I can see what you mean about the Church-Turing thesis, in that QCs would not likely represent a new model of computation.
However, I don't think you understood my comments on the P=NP question.
First of all, because of the nature of NP, any polynomial solution to an NP-complete problem can be used to solve ALL NP-complete problems (bootstrap method). For instance, earlier this year I saw Steve Cook from the University of Toronto (author of Cook's Theorem which proved the original NP-Complete problem, Circuit Satisfiability) demonstrate how a 3-SAT solution could be used to crack DES in O(n^2) time.
Once one NP-complete problem is solved in polynomial time, the rest will follow like dominoes. Therefore an algorithm that factors large numbers in polynomial time (an NP-hard problem) will immediately mean any known problem in NP will be polynomially solvable.
And since this algorithm theoretically exists for Quantum Computers, all known problems in NP will be polynomially solvable.
But here's the rub: Is it possible that a new class of problems could be discovered that are in NP for QCs, but are not in NP for standard computers?
That is, standard computers do not even have non-deterministic polynomial time algorithms to solve them, but QCs will. I don't know if this is true, but it warrants investigation if no one already has an answer.
I heard about this a couple of years ago and I still have a lot of unanswered questions.
A Pure Math Major I once knew explained to me that Quantum Computers could factor large numbers in polynomial time (a fact the article confirmed). This means RSA would be transparent to anyone with a QC. It seems that any current cryptographic system would suddenly become obsolete, as the computer could simultaneously check every key/password and give you the correct one.
This is almost like proving P=NP (for those of you who don't know any Complexity Theory, encryption and 'one-way' algorithms are possible because we think P=NP is untrue; but it has never been proven). But it's a little bit different.
In a way, it's like defining a new model of computation, the first one since the Turing Machine. (I wonder if this disproves Church's Thesis, which states that the Turing Machine is the most powerful model of computation possible.) It would redefine the boundaries of P and NP. Thus, we may find a new class of NP-complete problems, that would allow the foundation for totally new encryption schemes.
(These schemes would not exist for modern computers, as our current machines would not be able to break the code even WITH the key!)
It's probably a good thing that QCs are a long way down the line. I'm sure it would be easy to interface one to a current computer, and then the Internet, and crack everything on it. How could the transition possibly safely occur, short of dismantling the Internet while everyone buys a new computer?
Note that the difference is over 1.4 billion bytes. (Over a Gigabyte, by any definition).
To me, this is a significant difference, and a flaw in the terminology. As sizes grow, the difference between the standard metric prefix definitions (where mega=1 million and giga=1 billion) will grow exponentially from the actual terms we are using.
I'd also like to see people become more aware of these things and more conscious of using them. There is a lot of terminology confusion in the market.
Modems, historically, have been labelled in 'bit' transmission rates, rather than bytes. It is important to know the difference between 10MB/sec and 10Mb/sec; 10MB/sec = 80Mb/sec
Also, capital M, please. You have 128MB, not 128mb. Small m means 'milli', or one thousandth. Capital M means 'mega'. The metric system is well defined, but these small abuses diminish its worth.
I do recall a small story about 5 years ago on a similar idea.
It sounds like it was a different approach, but some researchers had come up with an idea that could allow over a terabyte of storage on a 'translucent' cube using technology similar to CD ROMs. The data could be accessed by moving lasers to different angles and positions on the surface.
I'm guessing the research didn't pan out, because I haven't heard anything about it since then. But the principle of this story is the same as then: Packing data in three dimensions to allow much greater density.
I think speculation on price and/or specs is premature, since its possible existence is still in question. But I think this kind of technology is inevitable, somewhere down the road.
I think a few people have touched on one of the major issues in all this, and what I think is a failing in the article.
You hear all the time about the shortage of programmers in the industry, and how we are nowhere near saturation. Therefore it doesn't make sense that a part of the workforce is under-utilized.
But the difficulty with those numbers is this: They assess the quantity rather than the quantity of the available positions. I have yet to see any full analysis of exactly what kind of jobs are most in demand (and I don't think the article even tried to address that). Then we can understand who is going to be hired for those jobs.
There exist jobs out there, and many of them, which can be done as well by an 18-year-old as a 48-year-old. So people who are over 35 may find themselves over-qualified for many positions.
I am a co-op student in Canada (Americans read: intern) and I never have trouble finding positions with good companies. But I'm not exactly getting thrown into management level jobs here. But for what I'm doing, I can do it just as well as a far more experienced developer, and my salary is considerably lower. This is the premise that allows co-ops/interns to get jobs in the first place.
I would find the article much more informative if it could relate what jobs the older people are failing to get. Giving preference to younger, lower wage people for, say, basic software testing positions is hardly any surprise. Just like you wouldn't hire a veteran sales rep to stand in the street selling newspapers.
Slashdot Mirror
I can see what you mean about the Church-Turing thesis, in that QCs would not likely represent a new model of computation.
