Building a superfast nondeterministic universal Turing machine (NUTM) has been shown to be possible with new groundbreaking research.
Researchers at the University of Manchester have a paper published in the Journal of the Royal Society Interface that demonstrates DNA computing can blow away current processing power, even in supercomputers.
DNA computing uses biological molecules rather than traditional silicon chips, where information is represented the four character genetic alphabet, A, G, C and T. Standard electronic processing uses the binary alphabet of 0s and 1s to set the state as either on or off.
To understand the implications, imagine searching a maze and coming to a diverging point. A choice needs to be made of either to go left or right in order to find a solution out of the maze. In our standard electronics, one path needs to be chosen and followed to determine if it's a success or failure. If it's a failure, then the other path can be tried. On and on until the right path is chosen to complete the maze.
The new DNA molecule computations don't need to choose which path to take. It can replicate itself and follow both paths at the same time which means finding the answer quicker.
This is made possible because the computer processors are made of DNA rather than silicon. Current computers have a fixed number of chips, while a DNA computer would have the ability to grow as it computes which makes it faster and allow it to solve many computational problems that were previously impossible in polynomial time. The ability to find a solution to a problem would be exponentially quicker compared to current technology.
In conventional computing, the trickier a problem is to solve, the more steps are required and the longer time it takes to find an answer. Nondeterministic universal Turing machines take the same amount of time to solve a complex problem as it would to solve a simple problem. The drawback is that the computational power is limited by the space it can take up since it grows.
Quantum computers may be the hype right now, but they are limited in their ability to follow multiple paths in a maze at once because they require certain symmetries to be present which limits their potential use. The DNA-based computations do not have such symmetry limits.
We have some time to wait for this hype become a reality. DNA can be really hard to control and might not be the ideal substance for future computing technology. Getting this to work in practice is a large hurdle will need to be overcome. DNA logic gates might be a more feasible and realistic application compared to DNA computing. So don't hold your breath, because this might not be possible. But if it is, it's going to take a while to figure it out.
For some background if you're interested, this work relates to the P vs. NP problem in computer science. For some questions with information provided, there is no known way to find an answer quickly, but if an answer is provided then it can be verified quickly with the information given. Questions answered in polynomial time are referred to as P, and an answer that can be verified in polynomial time is called NP.
Can every solved problem whose answer can be checked quickly by a computer also be quickly solved by a computer? P and NP are the two types of maths problems referred to: P problems are fast for computers to solve, and so are considered "easy". NP problems are fast (and so "easy") for a computer to check, but are not necessarily easy to solve.
Suppose someone wants to build two towers, by stacking rocks of different mass. One wants to make sure that each of the towers has exactly the same mass. That means one will have to put the rocks into two piles that have the same mass. If one guesses a division of the rocks that one thinks will work, it would be easy for one to check if one was right. (To check the answer, one can divide the rocks into two piles, then use a balance to see if they have the same mass.) Because it is easy to check this problem, called 'Partition' by computer scientists—easier than to solve it outright, as we will see—it is an NP problem.
References:
- Scientists reveal new super-fast form of computer that 'grows as it computes'
- First hint of how DNA calculators could supercharge computing
- Currin, A., Korovin, K., Ababi, M., Roper, K., Kell, D.B., Day, P.J., King, R.D. (2017) Computing exponentially faster: Implementing a nondeterministic universal Turing machine using DNA. Journal of the Royal Society Interface. (in press). On Arxiv: arxiv.org/abs/1607.08078
- P versus NP problem
- P versus NP
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2017-03-02, 12:02pm