Speaker 1: Brought to you by the reinvented two thousand twelve Camray.
Speaker 1: It's ready. Are you get in touch with technology with
Speaker 1: tech Stuff from how stuff works dot com. Hello again, everyone,
Speaker 1: and welcome to tech stuff. My name is Chris Poette,
Speaker 1: and I am an editor here at how stuff works
Speaker 1: dot com. Sitting across from me, as he always does
Speaker 1: on these occasions, is senior writer Jonathan Strickland. Hey there,
Speaker 1: all right, then, so we have some listener mail to
Speaker 1: start us off. Okay, this listener mail comes from Harry
Speaker 1: from the University of North Carolina, Chapel Hill. He says, Hey,
Speaker 1: as a table top gamer, I have been known to
Speaker 1: generate a few random numbers via my trustee D twenty. However,
Speaker 1: I know computers are able to do this without tossing
Speaker 1: around an ico hay, drawn, Just how do digital randomer
Speaker 1: generator's work and are they truly random? So? D twenty,
Speaker 1: for those of you who are not entrenched in the
Speaker 1: geek world as I am, that is a twenty sided die. Yeah. That,
Speaker 1: As it turns out, that's a far more effective tool
Speaker 1: for generating random numbers than a computer can be. Yeah,
Speaker 1: and uh, here's here's the basics of why that is
Speaker 1: a computer follows instructions. So you have to be able
Speaker 1: to give a computer instructions in order for it to
Speaker 1: do anything. Yes, in order for you to be able
Speaker 1: to tell it to generate a number, you have to
Speaker 1: tell it how to generate that number. And it is very,
Speaker 1: very challenging to create a way to tell a computer
Speaker 1: to generate a number so that that number is truly random.
Speaker 1: And when we're talking about truly random, or it may
Speaker 1: seem that a random number generator that you might use
Speaker 1: online is random, but it's random to you and not
Speaker 1: the computer, depending on what system they're using. Well, that's true,
Speaker 1: but a lot of the ones that I've seen for
Speaker 1: free are using an algorithm to determine a random number. Right,
Speaker 1: And there are a couple of different ways that computers
Speaker 1: tried to generate random numbers. Okay, so in one version,
Speaker 1: the computer actually just has a table of numbers that
Speaker 1: have been pregenerated through some complex means, and that the
Speaker 1: numbers themselves appear to be random because it's a string
Speaker 1: of numbers that don't repeat in any sort of in
Speaker 1: any source of sequence, no matter how long the number is.
Speaker 1: And we're talking about numbers that could have thousands and
Speaker 1: thousands of digits within them, right, I mean it's it
Speaker 1: could be as simple as generating numbers at random and
Speaker 1: making a list, and it's going down and saying, okay, number,
Speaker 1: this is the number, right, three, six, this is the number.
Speaker 1: But it also might also is likely to be using
Speaker 1: an algorithm it says, okay, well, add twenty to this one. Okay,
Speaker 1: at fourteen to this one, add one to that one. Right,
Speaker 1: So you if you know where you are in the sequence,
Speaker 1: you can predict what the next theoretically random number is. Right.
Speaker 1: So if it's if it's the list version that that
Speaker 1: we were talking about before, let's let's make it really simple.
Speaker 1: Let's say you have a list of ten numbers and
Speaker 1: each of those numbers is ten digits long, but the
Speaker 1: digits are apparently random. Yes, all right, so there's no
Speaker 1: like easy sequence to follow with you, and we have
Speaker 1: just completed, Uh, we've just used random number number eight, Okay,
Speaker 1: all right. That means that we would have random number
Speaker 1: number nine and random number number ten, and then it
Speaker 1: would go back to random number number one. So if
Speaker 1: you had the table in front of you, and you
Speaker 1: had you knew how many of those random numbers there were,
Speaker 1: and you knew where it was. In the previous iteration
Speaker 1: of generating a random number, you would know the next
Speaker 1: quote unquote random number. So the number itself may appear
Speaker 1: to be random, but you would still be able to
Speaker 1: predict what it was because you had the list. Right.
