Feb 02, 2020
Scientists at the University of Manchester reveal new super-fast form of computer that ‘grows as it computes’; a new type of self-replicating computer that uses DNA to make calculations, a breakthrough that could make computing far more efficient.
Professor Ross D King and his team have demonstrated for the first time the feasibility of engineering a nondeterministic universal Turing machine (NUTM), and their research is to be published in the prestigious Journal of the Royal Society Interface.
The theoretical properties of such a computing machine, including its exponential boost in speed over electronic and quantum computers, have been well understood for many years – but the Manchester breakthrough demonstrates that it is actually possible to physically create a NUTM using DNA molecules.
“Imagine a computer is searching a maze and comes to a choice point, one path leading left, the other right,” explained Professor King, from Manchester’s School of Computer Science. “Electronic computers need to choose which path to follow first. But our new computer doesn’t need to choose, for it can replicate itself and follow both paths at the same time, thus finding the answer faster.”
Computing with DNA was first proposed in 1994 as a way to solve problems faster than with normal computers. DNA has a number of advantages over silicon that makes it ideal for problem solving, namely that it’s extremely small and highly stable.
But the biggest advantage of DNA is that it can copy itself. In computing terms, this means that a DNA computer can run an arbitrary number of calculations at the same time, which is very important for solving complex problems. While a typical computer might have to do a billion calculations one after another, a DNA computer can just make a billion copies of itself and do all the calculations at once.
In fact, that’s just what the University of Manchester researchers did with their DNA computer. Theirs is the first physical demonstration of this concept, and they hope that a DNA computer could be used to solve complex problems faster than current computers, or even the quantum computers of the future.
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