Society is entering into a new era of technology that is dominated by artificial intelligence (AI). While conventional AI has been inspired from biology, recent studies suggest that biological cells themselves can be directly connected to computers as AI machines to harness the intelligence inherent in living cells. This project aims to discover natural AI structures in bacterial gene regulatory networks that can be leveraged for computing applications. This project seeks to develop a bio-hybrid computing system, where the gene regulatory networks of bacteria are used to perform AI computing. The team of researchers will establish an electrical - chemical - electrical communication mechanism, where information signals from a computer will stimulate bacterial gene regulatory networks to perform chemical-based computing. The output of this network will produce electrical signals that can be interpreted by a computer. By offloading computing to the bacteria, the impact of this research may transform the design of energy-efficient computing architectures with novel implications for healthcare and environmental sensing. This research will enhance both the PI and Co-PI's curriculums in Molecular and Nanoscale Communications and Environmental Biotechnology. In addition, this work will support multidisciplinary trainee-training to prepare the biotechnology workforce. Using the electroactive bacterium, Shewanella oneidensis, the project seeks to utilize gene regulatory artificial