>Mmm, strangely enough, I'd be worried about being taught languages and logic by someone who couldn't be bothered even analysing exactly what he's writing.
Hey, I never said I taught spelling and grammar. That was grammatically incorrect, you're certainly right. I apologize if this offended you.
I *do* however, understand the classical fallacies. Look up 'ad hominem abuse' sometime.
>Those who'd rather talk about it than do it go into teaching.
Just for the record... at the University level, teaching is a side-effect of doing research. I happen to quite enjoy teaching but my raison d'etre is my research.
If you mean to imply that researching is 'doing nothing', I would respectfully submit that you have never in your life attempted serious research. This is also kind of at odds with your comments on 'the talented' going into R&D.
>The incompetent put on suits and go into management.
I teach university computer science courses as part of my job. Yes, I agree, it looks like GATech went way overboard here, but unfortunately this is burying the root problem.
Computer science programs are LOADED with cheating. Not just a bit. A *lot*. The faculty at my institution didn't think we had a problem... until we looked. And what a problem it was.
It was, of course, inevitable. Lets face it.. CS is a hot program these days. Mom and Dad see lots job ops and strongly push junior to go into CS. Perhaps junior isn't really that interested in it; perhaps junior can't do math, but Mom and Pop are paying the bill, so...
Now you have a problem. Junior needs to pass (lest his winter vacations of beer drinking, etc. be untimely ripped from him).. but junior could care less about the material. He doesn't want to bother learning it.. and there is a *lot* there to learn.
How does one pass, yet do the bare minimal amount of work? Doesn't take a genius to figure this out... does it?
The trouble is that, in general, computer science courses (especially 'systems' type courses) usually heavily weight assignments. Sure, you could just do exams... but I believe that seriously cheats the students. Being able to parrot back 4 solutions to deadlock on a final exam is a world away from being asked to actually think through and then solve these problems IN CODE.
So we need assignments... but they are OH so easy to cheat on. Much easier than exams.
Net result: Every year thousands of people graduate with CS degrees that can not: explain the sleeping barber problem; do OMT diagrams; define a Turing machine; give an example of a non-computable function; demonstrate even the remotest knowledge of what the "NP" means in 'NP-complete', use structured programming concepts, comment code, apply even the most basic software engineering techniques, etc.
There seems to be a lot of people against these heavy-handed measures to weed out cheaters. I'm a libertarian at heart, so I agree in a lot of ways. On the other hand, do YOU want to graduate from a school that cranks out CS majors who go into a coma when someone says "Scheme" or "LISP"? Do you want people in industry to have experience with graduates from *your* university that can't even apply a simple waterfall model of software development?
If you don't take measures against cheating, the people who will lose (and lose big) are the good students. Think about it.
First off, you're right, I was being a jerk, and I feel badly about that. My apologies.
Now, about the parse tree... I would agree that they are performing the same function, but given that gcc almost certainly parses its input with an LR(n)-parser, I'm going to go out an a limb and say that the trees for i+=1, i=i+1, i++ are different.
If you have differently structured input, and an (almost) context-free grammar to parse it... you'd better get different trees for different structures.
I also disagree that it has 'nothing to do with optimization'. If you just spat out assembly code from the tree, you *should* notice a difference in i=i+1, i++. If you do any type of basic optimization (even simple peephole optimization would catch this in the IR), then you'll end up with equal output.
I also respectfully disagree that RTL is a faithful reproduction of the original parse tree. From the 'Reading RTL' section of the gcc docs:
"Correct RTL for a given program is very dependent on the particular target machine. And the RTL does not contain all the information about the program."
Since an LR(1) parse tree of a program should look the same independant of the underlying architecture , I'm going to make the bold assumption that some optimizations take place at the RTL level. This seems very reasonable and is the case in other compilers I've worked with, but since I've never specifically worked with gcc, I'm not 100% sure.
I would imagine there is a way to get gcc to print out the parse tree, rather than the IR, but not being that familiar with it, I wouldn't know what that was. You could always grab the BNF spec for the C grammar and code it up in Bison;)
Not to spoil it for you or anything, but you really should have at least a *marginal* understanding of optimizing compilers before you go pretending to be an expert.
I don't mean to be nasty here, but NOTHING offends me more than an arrogant ignorant person. We all make mistakes, and thats cool, but when you jump down someone elses back with condescending remarks you better be sure that you know what you're talking about.
Without further ado, here are two C programs:
add.c: main(){ int i; i = 0;i++;}
add2.c: main(){int i;i = 0;i+=1;}
Now, we compile them using the -S option on gcc (in my case on a SPARC running Solaris, but I'd wager you'd get similar results on just about any supported architecture). So again, we do a:
% gcc -S add.c % gcc -S add2.c
(I tried to post the.s files here, but our old friend the lameness filter clobbered them)
Now, do a 'diff' on 'em. Draw your own conclusions.