However, I don't think you understood my comments on the P=NP question.
First of all, because of the nature of NP, any polynomial solution to an NP-complete problem can be used to solve ALL NP-complete problems (bootstrap method). For instance, earlier this year I saw Steve Cook from the University of Toronto (author of Cook's Theorem which proved the original NP-Complete problem, Circuit Satisfiability) demonstrate how a 3-SAT solution could be used to crack DES in O(n^2) time.
Once one NP-complete problem is solved in polynomial time, the rest will follow like dominoes. Therefore an algorithm that factors large numbers in polynomial time (an NP-hard problem) will immediately mean any known problem in NP will be polynomially solvable.
And since this algorithm theoretically exists for Quantum Computers, all known problems in NP will be polynomially solvable.
But here's the rub:
Is it possible that a new class of problems could be discovered that are in NP for QCs, but are not in NP for standard computers?
That is, standard computers do not even have non-deterministic polynomial time algorithms to solve them, but QCs will. I don't know if this is true, but it warrants investigation if no one already has an answer.
I heard about this a couple of years ago and I still have a lot of unanswered questions.
A Pure Math Major I once knew explained to me that Quantum Computers could factor large numbers in polynomial time (a fact the article confirmed). This means RSA would be transparent to anyone with a QC. It seems that any current cryptographic system would suddenly become obsolete, as the computer could simultaneously check every key/password and give you the correct one.
This is almost like proving P=NP (for those of you who don't know any Complexity Theory, encryption and 'one-way' algorithms are possible because we think P=NP is untrue; but it has never been proven). But it's a little bit different.
In a way, it's like defining a new model of computation, the first one since the Turing Machine. (I wonder if this disproves Church's Thesis, which states that the Turing Machine is the most powerful model of computation possible.) It would redefine the boundaries of P and NP. Thus, we may find a new class of NP-complete problems, that would allow the foundation for totally new encryption schemes.
(These schemes would not exist for modern computers, as our current machines would not be able to break the code even WITH the key!)
It's probably a good thing that QCs are a long way down the line. I'm sure it would be easy to interface one to a current computer, and then the Internet, and crack everything on it. How could the transition possibly safely occur, short of dismantling the Internet while everyone buys a new computer?
Anyone seen the movie 'Sneakers'?
I'm all in favor of the changes.
When you buy a hard drive that is 20GB, how big is it?
20,000,000,000 bytes? (20*10**9)
21,474,836,480 bytes? (20*2**30)
Note that the difference is over 1.4 billion bytes. (Over a Gigabyte, by any definition).
To me, this is a significant difference, and a flaw in the terminology. As sizes grow, the difference between the standard metric prefix definitions (where mega=1 million and giga=1 billion) will grow exponentially from the actual terms we are using.
I'd also like to see people become more aware of these things and more conscious of using them. There is a lot of terminology confusion in the market.
Modems, historically, have been labelled in 'bit' transmission rates, rather than bytes. It is important to know the difference between 10MB/sec and 10Mb/sec; 10MB/sec = 80Mb/sec
Also, capital M, please. You have 128MB, not 128mb. Small m means 'milli', or one thousandth. Capital M means 'mega'. The metric system is well defined, but these small abuses diminish its worth.
I do recall a small story about 5 years ago on a similar idea.
It sounds like it was a different approach, but some researchers had come up with an idea that could allow over a terabyte of storage on a 'translucent' cube using technology similar to CD ROMs. The data could be accessed by moving lasers to different angles and positions on the surface.
I'm guessing the research didn't pan out, because I haven't heard anything about it since then. But the principle of this story is the same as then: Packing data in three dimensions to allow much greater density.
I think speculation on price and/or specs is premature, since its possible existence is still in question. But I think this kind of technology is inevitable, somewhere down the road.
I think a few people have touched on one of the major issues in all this, and what I think is a failing in the article.
You hear all the time about the shortage of programmers in the industry, and how we are nowhere near saturation. Therefore it doesn't make sense that a part of the workforce is under-utilized.
But the difficulty with those numbers is this: They assess the quantity rather than the quantity of the available positions. I have yet to see any full analysis of exactly what kind of jobs are most in demand (and I don't think the article even tried to address that). Then we can understand who is going to be hired for those jobs.
There exist jobs out there, and many of them, which can be done as well by an 18-year-old as a 48-year-old. So people who are over 35 may find themselves over-qualified for many positions.
I am a co-op student in Canada (Americans read: intern) and I never have trouble finding positions with good companies. But I'm not exactly getting thrown into management level jobs here. But for what I'm doing, I can do it just as well as a far more experienced developer, and my salary is considerably lower. This is the premise that allows co-ops/interns to get jobs in the first place.
I would find the article much more informative if it could relate what jobs the older people are failing to get. Giving preference to younger, lower wage people for, say, basic software testing positions is hardly any surprise. Just like you wouldn't hire a veteran sales rep to stand in the street selling newspapers.