Breakthrough Computers Made From Slime Use Amoeba-like Organisms to Solve Intricate and Costly Problems

Computers based on slime molds may be the next step for solving some of the most advanced and resource-heavy problems that tax the limits of conventional computing. A team at Waseda University developed a new type of computer modeled on living organisms, using amoeba-like slime molds to solve combinatorial optimization problems. The researchers simplified an existing model to make it easier to implement using physical systems, eliminating a major constraint, the volume-conservation law. The new model produced feasible solutions in far fewer iterations than the original model, while increasing the number of cities it could handle from 100 to 180 and demonstrating mathematical equivalence to a recurrent neural network. The paper, "Mathematical Model of the Amoeba-Inspired Combinatorial Optimization Machine for Physical Implementation and Its Equivalence to Recurrent Neural Networks," appeared in Physical Review Research on June 9, 2026.

• The new model uses slime mold dynamics to solve combinatorial optimization problems.
• The model can be implemented using a wide selection of physical materials and phenomena.
• The model produces feasible solutions in fewer iterations and handles more cities than the original model.
• The model is mathematically equivalent to a recurrent neural network.
• The researchers identified alternative candidates for physical implementation, including spintronic devices and photonic circuits.

The findings suggest that slime mold computers could be a valuable approach for solving complex optimization problems in various industries, offering energy efficiency and flexibility. The simplified model allows for the use of different materials and physical phenomena, making it easier to implement in real-world scenarios. The research highlights the potential of using biological systems to solve computational problems, demonstrating the power of nature-inspired approaches in technology.

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