>All the articles posted today are right on par quality-wise with the articles posted every other day!
I have to disagree. By virtue of the fact that they're purely fictious, and invented by the same persons posting about them; the articles posted today have a good deal *more* journalistic integrity than anything else I've ever read on Slashdot.
I'm going to make the brave supposition that quantum computers will overcome the decoherence problem and scale to non-trivial sizes.
(Even if this doesn't happen, the following algorithms still deserve honorable mention for being the first to make use of quantum parallelism to give results unattainable thus far by classical algorithms):
- Shor's algorithm for factoring and discrete log - Grover's search algorithm
...even moderately offended by the lack of functional languages offered to the contestants?
(I'm (not (one) of those) rabid, foaming LISP advocates) that insists *everything* is better with functional languages... but... I do believe there is a time and place for just about every style of programming. Some of those questions looked very much like the "time and place" for a nice modern functional language like Haskell. Even Scheme would've been nice... Miranda, some flavour of ML... anything.
Perhaps there is some reasoning behind this that I'm missing. I guess I just thought it was sad that the ACM seems to be promoting the view that functional languages are too 'esoteric' even for use in a programming contest.
Combinator calculus actually has a *practical* application. No kidding. In fact, the whole beauty of combinators is that you can reduce lambda-expressions into a variable-free, but equivalent form (via the `bracket-abstraction' algorithm).
Anyway, the point is, if you're writing the back end for a functional language... wouldn't it be real swell if you all had to implement was two combinators? No dealing with messy variables either. This is exactly the approach taken in the implementation of the functional language Miranda. (Although for reasons of efficiency, there are more than 2 combinators... you *could* use just S and K, but then you get some REALLY HUGE results for even relatively simple lambda-expressions).
So combinatory logic isn't just the domain of Schoenfinkle, Haskell Curry and assorted logic fetishists... it can and has been used for `real life' applications too.
Good point. I should have been more explicit in the parent post that my *only* field of typesetting experience is with very dense mathematics. I took a look through your papers and you seem to be working more on applied aspects of computer science, so it makes sense (to me anyways) that you might not be so interested in a mathematics typesetting package.
If the 'equation density' of one's paper becomes greater than a certain point, the ease-of-use of Microsoft Equation Editor is outweighted by the raw speed of use of TeX. As a bonus, you get very nice looking mathematics too.
Yes there is more of a one-time investment in learning TeX, but after that you become very productive. With LaTeX in particular, the whole point is that you focus solely on content, and let the software worry about presentation. Its got nothing to do with being 'neat' or wanting 'kudos'. It has everything to do with 'how fast, and with how little effort on trivialities, can I produce a mathematics paper that doesn't look like a dog's breakfast?'
>but the only game in town (for mathematics or anything)? No, not really.
I can't speak for general publishing, but for serious math publishing I have to respectfully disagree. If you have ever even remotely come into contact with serious mathematics you will be aware that Springer-Verlag (http://www.springer.de/) is one of the major publishers.
I have never prepared a manuscript for a Springer book or journal that was *not* in TeX format.
Could you give me some examples of the "quite a lot of software used before latex"? Specifically what "math" publishers use standards other than TeX... I'd truly be interested because I've never come across one.
As a side note, please be careful not to confuse LaTeX with TeX. LaTeX (which I admit to using most of the time) is kind of like "TeX for dummies". (Thats not entirely fair... LaTeX makes 95% of what I want to do easier and faster than plain TeX... but for that last 5%, LaTeX makes me want to punch things. LaTeX=easy, TeX=flexible).
>Well tell them than a 24-clause 20-variable 3-SAT problem isn't very hard.
I don't think anyone would argue with you on this point. These are still toy examples... proof-of-principle type stuff. Remember that this result came out of Len Adleman's lab; If you're aware of who Adleman is, then I assume you'll agree its likely he was quite aware of this fact. If you don't know who Adleman is... well, I assume anyone mathematically literate enough to come up with the (quite correct) argument that you made would have to be at least passingly familiar with him.
If you're interested in attacks on DNA computing, I highly recommend reading:
Juris Hartmanis. On the weight of computations. Bulletin of the European Association For Theoretical Computer Science, 55:136--138, 1995.
Its short, but sweet.
As for the "no person could complete by hand" bit; I have to agree with you. The concept of "doable by hand" is pretty ill-defined. In any case, thats not the *real* point of the paper. The point is that the lab tech who implemented the computation did not know the solution a priori. Seems like a pretty obvious control, but so far all previous experiments have been so trivial that a human (or moderately skilled monkey) could trivially see the answer just by looking at them.
