The Future of Optical Fibre 139
An anonymous reader writes "An Australian researcher has come up with a novel way of developing optical fibres. Steven Manos, a researcher at the Optical Fibre Technology Centre in Sydney, Australia has developed a method of using genetic algorithims for discovering optimal designs of optical fibres. An article on his work had this to say "The problem with designing optical fibres is starting with a specific set of criteria and then coming up with a design to fit this. The computer program developed by Manos, which is run on supercomputers, does this by mimicking the process of evolution. The computer program combines two patterns to create a third fibre 'offspring', which Manos described as "similar but a bit different". This process is repeated thousands of times with the 10 designs best suited for the particular application chosen to 'breed' again." Another case of "When in doubt, use brute force"?"
Brute force? Not exactly (Score:5, Insightful)
Re:Brute force? Not exactly (Score:5, Insightful)
I'd rather not think of the method as brute force.
Well said. Brute force would be enumerating every possible optical fibre and then testing them.
This method is more subtle and converges to a close-to-optimal solution with less computer power having to be applied.
Re:Brute force? Not exactly (Score:1, Insightful)
GA is not guaranteed to converge to a "close-to-optimal solution". With results from a GA you do NOT know the solution is optimal. The **hope** is that by wiggling around somewhat in parallel with your genetic inputs that you have a better chance to find a global optima. That is just a hope.
Re:Brute force? Not exactly (Score:1)
Yes, you're quite right, I probably shouldn't have put it in such broad terms. Although I didn't claim that it would be optimal, or that you would know it was optimal.
I suppose though that there might be a theoretical upper bound on the performance of a design (think about a spaceship, once you're close to c you're doing demonstratably well), so you at least know how close you are to the very best design
Re:Brute force? Not exactly (Score:2)
What can be tough about such stopping conditions is making sure you have a good scoring function so that the optimal solution indeed scores best, and that you know what that score should be (though, of course, not how to get there, or the alg is pointless).
Re:Brute force? Not exactly (Score:1)
Re:Brute force? Not exactly (Score:2)
In other words, consider the test criteria equivalent to Nature and the various fibers as types of animals. If Nature changes a few times, an animal ideal for the latest natural conditions might have been "breeded" ou
Re:Brute force? Not exactly (Score:2)
That's why GA systems often randomly introduce brand new genomes to a population. It supplies some entropy to "tunnel" out of local minima.
Re:Brute force? Not exactly (Score:3, Interesting)
Ok, its not like a design from first principles, but its still way to search the parameter space without having to test all coimbinations of parameters
So-called first principles are explanation, not design tools. In other words - guess what? - nature is still surprising even if it can be "explained" by what we already know. We can explain stuff. It's the construction that we don't understand so well.
Re:Brute force? Not exactly (Score:5, Insightful)
I'll agree with that. Brute force searching would go though all the parameters a la
for(parameter1 = min limit
for(parameter2 = min limit
for(parameter3... )
etc....
Evaluate(parameter1, param2,
Genetic algorithms try to limit the search space by starting with "probably good" sets of parameter values and trying to generate other "probably good but hopefully better" parameter combinations.
It won't necessarily find the absolute best set of parameters but it might find some reasonable ones.
Re:Brute force? Not exactly (Score:2)
Genetic algorithms can only be shown to find optimal paths quickly when the the path is already known.
Genetic algorithms are re-discovery algorithms. They are never well applied to situations with an unknown search space.
Re:Brute force? Not exactly (Score:5, Funny)
In other word instead of fudging designs while you wait ten years for a mathematician to find the equations for the perfect wing, you just get a computer program to 'evolve' one for you. I'll bet this is what boeing and airbus already do.
Sadly this will leave most applied physics mathematicians out of a job. Danm computers!! Taking our jobs and our women!!
Re:Brute force? Not exactly (Score:1)
Compouters don't need women so... First they take the jobs. Then they take the power. Then WE get the women.
Sounds pretty sweet to me!
Re:Brute force? Not exactly (Score:2)
There are many things we can create a blackbox algorithm which represents the first principles as good of better than algorithms based on a full understanding of the first principles.
Example:
At a division of Honeywell, we worked on "flattening the response curve" of the crt.
to do this the engineers developed complicated models based on energy output, gamma curves, crystal variations, etc and used these models to sense the point to point deviations across the crt and create a
Re:Brute force? Not exactly (Score:2, Insightful)
Even at tasks it can be applied to - like key cracking etc, it is still practiacally uselless without a bit of intelligence build in.
