大脑的处理效率、渐进式学习能力和可塑性是任何计算机系统都无法比拟的。干细胞技术的最新进展将细胞培养领域提升到了更高的复杂程度,例如三维(3D)脑类器官的发展,其比传统的单层细胞系统能更好地模拟人类大脑功能。类器官智能(OI)旨在通过将脑类器官与计算机技术连接,利用其天生的生物学能力进行生物计算和合成智能。随着干细胞技术、生物工程和机器学习的最新进展,我们可以探索脑类器官进行计算、存储给定信息(输入)、执行任务(输出)的能力,并研究这如何影响类器官自身的结构和功能连接。此外,了解学习如何在类器官中产生并改变连接模式,有助于揭示人类大脑认知的早期阶段。研究和理解这些概念是一项巨大的多学科工作,需要科学界和公众的参与。因此,2022年2月22日至24日,约翰霍普金斯大学举办了首届类器官智能研讨会,以组建一个类器官智能社区,并为将类器官智能确立为一门新的科学学科奠定基础。会上讨论了类器官智能在革新计算、神经学研究和药物开发方面的潜力,以及其在未来十年发展的愿景和路线图。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ff59/10013972/4d05621b6a10/frai-06-1116870-g0001.jpg

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