Well it certianly isn't the "first" DNA computer to solve a problem. However, it *is* the first one to solve a problem that would be seriously non-trivial for a human to do by hand.
It was definitely 3-SAT; I just spoke with one of the experimenters yesterday.
Re:Biologists and Psychologists Abuse this...
on
Digital Biology
·
· Score: 2
Its called the 'bootstrapping' problem. Look it up.
Re:Biologists and Psychologists Abuse this...
on
Digital Biology
·
· Score: 2
>Has anyone proved you can build a Turing machine in DNA yet?
Depends on what you mean by 'building a Turing Machine in DNA'. Your question is rather analogous to saying 'has anyone proved you can build a Turing machine with SDRAM yet?'. DNA is a storage medium and requires external mechanisms to operate on it for computation.
If you take DNA and the DNA-processing mechanisms from stichotrichous ciliates, then yes, you *can* build a Turing Machine. See:
Reversable Molecular Computation in Ciliates. Kari, L., Kari, J., Landweber, L.F., _Jewels are Forever_ (Karhumaki, J. et. al eds.), Springer-Verlag, 1999, pp 353--363
Thats particularly interesting because its _in vivo_ computing, but there are also tens (probably hundreds) of proposals for _in vitro_ DNA computing. Do a google search on 'DNA Computing' and look for the proceedings of the International conferences on DNA-based Computers (I believe the one this summer in Japan is number 8)... IIRC they're published under a DIMACS series. If you want a 'canonical' paper for _in vitro_ methods, I guess starting at the beginning would be the best:
Adleman, L., "Molecular Computation of Solutions to Combinatorial Problems," Science, Vol. 266, 11 November 1994, pp. 1021-1023.
Trolling is more effective if you actually bother to read the parent post first... the post is about scientific research in general. And yes, it is quite possible to make 'outlandish claims' in mathematics. Check out the disturbance Goedel's theorem caused.
Personally, I think mathematics is a science and I didn't want to intentionally exclude it from the discussion by mentioning only Nobel prizes.
Oh, and once again for the record, there is nothing *cold* about the alleged fusion reaction in the story this post is attached to. Please read the Science article. Failing that, at least read the plea to journalists to not call this 'cold fusion'.
I'm not sure what a 'scientist' really is anymore... but I think I play one on weekdays (and particularly productive weekends).
>Dr. Park and his ilk work to make a pariah of any scientist who gives any credence
This is the nature of scientific research. The more outlandish your claim, the greater the feeding frenzy will be if/when you are proven wrong. Of course, if your results hold up... you might get a Nobel Prize (or even a Fields Medal!).
This isn't necessarily a bad thing. In fact, a good scientist is always skeptical... they want to know *all* the details and be thoroughly convinced before accepting a new result. This is healthy and, in my opinion, good for science.
On the other hand, if skepticism is taken too far, it becomes dogma. Dogmatic faith is the antithesis of good science.
Now, I'm in absolutely no position to pass judgement on Dr. Park (I believe I fall into your "young postgrads" category) but personally I could never see myself interjecting a personal opinion of this sort in a scientific context.
If one has an issue with the facts presented in a paper, one takes up those issues explicitly. Innuendo about 'groaning', etc. seems unprofessional and out of place to me. To Dr. Park's credit he *does* make some very good points; most specifically that other respected scientists in the field have been unable to duplicate the results. This is very significant and valid criticism.
In the end, I think the situation is summed up very well by a quote I heard on a TV show once (I think it was 'Law & Order'):
"Scientists have a star system that make Hollywood look like a socialist love-in".
The comment offended me at the time.. but objectively speaking, there is a lot of truth in it.
This is going to be very unpopular (I can feel my karma approaching negative numbers)... but I think it has to be said.
>If you have money, you win.
This is true. You can stick your head in the sand and pretend its not, but the evidence is all around. O.J. Simpson anyone?
On the other hand, why are we surprised? We have *intentionally* built a capitalist society. Many Americans will *proudly* tell you that they are capitalists.
Capitalism works precisely because it starts on the base assumption that humans are greedy and selfish by nature (I'm not knocking Communism, which assumes humans are interested in 'helping their brother', but it has been less sucessful historically).
The most important thing in a capitalist society is... *gasp* CAPITAL! Of course the system favours people with lots of money and large tracts of land... this is by design. Money == Power. Period.
A side effect of this, of course, is that corporations (who have boatloads of capital) end up being far more powerful than individuals. Thats just the way it is.
