Living intelligence toward human-level models (HLMs) via Organoid-AI integration
Year: 2025
Type: article
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.
Source: EngMedicine
Authors: Long Bai, Jianhua Wang, Yuxiao Lai, Jiacan Su
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,300
OpenAlex ID: W4415200697