Even the best prime generators dont doa brute iteration through all integers > 0 to infinity - that would be pointless. You need to know where to look as well, or your waisting your time.
I hope as computers continue to advance we dont forget this and simply rely on computing power. Because no matter ho
Re:Brute force? Not exactly (Score:2)
A true brute force, exhaustive search of all possible parameter values may take longer, bu
Question? (Score:1)
Or is this process used to design the cable itself?
Re:Question? (Score:2, Informative)
Optical Fibre Technology Centre:
http://www.oftc.usyd.edu.au/?section=fibre [usyd.edu.au]
Re:Breeding!!! (Score:1)
Re:Question? (Score:2)
Sorry to not answer the question (it's designing the cable *fibers* themselves - hence "design of optical fibers" in the article description and the linked article all about optical fibers) - but the incorrectly spelled "breeding" makes me laugh. It's even more amusing when you *read the article* and see the word "breeding" used in the caption under the large ph
Mimicking evolution? (Score:2)
Re:Mimicking evolution? (Score:2)
It's an idea which helps explain some things which are tough to explain fully with evolution. It is important to keep asking questions, evolution does a pretty poor job at explaining some phenomenon.
I personally doubt any religiously sponsored pseudo-science will result in a credible theory to help explain evolution, but you can't close your mind to the objections they raise. The little propellor-bacteria and similar systems are kind of cool... while evolution sort-of explains them, it is certainly a we
Re:Mimicking evolution? (Score:2)
One problem, though. The circuit board only worked *exactly* where the board was, because it actually made part of one of the wires behave like an antenna and it relied on the specific electromagnetic field in that location to run the circuit. As a result, moving the circuit board made it no longer function.
I wonder whether the same result m
Re:First cars... (Score:2, Informative)
One thing they get used for in academia is designing robots. Its very hard to teach a robot to do something like walking, and the optimal solution depends on so many factors that its hard for humans to hard-code the behavior. But set up the proper simulated environment on a computer, and have a genetic algorithm wh
Re:First cars... (Score:1)
PDFs from Manos (Score:5, Informative)
There are some interesting PDFs of papers co-written by Steven Manos available including these two:
I'm not going to pretend that I know exactly what's going on, but the first of those two is worth looking at if you have even a passing interest. The second looks to be a little more towards the "deep end".
Re:PDFs from Manos (Score:1, Offtopic)
But thanks for the reply anyway.
Re:Fucking hell why all the excitement about GA? (Score:2)
The way a lot of genetic algorithm applications are approached it also seems that there is great potential for overfitting - remember that sinc
Re:Fucking hell why all the excitement about GA? (Score:1)
I'm a bit puzzled by GA hoopla as well. Sure it can achieve results, but it's something of a copout. If GA's can do a reasonable job at optimising a (fitness) function (that's, after all, all they really try to do), then surely there's an actual special purpose algorithm that can do a better job.. (Although that goes quite directly to the heart of the P vs. NP question..)
I think it's just people throwing GA's at a problem because it's quite easy and works slightly..
I, for one, hope that one
Re:Fucking hell why all the excitement about GA? (Score:1)
There are dozens of parameter searching techniques that could be used to solve this problem. It may have been more useful to demonstrate these against the present algorithm to see how efficiently the space is examined and if the 'fitness' can be improved further
Much Better (Score:5, Informative)
in this case they have a very specific set of criteria.
it didn't however mention in the article how they're testing the designs (did it?)...
and are they actually manufacturing any of the designs that have come from thiss yet?
Re:Much Better (Score:2)
"site:slashdot.org formula one genetic" -> Breeding Race Cars With Genetic Algorithms [slashdot.org]
Only on slashdot... (Score:5, Funny)
Re:Only on slashdot... (Score:1)
I thought the future of fiber optics was... (Score:2, Interesting)
What the... (Score:2, Insightful)
Another case of "When in doubt, use brute force"?
Evolutionary search isn't "brute force", you id... At least not for meaningful definitions of 'brute force'
Brute force would be starting at one end of design space and evaluating each design in turn.
Re:What the... (Score:1)
Oh wait, you can't. All the other species have brute forced them out of the environment...
GA's are not brute force (Score:5, Insightful)
Evolutionary Algorithms provide informed search as they perform competition among the individuals (each representing one possible solution) in the population. Their performance is way above exhaustive search techniques (which _are_ brute force) but below classical search techniques. In this case, however, such classical techniques cannot be applied as the problem space is not well-defined.