I'm not saying this is a good thing (personally I find it frightening that big corps have so much power), but I'm not sure there is a lot that can be done about it at this point. You also can't argue that its been rather sucessful. Most Western nations are capitalist to one degree or another (like all things policital, its a spectrum, not an absolute) and the U.S. is one of the 'most capitalist' of the lot. Is it a coincidence that its also so powerful and affluent? (Yes, its an oversimplification, but I think the underlying point is valid).
Bottom line: we can't create a capitalist society and then turn around and pretend to be shocked when we see... a capitalist society.
>The top of the governmental food chain is the queen
Actually, thats not quite correct. H.M. The Queen is our Head of State.
The Right Honourable J. Chretien is our Head of Government.
Personally I'd put the head of government at the top of the 'governmental food chain'.
The Governor General acts in right of Her Majesty the Queen in Canada. And surprisingly has a fairly scary amount of power (e.g. ability to dissolve parlaiment)... though is never able to actually exercise that ability since it would cause an obscene public outrage. It is there though.. just ask Lord Byng;)
>BTW No, and we don't pronounce it "a-boot" Who started that myth?
You're correct in that we don't pronounce it 'a-boot', but we *do* tend to pronounce 'ou' as a dipthong. The trouble is that when an English speaker who is not accustomed to this phoneme hears it... their brain instinctively maps it on to the closest phoneme that they are accustomed to, which is usually 'oo'.
There is a cute little article on the historical aspects at: http://www.m-w.com/wftw/00may/052200.htm
I have to admit... I never thought I'd see the day that Slashdot became a stratified service site. The same Slashdot that strongly supports free (as in beer) OSes over the more traditional pay type. The same Slashdot where people strongly object to free registration to read NYTimes articles...
Its reasonable, of course. Someone has to pay the bill for bandwidth; and I shudder to think how large that bill would be for Slashdot. I have no objections at all to selling advertising... but to be honest the bit about 'Eventually we intend to offer additional features to subscribers' kinda bothers me.
Lots of people here are big fans of Linux. Do you get 'extra features' if you pay Linus $5/1000 lines of kernel code? Not the best analogy, but this just looks like a slippery slope.
Its not that I have no faith in Slashdot; its just that this scene has repeated itself on SO many once-free websites. It starts with a few harmless extra features for subscribers but the 'free' service eventually erodes into uselessness.
Again, I'm not questioning the addition of ads to generate revenue. I also think its pretty swell that we're being given the opportunity to buy our way out of ads. Its just the extra-feature thing that worries me. It seems so... contrary to the overwhelmingly cyber-libertarian feel of Slashdot.
Slashdot is moving from a fairly egalitarian 'society' to one with a class structure. Who saw that coming?
I figured I'd chime in with my two cents worth since not too long ago I found myself in exactly the same spot as you. I loved mathematics but was very skeptical about being able to make a living doing pure math. Heres what I did:
As an undergraduate I double-majored in pure math and computer science. I took every theoretical computer science course I could get my hands on and by my 3rd/4th year of undergrad I was pretty much doing exclusively math. Yes, 2nd year specifically involved suffering through many 'coding' courses, but in the long run this isn't such a bad thing. A computer is a wonderful tool for a mathematician and knowing how to program one well is actually a very desirable skill (note, I still hated the programming classes;) ). I enjoyed TCS so much, in fact, that I ended up doing my Ph.D. in computer science and not mathematics.
Don't let anyone fool you... theoretical computer science *is* math; and to be honest, its math that I found more interesting than any of my 'pure math' courses. As far as courses, on the math side I took as many abstract algebra courses as I could and on the CS side I focused on automata theory and formal languages (with a good helping of recursive function theory and semantics).
There were a number of posters above who mentioned mathematical biology and bioinformatics. For me, anyway, this was bang on the target. There is a huge need for competent mathematicians who are willing to learn a little bit about biology. We are at the point where biology is beginning the transition from a qualitative to a quantative science and we *need* good models.
Again, don't be fooled into thinking you have to do applied math. Sure, coming up with a model is 'applied' in some sense, but once you have the model you get to investigate it and try to prove properties that you think it has (e.g. recent work involved showing that the gene-descrambling process in hyptochious ciliates is computationally universal. Proving that is fun mathematics).
And of course, once you get a job and a grant, theres nothing preventing you from also researching other topics too (my 'academic hobby' is foundations of mathematics... but you don't get too many grants for that;) ).
Job prospects in Computer Science (academically speaking) are good right now; though its certainly tougher as a theoretician than, say, a software engineer. But, if you can market yourself correctly, I think its easier than pure math.
I hope that stream-of-conciousness rambling was of some value to you.
