Building a superfast nondeterministic universal Turing machine (NUTM) has been shown to be possible with new groundbreaking research.
Source: wikipedia, pixabay
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
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Excellent content? There is no doubt about that. 164 votes on your comment right there :)
This whole process assumes every "branch" can be split and with it all state (RAM/DISK) and then processed in parallel.
You can achieve identical algorithms today assuming you had a GPU with more CORES than BRANCHES and that you had fast replicating copy-on-write RAM.
There is nothing magical about DNA that couldn't be replicated with silicon and 4 bit computing. It isn't like you can construct new DNA molecules without brining in new raw material, which means the DNA machine is limited by the number of molecules it has available to reconfigure, just like silicon and FPGAs.
So in the end the size doesn't matter? They made an allusion to your desktop computer on this principle being quicker than a supercomputer, but I guess that was only the idea of exponential time to arrive at a a solution making that tech faster than anythin, and not actually the DNA tech itself.
Today's tech can do parallel processing, so what is the drive for a "quantum" solution that would do exponentially fast solution calculations? Wouldn't it still be faster in its design compared to the current tech?
DNA is a data-storage system that is 1000x denser than any RAM that we have today. DNA is not a computation system.
Massive parallelism, like described in the article, is based upon the ability to rapidly and accurately clone DNA. Every time a branch is discovered, then entire state is "cloned" and farmed off to another processing core.
https://www.extremetech.com/extreme/134672-harvard-cracks-dna-storage-crams-700-terabytes-of-data-into-a-single-gram
Parallel processing in this manner allows computation to be spread out to more cores: if you can transport the cloned DNA to an available processor efficiently.
Before DNA computers can become a reality, we will need the technology to completely sequence the human genome in a microsecond.
Ah ok, good for storage potential for now, but not processing for a while... if at all. Thanks for the explanation!
That is interesting. I had never heard of this worded this way.
Your explanation is good.
It seems like this would lose out to quantum computers when miniaturization is taken into account. These types of computers would never be able to become as small as a quantum computer in theory right?
I don't know enough to accurately answer. I did a post on the first quantum computer blueprint, that was scalable. It was pretty big. DNA is very small. The article mentioned how even growing, it's still smaller than microchips. The race is on... lol... quantum vs DNA computing... who will be better!
QUICK. Use it to mine Bitcoin. o__o;
Upvoted
@shayne
Imagine mining BTC on this puppy... :p
They have a coin for that:
Such coin, much wow! :O
Funny
This is really cool , but why does this give me the feeling that this is what is going to cause a self aware A.I and take over the world XD .
Embrace it...
Don't fight it!
true XD
I also had that feeling XD
I resteemed so I can come back to read@a later time ;)
This sounds real interesting, can't wait to read. Thx!
Amazing times!!
}this is a great advance.