American Journal of Advanced Multidisciplinary Research and Innovation

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Biological Computing and Synthetic Intelligence: Exploring New Models of Computation Inspired by Living Systems

Author(s) Gerry George
Country United States
Abstract The convergence of biology, computation and artificial intelligence is creating new paradigms for understanding and developing intelligent computational systems. Biological computing extends conventional computational thinking by using biological molecules, cells, biochemical reactions and living systems as computational substrates, while synthetic intelligence explores artificial systems capable of exhibiting adaptive, self-organising and intelligence-like behaviours inspired by biological processes. This paper examines emerging models of computation derived from living systems, including DNA computing, molecular computation, cellular computing, neural computation, membrane computing, synthetic gene circuits, organoid-based computation and biohybrid systems. It analyses how biological characteristics such as parallelism, self-organisation, adaptation, evolution, robustness and energy efficiency can inspire alternative approaches to computation. Particular attention is given to the relationship between biological computing and artificial intelligence, including neuromorphic architectures, evolutionary computation, reservoir computing, embodied intelligence and adaptive learning systems. The paper proposes a Biological Computing and Synthetic Intelligence Framework integrating biological substrates, computational abstractions, learning mechanisms, sensing, feedback and intelligent decision-making. Potential applications across healthcare, drug discovery, environmental monitoring, robotics, advanced manufacturing and autonomous systems are discussed. The study also examines major challenges involving reproducibility, scalability, biological variability, ethical considerations, interpretability, computational reliability and integration with conventional digital infrastructure. The paper argues that biological computing should not necessarily be viewed as a replacement for silicon-based computing but as a complementary paradigm capable of addressing specific classes of complex, adaptive and highly parallel computational problems. The convergence of synthetic biology and artificial intelligence could ultimately lead to computational systems that learn, adapt, self-organise and interact with their environments in ways more closely resembling living organisms.
Keywords Biological Computing, Synthetic Intelligence, DNA Computing, Synthetic Biology, Molecular Computation, Cellular Computing, Neuromorphic Computing, Artificial Intelligence, Biohybrid Systems, Living Systems.
Field Engineering
Published In Volume 7, Issue 1, January-February 2025
Published On 2025-02-17
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