Slashdot Mirror
>Mmm, strangely enough, I'd be worried about being taught languages and logic by someone who couldn't be bothered even analysing exactly what he's writing.
Hey, I never said I taught spelling and grammar. That was grammatically incorrect, you're certainly right. I apologize if this offended you.
I *do* however, understand the classical fallacies. Look up 'ad hominem abuse' sometime.
>Those who'd rather talk about it than do it go into teaching.
Just for the record... at the University level, teaching is a side-effect of doing research. I happen to quite enjoy teaching but my raison d'etre is my research.
If you mean to imply that researching is 'doing nothing', I would respectfully submit that you have never in your life attempted serious research. This is also kind of at odds with your comments on 'the talented' going into R&D.
>The incompetent put on suits and go into management.
This is something we can both agree on.
I teach university computer science courses as part of my job. Yes, I agree, it looks like GATech went way overboard here, but unfortunately this is burying the root problem.
Computer science programs are LOADED with cheating. Not just a bit. A *lot*. The faculty at my institution didn't think we had a problem... until we looked. And what a problem it was.
It was, of course, inevitable. Lets face it.. CS is a hot program these days. Mom and Dad see lots job ops and strongly push junior to go into CS. Perhaps junior isn't really that interested in it; perhaps junior can't do math, but Mom and Pop are paying the bill, so...
Now you have a problem. Junior needs to pass (lest his winter vacations of beer drinking, etc. be untimely ripped from him).. but junior could care less about the material. He doesn't want to bother learning it.. and there is a *lot* there to learn.
How does one pass, yet do the bare minimal amount of work? Doesn't take a genius to figure this out... does it?
The trouble is that, in general, computer science courses (especially 'systems' type courses) usually heavily weight assignments. Sure, you could just do exams... but I believe that seriously cheats the students. Being able to parrot back 4 solutions to deadlock on a final exam is a world away from being asked to actually think through and then solve these problems IN CODE.
So we need assignments... but they are OH so easy to cheat on. Much easier than exams.
Net result: Every year thousands of people graduate with CS degrees that can not: explain the sleeping barber problem; do OMT diagrams; define a Turing machine; give an example of a non-computable function; demonstrate even the remotest knowledge of what the "NP" means in 'NP-complete', use structured programming concepts, comment code, apply even the most basic software engineering techniques, etc.
There seems to be a lot of people against these heavy-handed measures to weed out cheaters. I'm a libertarian at heart, so I agree in a lot of ways. On the other hand, do YOU want to graduate from a school that cranks out CS majors who go into a coma when someone says "Scheme" or "LISP"? Do you want people in industry to have experience with graduates from *your* university that can't even apply a simple waterfall model of software development?
If you don't take measures against cheating, the people who will lose (and lose big) are the good students. Think about it.
First off, you're right, I was being a jerk, and I feel badly about that. My apologies.
;)
Now, about the parse tree... I would agree that they are performing the same function, but given that gcc almost certainly parses its input with an LR(n)-parser, I'm going to go out an a limb and say that the trees for i+=1, i=i+1, i++ are different.
If you have differently structured input, and an (almost) context-free grammar to parse it... you'd better get different trees for different structures.
I also disagree that it has 'nothing to do with optimization'. If you just spat out assembly code from the tree, you *should* notice a difference in i=i+1, i++. If you do any type of basic optimization (even simple peephole optimization would catch this in the IR), then you'll end up with equal output.
I also respectfully disagree that RTL is a faithful reproduction of the original parse tree. From the 'Reading RTL' section of the gcc docs:
"Correct RTL for a given program is very dependent on the particular target machine. And the RTL does not contain all the information about the program."
Since an LR(1) parse tree of a program should look the same independant of the underlying architecture , I'm going to make the bold assumption that some optimizations take place at the RTL level. This seems very reasonable and is the case in other compilers I've worked with, but since I've never specifically worked with gcc, I'm not 100% sure.
I would imagine there is a way to get gcc to print out the parse tree, rather than the IR, but not being that familiar with it, I wouldn't know what that was. You could always grab the BNF spec for the C grammar and code it up in Bison
Not to spoil it for you or anything, but you really should have at least a *marginal* understanding of optimizing compilers before you go pretending to be an expert.
.s files here, but our old friend the lameness filter clobbered them)
I don't mean to be nasty here, but NOTHING offends me more than an arrogant ignorant person. We all make mistakes, and thats cool, but when you jump down someone elses back with condescending remarks you better be sure that you know what you're talking about.
Without further ado, here are two C programs:
add.c:
main(){ int i; i = 0;i++;}
add2.c:
main(){int i;i = 0;i+=1;}
Now, we compile them using the -S option on gcc (in my case on a SPARC running Solaris, but I'd wager you'd get similar results on just about any supported architecture). So again, we do a:
% gcc -S add.c
% gcc -S add2.c
(I tried to post the
Now, do a 'diff' on 'em. Draw your own conclusions.
