Except that the model bio supercomputer they have created is a whole lot smaller than current supercomputers, uses much less energy, and uses proteins present in all living cells to function.
The model bio-supercomputer came about thanks to a combination of geometrical modeling and engineering knowhow. The circuit the researchers have created looks a bit like a road map of a busy and very organized city as seen from a plane. Just as in a city, cars and trucks of different sizes, powered by motors of different kinds, navigate through channels that have been created for them, consuming the fuel they need to keep moving.
Strands of proteins of different lengths move around the chip in the bio computer in directed patterns, a bit like cars and trucks navigating the streets of a city. Credits: Till Korten
But in the case of the biocomputer, the city is a chip measuring about 1.5 cm square in which channels have been etched. Instead of the electrons that are propelled by an electrical charge and move around within a traditional microchip, short strings of proteins (which the researchers call biological agents) travel around the circuit in a controlled way, their movements powered by ATP, the chemical that is, in some ways, the juice of life for everything from plants to politicians.
Because it is run by biological agents, and as a result hardly heats up at all, the model bio-supercomputer that the researchers have developed uses far less energy than standard electronic supercomputers do, making it more sustainable. Traditional supercomputers use so much electricity that they heat up a lot and then need to be cooled down, often requiring their own power plant to function.
Although the model bio supercomputer was able to very efficiently tackle a complex classical mathematical problem by using parallel computing of the kind used by supercomputers, the researchers recognize that there is still a lot of work ahead to move from the model they have created to a full-scale functional computer.
Citation: Dan Nicolau Jr et al, “Parallel computation with molecular-motor-propelled agents in nanofabricated networks”, Proceedings of the National Academy of Sciences (PNAS): http://www.pnas.org/content/early/2016/02/17/1510825113
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