G.H. Hardy (Noted Number Theorist and atheist) got stuck in Denmark once and was forced to take a boat back to England across quite stormy seas. Before going on the boat, however, he sent a postcard to a friend claiming that he had solved the Riemann Hypothesis.
His reasoning? No just God could possibly allow him to drown and receive false credit for proving such a famous hypothesis!
The book "Legends of Caltech" tells of students who played a trick on their math professor as follows:
The Professor (Tom Apostol) gave very carefully scripted lectures designed to end precisely in the time allotted. For a few weeks, each day students would go in the lecture hall before class and 1) Change the clock to run 10-15% faster. 2) Set the clock backwards a few minutes so it caught up at the beginning of lecture. When the Professor (who didn't wear a watch) noticed himself seemingly falling farther and farther behind, he tended to get more and more incoherent as he tried to finish the lecture which he "knew" he had enough time to do.
National Geographic talking about the limitations of the new concept.
"The device can check whether a list of zeros and ones has an even number of ones. The computer cannot count how many ones are in a list, since it has a finite memory and the number of ones might exceed its memory size. Also, it can only answer yes or no to a question. "
Don't computers already have a finite memory? And aren't binary numbers just a long series of yes/no questions?
Let's say you're a firm hoping to make $10,000 in sales in the next month, corresponding to 20,000 Peppercoins. Each peppercoin corresponds to a random variable which is $10 with probability 0.05
Your expected income is in fact $10000 while your standard deviation is 10(20000*.05*.95)^(1/2)=$308 or so. So while the variation is painful, it actually turns out you'll be in the $9000-$11000 range 99% of the time.
Similarly, if you scale down by a factor of 10, so you have 2,000 coins. Your expected income is $1000 while the S.D. is 10(2000*.05*.95)^(1/2)=about $100 or so. The 95% range here would be from $800-$1200, which is more painful but still managable.
The odds of a run of 500 lows in a row is about 7.27*10^-12, safely ignorable
The chicken and egg problem still seems to be around: In order for a company to be able to use micropay, it needs to have transactions occur in sufficient quantity that the law of large numbers applies and the payments average out to the correct amount.
If you're a startup looking selling something like MP3's online, however, then you will most likely start with a small customer base. Should you just hope for the best on those first few hundred transactions?
As an alternative, why not use the ISPs themselves to delete spam? For example, Someone sends out a spam message to 100 million addresses including 10 million AOL users. 100 people on AOL forward the message to a server complaining it is spam. AOL then deletes the message automatically from all the remaining mailboxes and sends a message to the sender explaining what happened.
Of course, it seems likely that spammers would use some sort of random process to make all the messages different, but it would seem to be much more time consuming and difficult.
Slashdot Mirror
"According to sources, the wholesale value of the allegedly pirated music may be as high as $60 million"
Then again, the music could be mostly Backstreet Boys, Brittney Spears, and N'Sync, in which case the value of the music is closer to $60.
G.H. Hardy (Noted Number Theorist and atheist) got stuck in Denmark once and was forced to take a boat back to England across quite stormy seas. Before going on the boat, however, he sent a postcard to a friend claiming that he had solved the Riemann Hypothesis. His reasoning? No just God could possibly allow him to drown and receive false credit for proving such a famous hypothesis!
The book "Legends of Caltech" tells of students who played a trick on their math professor as follows: The Professor (Tom Apostol) gave very carefully scripted lectures designed to end precisely in the time allotted. For a few weeks, each day students would go in the lecture hall before class and 1) Change the clock to run 10-15% faster. 2) Set the clock backwards a few minutes so it caught up at the beginning of lecture. When the Professor (who didn't wear a watch) noticed himself seemingly falling farther and farther behind, he tended to get more and more incoherent as he tried to finish the lecture which he "knew" he had enough time to do.
National Geographic talking about the limitations of the new concept.
"The device can check whether a list of zeros and ones has an even number of ones. The computer cannot count how many ones are in a list, since it has a finite memory and the number of ones might exceed its memory size. Also, it can only answer yes or no to a question. "
Don't computers already have a finite memory? And aren't binary numbers just a long series of yes/no questions?
Is to give you an excuse to avoid work. See http://arxiv.org/abs/astro-ph/9912202 for a paper (in PDF) describing this
Why do I have such a sinking feeling about their endeavour?
Let's say you're a firm hoping to make $10,000 in sales in the next month, corresponding to 20,000 Peppercoins. Each peppercoin corresponds to a random variable which is $10 with probability 0.05
Your expected income is in fact $10000 while your standard deviation is 10(20000*.05*.95)^(1/2)=$308 or so. So while the variation is painful, it actually turns out you'll be in the $9000-$11000 range 99% of the time.
Similarly, if you scale down by a factor of 10, so you have 2,000 coins. Your expected income is $1000 while the S.D. is 10(2000*.05*.95)^(1/2)=about $100 or so. The 95% range here would be from $800-$1200, which is more painful but still managable.
The odds of a run of 500 lows in a row is about 7.27*10^-12, safely ignorable
The chicken and egg problem still seems to be around: In order for a company to be able to use micropay, it needs to have transactions occur in sufficient quantity that the law of large numbers applies and the payments average out to the correct amount.
If you're a startup looking selling something like MP3's online, however, then you will most likely start with a small customer base. Should you just hope for the best on those first few hundred transactions?
As an alternative, why not use the ISPs themselves to delete spam? For example, Someone sends out a spam message to 100 million addresses including 10 million AOL users. 100 people on AOL forward the message to a server complaining it is spam. AOL then deletes the message automatically from all the remaining mailboxes and sends a message to the sender explaining what happened.
Of course, it seems likely that spammers would use some sort of random process to make all the messages different, but it would seem to be much more time consuming and difficult.