Speaker 1: So that's a problem because random numbers are used in
Speaker 1: things like encryption, so you want you want those numbers
Speaker 1: to be as true as close to true random as
Speaker 1: possible so that it is not easy or or preferably
Speaker 1: possible to break that encryption. I think this is a
Speaker 1: good time to introduce two concepts. Okay, uh, that would
Speaker 1: be the the pseudo random number generator, sure, and the
Speaker 1: true random number generator. Right. So true random number generators
Speaker 1: are actually kind of easier to to explain. Yeah, I
Speaker 1: think so too. So a true random number generator is
Speaker 1: something that can generate a random number excluding any minor
Speaker 1: quantum effects that you want to imagine. So let's talk
Speaker 1: about that D twenty. Yeah, that's an excellent example of
Speaker 1: a true random number generator, right when you roll that
Speaker 1: D twenty. Theoretically, anytime you roll that D twenty, there
Speaker 1: should be an equal chance of any number between one
Speaker 1: and twenty popping up as the the eventual result. That is,
Speaker 1: assuming that your D twenty is equally sharp on all sides,
Speaker 1: and I mean the edges are the exact same and
Speaker 1: the surface. That's what I'm talking about, elimiting the quantum effects, Okay,
Speaker 1: because when I when I'm talking about quantum effects in
Speaker 1: this case, I'm talking about things that are so small
Speaker 1: that we can't really observe them anyway. So it doesn't
Speaker 1: you know, if you eliminate all that and you say that,
Speaker 1: with all things being equal, rolling on the same surface
Speaker 1: with a perfectly uh intact D twenty, you should get
Speaker 1: a random result every time you roll it, right, right,
Speaker 1: I have a couple of D twenties that look like
Speaker 1: a dog chewed on them. Yes, and in those cases,
Speaker 1: there might be some numbers that might roll up more
Speaker 1: often than others just because of the shape of that
Speaker 1: D twenty exactly. But a true random number generator would
Speaker 1: not give any preference to any particular result. Uh. Pseudo
Speaker 1: random number generators are different. Yes, they We've already been
Speaker 1: talking about pseudorandom number generators, which is the number generators
Speaker 1: that are using the algorithms or a predetermined list of
Speaker 1: numbers that that are being used to theoretically generate random number. Now,
Speaker 1: the the the algorithms use something called a seedy, and
Speaker 1: a seed is a predetermined figure that gets plugged into
Speaker 1: the algorithm that helps generate the seemingly random numbers. But
Speaker 1: if you know what the seed is, then theoretically you
Speaker 1: can eventually determine what the algorithm is and then break
Speaker 1: the encryption. Now this is this is not as easy
Speaker 1: as I'm making it sound. It's not like this is
Speaker 1: a trivial task. No, No, it's actually incredibly difficult. Yeah,
Speaker 1: as long as uh. I mean, if if you have
Speaker 1: no clue what the seed is or what the algorithm is,
Speaker 1: it's it's going to appear to you to be random, right,
Speaker 1: it's going to seem like an impossible test to break it.
Speaker 1: But if you were to find one of those two elements,
Speaker 1: then theoretically, over several results, you would be able to
Speaker 1: eventually derive the other. You would either be able to
Speaker 1: derive the seed or you'd be able to derive the algorithm.
Speaker 1: And again, this is it's not easy, but it is
Speaker 1: theoretically at any rate possible, which is why you want
Speaker 1: to get as close to a true random number generator
Speaker 1: as possible, because then you can't predict it because it
Speaker 1: is random. Now, what I think is interesting is the
Speaker 1: way again we're talking about when you get back to
Speaker 1: the computers, if you're if you're doing the pseudo random
Speaker 1: number generator, that's a lot easier. Yes, because that's something
Speaker 1: you can do within the realm of computing. Yes, And
Speaker 1: and there are quite a few, as I found out,
Speaker 1: pseudo random number generators available online. You can you can
Speaker 1: say hey, I need a random number, and you can
Speaker 1: go find a website somewhere that will give you something
Speaker 1: that appears to be a completely random number. Yeah. And
Speaker 1: it's um it's a really efficient, is some I mean,
Speaker 1: it doesn't take long at all for a pseudo random
Speaker 1: number generator to come up with a number. True random
Speaker 1: number generators tend to take longer to to generate that number.
