Researchers developed a novel multicellular artificial neural network architecture using engineered bacterial cells. These artificial networks can solve computational problems by mimicking natural neural systems, demonstrating potential applications in biotechnology. The study explores how combining bacterial cells in specific configurations enables problem-solving abilities similar to neural networks, opening avenues for creating biologically based computational systems.
https://www.nature.com/articles/s41589-024-01711-4
The development of a modular multicellular system composed of engineered bacterial cells designed to solve computational problems. These bacterial cells, modeled as “artificial neurosynapses,” can form a neural network-like structure. This system demonstrates computational abilities, such as performing full adder and subtractor functions, identifying prime numbers between 0 and 9, and determining whether letters from A to L are vowels. Additionally, the system can solve complex problems, like calculating the maximum number of pie pieces from a set number of straight cuts. The findings highlight potential applications in biocomputing and synthetic biology.
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