You haven't dealt with Sun lately, have you?
/.
They're the 'dot' in
rm -rf
>All the articles posted today are right on par quality-wise with the articles posted every other day!
I have to disagree. By virtue of the fact that they're purely fictious, and invented by the same persons posting about them; the articles posted today have a good deal *more* journalistic integrity than anything else I've ever read on Slashdot.
I'm going to make the brave supposition that quantum computers will overcome the decoherence problem and scale to non-trivial sizes.
(Even if this doesn't happen, the following algorithms still deserve honorable mention for being the first to make use of quantum parallelism to give results unattainable thus far by classical algorithms):
- Shor's algorithm for factoring and discrete log
- Grover's search algorithm
...even moderately offended by the lack of functional languages offered to the contestants?
(I'm (not (one) of those) rabid, foaming LISP advocates) that insists *everything* is better with functional languages... but... I do believe there is a time and place for just about every style of programming. Some of those questions looked very much like the "time and place" for a nice modern functional language like Haskell. Even Scheme would've been nice... Miranda, some flavour of ML... anything.
Perhaps there is some reasoning behind this that I'm missing. I guess I just thought it was sad that the ACM seems to be promoting the view that functional languages are too 'esoteric' even for use in a programming contest.
Amen to that!
Combinator calculus actually has a *practical* application. No kidding. In fact, the whole beauty of combinators is that you can reduce lambda-expressions into a variable-free, but equivalent form (via the `bracket-abstraction' algorithm).
Anyway, the point is, if you're writing the back end for a functional language... wouldn't it be real swell if you all had to implement was two combinators? No dealing with messy variables either. This is exactly the approach taken in the implementation of the functional language Miranda. (Although for reasons of efficiency, there are more than 2 combinators... you *could* use just S and K, but then you get some REALLY HUGE results for even relatively simple lambda-expressions).
So combinatory logic isn't just the domain of Schoenfinkle, Haskell Curry and assorted logic fetishists... it can and has been used for `real life' applications too.
Good point. I should have been more explicit in the parent post that my *only* field of typesetting experience is with very dense mathematics. I took a look through your papers and you seem to be working more on applied aspects of computer science, so it makes sense (to me anyways) that you might not be so interested in a mathematics typesetting package.
If the 'equation density' of one's paper becomes greater than a certain point, the ease-of-use of Microsoft Equation Editor is outweighted by the raw speed of use of TeX. As a bonus, you get very nice looking mathematics too.
Yes there is more of a one-time investment in learning TeX, but after that you become very productive. With LaTeX in particular, the whole point is that you focus solely on content, and let the software worry about presentation. Its got nothing to do with being 'neat' or wanting 'kudos'. It has everything to do with 'how fast, and with how little effort on trivialities, can I produce a mathematics paper that doesn't look like a dog's breakfast?'
>but the only game in town (for mathematics or anything)? No, not really.
I can't speak for general publishing, but for serious math publishing I have to respectfully disagree. If you have ever even remotely come into contact with serious mathematics you will be aware that Springer-Verlag (http://www.springer.de/) is one of the major publishers.
I have never prepared a manuscript for a Springer book or journal that was *not* in TeX format.
Could you give me some examples of the "quite a lot of software used before latex"? Specifically what "math" publishers use standards other than TeX... I'd truly be interested because I've never come across one.
As a side note, please be careful not to confuse LaTeX with TeX. LaTeX (which I admit to using most of the time) is kind of like "TeX for dummies". (Thats not entirely fair... LaTeX makes 95% of what I want to do easier and faster than plain TeX... but for that last 5%, LaTeX makes me want to punch things. LaTeX=easy, TeX=flexible).
>Well tell them than a 24-clause 20-variable 3-SAT problem isn't very hard.
I don't think anyone would argue with you on this point. These are still toy examples... proof-of-principle type stuff. Remember that this result came out of Len Adleman's lab; If you're aware of who Adleman is, then I assume you'll agree its likely he was quite aware of this fact. If you don't know who Adleman is... well, I assume anyone mathematically literate enough to come up with the (quite correct) argument that you made would have to be at least passingly familiar with him.
If you're interested in attacks on DNA computing, I highly recommend reading:
Juris Hartmanis. On the weight of computations. Bulletin of the European Association For Theoretical Computer Science, 55:136--138, 1995.
Its short, but sweet.
