Other Gadgets (general gadgets)

[ltl/fb]

Originally posted by Mmmm, Burger (C.J.)
Depends on whether you have to restart the playlist. If I pause it, it shuts off, and will pick up where I left off when I hit play again. On the shuffle, even if I turn it off, it picks up where I left off.

Aaaaah. Thanks! ETA any input on cable phone crap?

[Mmmm, Burger (C.J.)]

Originally posted by ltl/fb
Aaaaah. Thanks! ETA any input on cable phone crap?

I don't think there's much difference btween DSL and Cable these days, so long as you're paying for the same speed level. Question is always reliability.

[Hank Chinaski]

Originally posted by Mmmm, Burger (C.J.)
Depends on whether you have to restart the playlist. If I pause it, it shuts off, and will pick up where I left off when I hit play again. On the shuffle, even if I turn it off, it picks up where I left off.

and I swear the iPod on shuffle plays some stuff twice before it plays others even once. maybe mine is broken.

[Mmmm, Burger (C.J.)]

Originally posted by Hank Chinaski
and I swear the iPod on shuffle plays some stuff twice before it plays others even once. maybe mine is broken.

I have read reports that this happens. Is it possible you already have them in your playlist twice? OR that you're restarting it?

[LessinSF]

http://www.evilmadscientist.com/article.php/cnctoast

Originally posted by Hank Chinaski
pseudo-random is geek-speak that acknowledges the way a processor "picks" a number makes it not truly random. say a program is to "randomly" pick 1 of a set of integers from 1-50. An algorith will typically be set to generate a number that varies and can be random. the number are not integers though. the generated number might be 49.7 and would be rounded to 50. Or it might be 49.2 and rounded to 49. but what if it is 49.5? the program has to have a way to pick- it might go up or down. something like that, anyway, makes it not completely unbiased to the numbers. but it is pretty random.

You can't fake geekitude. Pseudorandom generators are not "pseudorandom" because of rounding issues, nor because they repeat individual elements. They are pseudorandom because the whole sequence of numbers they generate is predetermined based upon some numeric algorithm. (One consequence of this is that the entire sequence will eventually repeat itself, although modern RNGs are are designed with such a long period that repetition should not be an issue in the intended applications.)

Incidentally,

1) The assertion that algorithms for producing a pseudorandom integer "typically" generate noninteger results is incorrect. To the contrary, most of the modern processes are integer processes that need to be manipulated in order to produce a floating point value. It is true that some implementations do that work internally (in which case they are almost always normalized to produce a result in the range (0,1)) and expect the user to convert back to integers as necessary.

2) It is odd in the extreme to suggest there would be some difficulty in "picking" how to round 49.5 (or any other number with 1/2 as the fractional part). The convention that 1/2 rounds up to 1 is for all intents and purposes universally accepted.

3) Having a convention such as rounding up or down is not a "bias" that affects the apparent randomness of a pseudorandom number algorithm unless the algorithm is incorrectly designed.

[Mmmm, Burger (C.J.)]

Originally posted by credit this
You can't fake geekitude.

Well, Hank faked it long enough to get Eva Silverstein's pants down to her ankles. But then she caught on.

[Hank Chinaski]

Originally posted by credit this
You can't fake geekitude. Pseudorandom generators are not "pseudorandom" because of rounding issues, nor because they repeat individual elements. They are pseudorandom because the whole sequence of numbers they generate is predetermined based upon some numeric algorithm.

Which is effectively random. I was only trying to tell Burger iPods are not really random, and can't be.

Of course my knowledge base is limited to preparing about a dozen extremely complex patent applications on the rolling codes for producing "random" numbers in car remote keyless entry systems. I'm sure you have greater expertise.

And since I try patent cases, I know to try to "dumb" down an explaination. My "rounding" example is an accurate problem, but was meant more as something these sheep could understand.

2) It is odd in the extreme to suggest there would be some difficulty in "picking" how to round 49.5 (or any other number with 1/2 as the fractional part). The convention that 1/2 rounds up to 1 is for all intents and purposes universally accepted.