No, Taco, No (Score:5, Insightful)
No, Taco, No.
From the 'brute force' [wikipedia.org] entry in Wikipedia:
In computer science, Brute Force, sometimes called the Naive Method, is a term used to refer to the simplest, most intuitive, most spontaneous, and usually most inefficient methods of accomplishing a task.
This is exactly what a genetic algorhthem is not. If you have a million numbers brute force would be to go from the first to the last in order. Using a genetic algorhythem provides a shortcut though Design Space wherein you need to try far fewer combinations in order to come to a successful result.
C'mon Taco, of all people, you should know this!
Re:No, Taco, No (Score:1)
An Australian Genetic algorithm? (Score:5, Funny)
Another case of "When in doubt, use brute force"?" (Score:1)
Genetic algoroithms are simply another form of optimization algorithm, just like Simulated annealing, Ant-Cology optimization, just to name a few. Each variety has its strengths and weaknesses for different search spaces and genetic algorithms have there place. These often have nature related names because nature is an excellent optimizer from which we draw inspiration.
If you want to talk brute force, try an exhaustive search of complex high-dimension, continous, real valued parameter sp
on brute force (Score:2)
research paper (Score:1)
Danger!!!! (Score:2)
We must kill it before it develops language skills!!
Re:Danger!!!! (Score:1)
It's just a matter of time and technology. So a device will generate fiber optic cables and they'll spread all over the world, plugging into every device they meet in their way
[sounds like a scenario for some crappy movie or smth]
Comment removed (Score:5, Informative)
Slow, haunting music plays... incessantly (Score:2, Funny)
Reminds me of Tyco (Score:1)
Brute force? No way? (Score:5, Informative)
Suppose you wanted to find the lowest value of f(x)=sin(x) where x is from 0-360. (OK we all know its at x=270 but hear me out) - you can do it a couple of ways:
1. calculate sin(x) for all 360 possible values of "x" or
2. calculate sin(x) for (say) 20 values of "x".
Statistics says approach 2 will give you a couple of promising results, for only 1/18th of the effort. Now "breed" another 20 from the 6 values of x for which sin(x) were lowest, say 190, 210, 212, 260, 278, 290. This "next generation" gives sin(x) values whiach are closer to zero. Take the best 6 again. After three generations you are *close* to finding the values for "x" that give you sin(x)=0.
So systematic examination takes 360 tries and the genetic shortcut takes 60 tries - about 17% of the computational effort.
Now imagine a function a bit more complex; some mad multivariate affair like the wave equation. Each variable becomes a "gene" in the above "breeding program". All the time we are looking for parents and offspring that *tend* towards the answer we are looking for. (We also chuck in some unrelated parents too, since inbreeding can be bad - a tip stolen from Monte Carlo techniques [which see]).
The computational savings from GA, GP and MC techniques are potentially huge (as in orders of magnitude) so long as you dont care that:
a) The answer is not 100% exact
b) Some alternative minima are missed
Re:Brute force? No way? (Score:2, Interesting)
b) Some alternative minima are missed
A friend of mine got a job to work on genetic algorithms, in an academic institute. Being an engineer, he asked to be moved to another position 3 months after.
His explanation was very short: in GA you look for problems and you try to prove that they could be solved by this method.
Actually, all methods used in engineering were invented to solve some problem; not vice versa. Ok, maybe they not all of them, i canno
Re:Brute force? No way? (Score:2)
Re:Brute force? No way? (Score:2)
The problems arise with tooling (complicated), instrumentation (expensive) and reagents (twitchy) needed to cleanly detect signals. Oh, and a degree in biochemistry for the user
Re:Brute force? No way? (Score:2)
Finding a single useful organism could have tremendous impact. Consider the cost of a lottery ticket and the odds of payoff. A microarray would look like a lottery ticket in size and shape and ought to cost slightly less than a dollar to manufacture. QED.
It
Re:Brute force? No way? (Score:3, Insightful)
The problem of local minima is often significant. A good analogy is real genetics - each species has evolved into a "local minima" for likelihood of extinction. If the wings on a given type of butterfly become slightly larger or smaller there will typically be a survivability penalty of some kind, and wing size has stabilized at the optimum for that species. But look at the difference in possible local minima: in one case it res
Re:Brute force? No way? (Score:2)
massive fiber overcapacity already? (Score:2, Interesting)
20 tbps should be good enough for anyone (Score:2)
The article v
Genetic Algorithm + Hill climbing (Score:4, Interesting)
GAs are great for jumping out of local optima to find new realms of the solution space, but don't converge as quickly on the neighborhood optima. So the combination of a GA with more classical optimzation can work well.
