Living intelligence toward human-level models (HLMs) via Organoid-AI integration

The convergence of brain organoids and artificial intelligence (AI) has driven the development of organoid intelligence (OI), a new paradigm for constructing human-level cognitive models. Brain organoids derived from human stem cells exhibit self-organizing neural networks with dynamic activity and plasticity, offering a biologically based alternative to conventional AI systems. The integration of living networks with computational frameworks enables the design of closed-loop systems that combine the adaptability of biological tissues with the scalability and interpretability of AI. This approach not only provides a novel model for studying human cognition but also opens new pathways for biologically inspired computing. The development of such hybrid systems requires interdisciplinary collaboration among stem cell biology, bioengineering, neuroscience, and machine learning. The long-term goal is to establish biohybrid platforms capable of learning, memory formation, and task-specific computation, thereby redefining our understanding of intelligence and enabling the next generation of neurotechnologies. • Organoid Intelligence (OI) combines brain organoids and AI. • OI creates biologically embodied models for human-level cognition. • Biohybrid platforms can learn, remember, and perform computations. • OI requires interdisciplinary collaboration for development.

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Publication Details

Journal
EngMedicine
Published
2025-10-15
DOI
https://doi.org/10.1016/j.engmed.2025.100106
Citations
2
Primary Topic
Cell Image Analysis Techniques
Type
article
Field-Weighted Citation Impact
3.27
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article

Living intelligence toward human-level models (HLMs) via Organoid-AI integration

Long Bai, Yuxiao Lai, Jianhua Wang, Jiacan Su
2 citations
EngMedicine
Cell Image Analysis Techniques
3.27
article

Living intelligence toward human-level models (HLMs) via Organoid-AI integration

Long Bai, Yuxiao Lai, Jianhua Wang, Jiacan Su
article en
2 citations

Abstract

The convergence of brain organoids and artificial intelligence (AI) has driven the development of organoid intelligence (OI), a new paradigm for constructing human-level cognitive models. Brain organoids derived from human stem cells exhibit self-organizing neural networks with dynamic activity and plasticity, offering a biologically based alternative to conventional AI systems. The integration of living networks with computational frameworks enables the design of closed-loop systems that combine the adaptability of biological tissues with the scalability and interpretability of AI. This approach not only provides a novel model for studying human cognition but also opens new pathways for biologically inspired computing. The development of such hybrid systems requires interdisciplinary collaboration among stem cell biology, bioengineering, neuroscience, and machine learning. The long-term goal is to establish biohybrid platforms capable of learning, memory formation, and task-specific computation, thereby redefining our understanding of intelligence and enabling the next generation of neurotechnologies. • Organoid Intelligence (OI) combines brain organoids and AI. • OI creates biologically embodied models for human-level cognition. • Biohybrid platforms can learn, remember, and perform computations. • OI requires interdisciplinary collaboration for development.

EngMedicineVol. 2(4)
Shanghai University (CN), Wenzhou University (CN), Shanghai Jiao Tong University (CN), XinHua Hospital (CN), Manufacturing Institute (US), Shanghai Institutes for Biological Sciences (CN), Chinese University of Hong Kong, Shenzhen (CN), Shenzhen Institutes of Advanced Technology (CN)
Openalex Percentile: Top 7%
Cell Image Analysis Techniques
3.27
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