There is no difficulty in so picking, but it makes the process non-random. If you always round .5 up which, integer has a greater liklihood of being picked, 0 or 1? Not. Random.

[Mmmm, Burger (C.J.)]

Originally posted by Hank Chinaski


There is no difficulty in so picking, but it makes the process non-random. If you always round .5 up which, integer has a greater liklihood of being picked, 0 or 1? Not. Random.

Are you dumbing yourself down again?

Take the simple case. There are ten possible decimals.

0.0, 0.1, 0.2, 0.3, 0.4
0.5, 0.6, 0.7, 0.8, 0.9

The first five get rounded down to 0; the second five get rounded up to one. Assuming each is equally likely to be generated by the RNG, how is there a bias?

Of course, you can recreate this precise exercise to an infinite number of decimal places.

Has the Federal Circuit made you patent litigators lazy?

[Hank Chinaski]

Originally posted by Mmmm, Burger (C.J.)
Are you dumbing yourself down again?

Take the simple case. There are ten possible decimals.

0.0, 0.1, 0.2, 0.3, 0.4
0.5, 0.6, 0.7, 0.8, 0.9

The first five get rounded down to 0; the second five get rounded up to one. Assuming each is equally likely to be generated by the RNG, how is there a bias?

Of course, you can recreate this precise exercise to an infinite number of decimal places.

Has the Federal Circuit made you patent litigators lazy?

using standard algorithm protocals ( www.standardrandomgenerators.com ) 0.0 is not a possible result.

[Mmmm, Burger (C.J.)]

Originally posted by Hank Chinaski
using standard algorithm protocals ( www.standardrandomgenerators.com ) 0.0 is not a possible result.

Is 1.0?

[Hank Chinaski]

Originally posted by Mmmm, Burger (C.J.)
Is 1.0?

I believe that was Credit This' gpa in diff Eqs.

[Hank Chinaski]

Originally posted by Mmmm, Burger (C.J.)
Is 1.0?

oh. the real problem with zero would be no -.5, -.4, etc.

Originally posted by Hank Chinaski

Which is effectively random. I was only trying to tell Burger iPods are not really random, and can't be.

Huh? The most random thing here is trying to figure out what you're trying to tell anyone when you say "random" in one sentence and "not really random" in the next.

Originally posted by Hank Chinaski
Of course my knowledge base is limited to preparing about a dozen extremely complex patent applications on the rolling codes for producing "random" numbers in car remote keyless entry systems. I'm sure you have greater expertise.

Apparently so, since I'm right and you're wrong.

Seriously, my experience is limited to amateur coding mostly in jr. high and HS when I had time on my hands, but I do remember how it works.

Originally posted by Hank Chinaski
And since I try patent cases, I know to try to "dumb" down an explaination.

Not to mention spelling.

Usually the goal when simplifying by example is to pick an accurate example.

Originally posted by Hank Chinaski
My "rounding" example is an accurate problem, but was meant more as something these sheep could understand.

By "accurate" you mean "not accurate," right? Baa.

Originally posted by Hank Chinaski

There is no difficulty in so picking, but it makes the process non-random.

No, it doesn't, unless you screw up the algorithm.

Originally posted by Hank Chinaski
If you always round .5 up which, integer has a greater liklihood of being picked, 0 or 1?

They have equal frequency if the numbers that you are rounding are uniformly distributed in the range [0,1). More generally, they have equal frequency in any algorithm that properly maps any uniform distribution range onto a range that is equally distributed around 0.5.

Originally posted by Hank Chinaski
The real problem with zero would be no -.5, -.4, etc.

I never said it was impossible to design a faulty algorithm. Congratulations. My point was that it is easy to write a working algorithm. If, as I think you are suggesting, you have mapped a random number range onto a floating-point range such as [0, 50) then you would simply use a floor function (int()) rather than rounding to map back onto an integer range with the proper uniform distribution.

Originally posted by Mmmm, Burger (C.J.)
Well, Hank faked it long enough to get Eva Silverstein's pants down to her ankles. But then she caught on.

I haven't heard that name in a while. Assuming we are talking about the same person, I can assure you that I have spent considerably more time with her than Hank has. (And nobody's pants were lowered.)