Smarter Measurement, Smarter Computing: New Algorithm Reveals How Efficiently Bacteria and Computers Process Information
How much information can bacteria actually process while scanning their environment in search of food? That question was central to the research of Manuel Reinhardt, who developed an innovative algorithm to find out. The result: a new computational method that not only provides crucial insights into biological systems but also holds great promise for the future of energy-efficient computing.
Reinhardt designed an algorithm called Path Weight Sampling, which calculates with exceptional precision how quickly information flows through a system. Until now, scientists relied on rough estimates and approximations, often without knowing how accurate they really were. Reinhardt’s method breaks through that uncertainty and now offers the most precise measuring tool available.
But the algorithm’s potential goes far beyond the world of bacteria. Any system that processes information — from cells to computers and AI — can be analyzed using this method. And that’s urgently needed, as modern information processing, such as in data centers or artificial intelligence, consumes massive amounts of energy. By better understanding how information can be processed efficiently, we can design new, more sustainable forms of computing. Nature, with its frugal yet smart systems like biochemical networks in bacteria, serves as an inspiring model.
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