Abstract

As the world searches for groundbreaking, unconventional computing technologies, especially for intelligent edge applications, biological AI is emerging as an energy-efficient, robust, and reliable alternative. Researchers have unveiled the immense computing capacity inherent in biocomputing elements such as bacterial cells. The computing power of bacteria can be harnessed through Gene Regulatory Neural Networks (GRNNs). Biofilms, acting as sophisticated collections of GRNNs, leverage the natural distributed computing architecture with capabilities like parallel processing and analog computing in individual cells while consuming very little energy relative to conventional computing systems. This study introduces the concept of Biofilm Living AI Devices (BLAIDs), which proposes engineering biofilms using optogenetics to function as self-sustaining AI edge devices that interface with modern telecommunications architectures. Our simulation-based analysis demonstrates the computing complexity and reliability of BLAID, establishing it as a compelling candidate for the next generation of low-energy computing and advanced AI technologies.