Re:Genetic Algorithm + Hill climbing (Score:2, Interesting)
re: "When in doubt, use brute force"? (Score:1)
Of couse, I am also a big proponent of the idea that evolution gave humans the greatest gift of all - the ability to self-evolve ourselves.
this guy is way too confident (Score:3, Insightful)
How can anyone make a claim like this? Just the fact that one can't think of any other algorithm doesn't mean no such algorithm exists. For many problems that can be solved by genetic algorithms, other (problem-specific) algorithms exists (or may exists) that are way more efficient. The nice thing about genetic algorithms is that it is a standard tool that often works, not that it is an exceptionally smart way of doing things.
Re:this guy is way too confident (Score:5, Insightful)
So why don't you hear a great deal about such algorithms? Well, for one, they don't have cool names like "Genetic Algorithms". Also, they are highly prized and considered extremely valuable intellectual property for the companies that actually make optical fiber. We are not going to publicise all the details the most fundamental design tools of our business.
GA's are not the future of optical fiber. They are, however, excellent for generating academic papers, which in turn are highly useful for getting tenure.
Re:this guy is way too confident (Score:2, Funny)
Re: (Score:2, Informative)
What's so great about meat? (Score:4, Insightful)
More like another case of computer science being fascinated by meat.
Remember when neural networks were the next big thing? Everyone was applying them to everything, whether or not it made sense to solve the problem that way. It's neural! Just like our brains! Our brains are smart, they will make our computers smart!
I'm sure genetic algorithms will eke out a useful place in the computer science toolkit, I just doubt it will be as broad as the current fashion of applying them to everything from optical fiber to race cars [slashdot.org] to compilers [slashdot.org].
Re:What's so great about meat? (Score:2)
Meat made that computer and this forum... (Score:2)
While you're demonstrating ignorance, there is a lot of very promising work going into applications of neural networks to control systems and the broader field of AI in general. The problem with neural networks is that you need large numbers of processors to do some of the more complicated nets in anything approaching real time. Your brain has several billion little processors massively interconnected.
Up until very recently with the advent of large scale FPGAs, this
SWAG (Score:1)
At least they are using a computer to do it.
It had to be said. (Score:2, Funny)
Genetic Algorithms are so cool (Score:3, Interesting)
The difficult thing is how to score individual trials. I don't know how many times I've checked things after a overnight run and found that my results aren't what I expected. Pretty much everytime this comes down to how I've scored a trial. Just remember you get what you ask for.
For a circuit example, suppose I ask for a certain power comsumption and speed but I overstate the speed goal. Because I'm so far off the speed goal the power will largely be ignored. There are easy ways to tweak this but the point is...again...you get what you ask for.
I'm waiting... (Score:1)
Where's Crow? Tom Servo? (Score:2)
Steven Manos... I guess the "fate" of fibre is in his "hands."
On GAs and randomized data (Score:1)
1. "Breed" them with each other.
2. "Breed" them with totally random data.
No matter how well your select your original machines, there's practically always room for improvement (otherwise, why use a GA in the first place?) Unless you are REALLY good at selecting your first few machines, the random data really is powerfull. Case
Identically simialar (except for the differences) (Score:1)
Brute force? (Score:2)
No. Brute force would be making a list of all possible designs, removing the ones which did not fit the requirements, and sorting by price. This method explores only a small subset of all possible designs - while it won't find the theoretical best possible design, it'll find one good enough, and it'll do it in a timespan shorter than the age of the universe.
Fiber Optics? (Score:2)
Re: (Score:2, Offtopic)
Re:Pretty cool stuff. (Score:1, Funny)
America > World
Re:Manos, the Fibre of Fate (Score:2)
ThE MaStEr DoEs NoT aPpRoVe Of WiReLeSs, OnLy FiBrE
Re:Manos, the Fibre of Fate (Score:2)
Re:What's with the French? (Score:2)
Actually it has more to do with the Normans invading england in 1066 and dumping literally thousands of french words into the english language. English is an unusual language in that its actually a true amalgamation of a number of languages (anglosaxon , norman french and old norse with a few others thrown into the mix too). Generally (linguists don't flame me ok) it has germanic verbs & nouns + norman frenc
Re:What's with the French? (Score:2)
Re:What's with the French? (Score:2)
I thought i was being 'informative'.