As for the "no person could complete by hand" bit; I have to agree with you. The concept of "doable by hand" is pretty ill-defined. In any case, thats not the *real* point of the paper. The point is that the lab tech who implemented the computation did not know the solution a priori. Seems like a pretty obvious control, but so far all previous experiments have been so trivial that a human (or moderately skilled monkey) could trivially see the answer just by looking at them.
Well it certianly isn't the "first" DNA computer to solve a problem. However, it *is* the first one to solve a problem that would be seriously non-trivial for a human to do by hand.
It was definitely 3-SAT; I just spoke with one of the experimenters yesterday.
Its called the 'bootstrapping' problem. Look it up.
>Has anyone proved you can build a Turing machine in DNA yet?
Depends on what you mean by 'building a Turing Machine in DNA'. Your question is rather analogous to saying 'has anyone proved you can build a Turing machine with SDRAM yet?'. DNA is a storage medium and requires external mechanisms to operate on it for computation.
If you take DNA and the DNA-processing mechanisms from stichotrichous ciliates, then yes, you *can* build a Turing Machine. See:
Reversable Molecular Computation in Ciliates. Kari, L., Kari, J., Landweber, L.F., _Jewels are Forever_ (Karhumaki, J. et. al eds.), Springer-Verlag, 1999, pp 353--363
Thats particularly interesting because its _in vivo_ computing, but there are also tens (probably hundreds) of proposals for _in vitro_ DNA computing. Do a google search on 'DNA Computing' and look for the proceedings of the International conferences on DNA-based Computers (I believe the one this summer in Japan is number 8)... IIRC they're published under a DIMACS series. If you want a 'canonical' paper for _in vitro_ methods, I guess starting at the beginning would be the best:
Adleman, L., "Molecular Computation of Solutions to Combinatorial Problems," Science, Vol. 266, 11 November 1994, pp. 1021-1023.
> A fields metal for cold fusion research...
Trolling is more effective if you actually bother to read the parent post first... the post is about scientific research in general. And yes, it is quite possible to make 'outlandish claims' in mathematics. Check out the disturbance Goedel's theorem caused.
Personally, I think mathematics is a science and I didn't want to intentionally exclude it from the discussion by mentioning only Nobel prizes.
Oh, and once again for the record, there is nothing *cold* about the alleged fusion reaction in the story this post is attached to. Please read the Science article. Failing that, at least read the plea to journalists to not call this 'cold fusion'.
>I'm no scientist
I'm not sure what a 'scientist' really is anymore... but I think I play one on weekdays (and particularly productive weekends).
>Dr. Park and his ilk work to make a pariah of any scientist who gives any credence
This is the nature of scientific research. The more outlandish your claim, the greater the feeding frenzy will be if/when you are proven wrong. Of course, if your results hold up... you might get a Nobel Prize (or even a Fields Medal!).
This isn't necessarily a bad thing. In fact, a good scientist is always skeptical... they want to know *all* the details and be thoroughly convinced before accepting a new result. This is healthy and, in my opinion, good for science.
On the other hand, if skepticism is taken too far, it becomes dogma. Dogmatic faith is the antithesis of good science.
Now, I'm in absolutely no position to pass judgement on Dr. Park (I believe I fall into your "young postgrads" category) but personally I could never see myself interjecting a personal opinion of this sort in a scientific context.
If one has an issue with the facts presented in a paper, one takes up those issues explicitly. Innuendo about 'groaning', etc. seems unprofessional and out of place to me. To Dr. Park's credit he *does* make some very good points; most specifically that other respected scientists in the field have been unable to duplicate the results. This is very significant and valid criticism.
In the end, I think the situation is summed up very well by a quote I heard on a TV show once (I think it was 'Law & Order'):
"Scientists have a star system that make Hollywood look like a socialist love-in".
The comment offended me at the time.. but objectively speaking, there is a lot of truth in it.
This is going to be very unpopular (I can feel my karma approaching negative numbers)... but I think it has to be said.
>If you have money, you win.
This is true. You can stick your head in the sand and pretend its not, but the evidence is all around. O.J. Simpson anyone?
On the other hand, why are we surprised? We have *intentionally* built a capitalist society. Many Americans will *proudly* tell you that they are capitalists.
Capitalism works precisely because it starts on the base assumption that humans are greedy and selfish by nature (I'm not knocking Communism, which assumes humans are interested in 'helping their brother', but it has been less sucessful historically).
The most important thing in a capitalist society is... *gasp* CAPITAL! Of course the system favours people with lots of money and large tracts of land... this is by design. Money == Power. Period.
A side effect of this, of course, is that corporations (who have boatloads of capital) end up being far more powerful than individuals. Thats just the way it is.
I'm not saying this is a good thing (personally I find it frightening that big corps have so much power), but I'm not sure there is a lot that can be done about it at this point. You also can't argue that its been rather sucessful. Most Western nations are capitalist to one degree or another (like all things policital, its a spectrum, not an absolute) and the U.S. is one of the 'most capitalist' of the lot. Is it a coincidence that its also so powerful and affluent? (Yes, its an oversimplification, but I think the underlying point is valid).
Bottom line: we can't create a capitalist society and then turn around and pretend to be shocked when we see... a capitalist society.
Well put! Such is the benefit of a pseudo-'constitutional monarchy'.
>The top of the governmental food chain is the queen
;)
Actually, thats not quite correct. H.M. The Queen is our Head of State.
The Right Honourable J. Chretien is our Head of Government.
Personally I'd put the head of government at the top of the 'governmental food chain'.
The Governor General acts in right of Her Majesty the Queen in Canada. And surprisingly has a fairly scary amount of power (e.g. ability to dissolve parlaiment)... though is never able to actually exercise that ability since it would cause an obscene public outrage. It is there though.. just ask Lord Byng
>BTW No, and we don't pronounce it "a-boot" Who started that myth?
You're correct in that we don't pronounce it 'a-boot', but we *do* tend to pronounce 'ou' as a dipthong. The trouble is that when an English speaker who is not accustomed to this phoneme hears it... their brain instinctively maps it on to the closest phoneme that they are accustomed to, which is usually 'oo'.
There is a cute little article on the historical aspects at: http://www.m-w.com/wftw/00may/052200.htm
I have to admit... I never thought I'd see the day that Slashdot became a stratified service site. The same Slashdot that strongly supports free (as in beer) OSes over the more traditional pay type. The same Slashdot where people strongly object to free registration to read NYTimes articles...
Its reasonable, of course. Someone has to pay the bill for bandwidth; and I shudder to think how large that bill would be for Slashdot. I have no objections at all to selling advertising... but to be honest the bit about 'Eventually we intend to offer additional features to subscribers' kinda bothers me.
Lots of people here are big fans of Linux. Do you get 'extra features' if you pay Linus $5/1000 lines of kernel code? Not the best analogy, but this just looks like a slippery slope.
Its not that I have no faith in Slashdot; its just that this scene has repeated itself on SO many once-free websites. It starts with a few harmless extra features for subscribers but the 'free' service eventually erodes into uselessness.
Again, I'm not questioning the addition of ads to generate revenue. I also think its pretty swell that we're being given the opportunity to buy our way out of ads. Its just the extra-feature thing that worries me. It seems so... contrary to the overwhelmingly cyber-libertarian feel of Slashdot.
Slashdot is moving from a fairly egalitarian 'society' to one with a class structure. Who saw that coming?
I figured I'd chime in with my two cents worth since not too long ago I found myself in exactly the same spot as you. I loved mathematics but was very skeptical about being able to make a living doing pure math. Heres what I did:
;) ). I enjoyed TCS so much, in fact, that I ended up doing my Ph.D. in computer science and not mathematics.
;) ).
As an undergraduate I double-majored in pure math and computer science. I took every theoretical computer science course I could get my hands on and by my 3rd/4th year of undergrad I was pretty much doing exclusively math. Yes, 2nd year specifically involved suffering through many 'coding' courses, but in the long run this isn't such a bad thing. A computer is a wonderful tool for a mathematician and knowing how to program one well is actually a very desirable skill (note, I still hated the programming classes
Don't let anyone fool you... theoretical computer science *is* math; and to be honest, its math that I found more interesting than any of my 'pure math' courses. As far as courses, on the math side I took as many abstract algebra courses as I could and on the CS side I focused on automata theory and formal languages (with a good helping of recursive function theory and semantics).
There were a number of posters above who mentioned mathematical biology and bioinformatics. For me, anyway, this was bang on the target. There is a huge need for competent mathematicians who are willing to learn a little bit about biology. We are at the point where biology is beginning the transition from a qualitative to a quantative science and we *need* good models.
Again, don't be fooled into thinking you have to do applied math. Sure, coming up with a model is 'applied' in some sense, but once you have the model you get to investigate it and try to prove properties that you think it has (e.g. recent work involved showing that the gene-descrambling process in hyptochious ciliates is computationally universal. Proving that is fun mathematics).
And of course, once you get a job and a grant, theres nothing preventing you from also researching other topics too (my 'academic hobby' is foundations of mathematics... but you don't get too many grants for that
Job prospects in Computer Science (academically speaking) are good right now; though its certainly tougher as a theoretician than, say, a software engineer. But, if you can market yourself correctly, I think its easier than pure math.
I hope that stream-of-conciousness rambling was of some value to you.