Speaker 1: So uh. And when I'm saying longer, I'm talking about
Speaker 1: maybe a matter of seconds. But in computing terms, that's
Speaker 1: an eternity. Now, you would want a true number random
Speaker 1: number generator for for certain tasks, like like a lottery.
Speaker 1: You don't want people to be able to predict your lottery. Um,
Speaker 1: that would be bad because then it would no longer
Speaker 1: be a gamble. Yeah, well those are those are the
Speaker 1: machines that they used to pull the ping pong balls
Speaker 1: out of her true random numbers exactly. So again assuming
Speaker 1: all the ping pong balls are in the same shape
Speaker 1: and blah blah blah, and they are the same weights, exactly. Uh.
Speaker 1: But things like random sampling if you wanted to do,
Speaker 1: if you wanted to do true random sampling, and I
Speaker 1: can give you an example of where this would be
Speaker 1: really important. Excellent airports. Yes, so in an airport security line.
Speaker 1: You know, supposedly airport security are going to single out
Speaker 1: people for random screening. Now to make that truly a
Speaker 1: random event where it's not based upon anyone's appearance, you know,
Speaker 1: you want to take all of that out because you
Speaker 1: don't want to do the profiling thing, because that has
Speaker 1: its own set of problems. If you're truly random, you
Speaker 1: need to have a system that's going to just tell
Speaker 1: you a really random result, like say the third person,
Speaker 1: the third person to go through the line next, that
Speaker 1: will be someone you single out, and then seventh will
Speaker 1: be the next one or whatever. But you would want
Speaker 1: a true random number generator to come up with that
Speaker 1: so that you could show that there was no preference,
Speaker 1: there was no bias that went into that sample. Plus
Speaker 1: it makes it a little more frightening for someone who
Speaker 1: might be thinking about trying something. Is the idea that
Speaker 1: you might be selected completely at random for a check.
Speaker 1: But yeah, it doesn't matter how quote unquote normal you
Speaker 1: look or unassuming you look, you could still be picked indeed. Um.
Speaker 1: Whereas with a pseudo random number generator, you might want
Speaker 1: that for something like if you're uh doing some sort
Speaker 1: of simulation, because it's going to be much more efficient
Speaker 1: and a lot of When we're talking simulation, we're talking
Speaker 1: about simulation of complex systems, like let's say atmospheric systems.
Speaker 1: That's incredibly complex, and if you were to rely on
Speaker 1: true random number generators to generate the numbers you need
Speaker 1: to run that simulation, it would not be nearly as
Speaker 1: responsive as what you would need to to get a
Speaker 1: true simulation. True simulation is kind of a oxymoron, but
Speaker 1: at any rate, um, But there's some really cool ways
Speaker 1: that various organizations and and and mathematicians have come up
Speaker 1: with to try and create as random a number generator
Speaker 1: as possible. Using computers. Yes, I figured, since you just
Speaker 1: mentioned it, the use of atmospheric noise would be a
Speaker 1: good place to start in that it's a random dot org.
Speaker 1: It's a great resource as far as putting this podcast together.
Speaker 1: And yes, yes, definitely, Um, that's that's how they try
Speaker 1: to generate random numbers. Right, So let's say, let's say
Speaker 1: that what they do is it's a combination of the
Speaker 1: pseudo random number generator and the true random number generator method. Uh.
Speaker 1: They use observations of atmospheric phenomena to generate a random
Speaker 1: number and um, and they do that by putting it
Speaker 1: through I suppose it's like putting it through an algorithm.
Speaker 1: But at any rate that they depending on what's going
Speaker 1: on the atmosphere at any given moment, that's what's going
Speaker 1: to generate that random number. Uh. Now, now we start
Speaker 1: to enter a philosophical debate about whether or not that
Speaker 1: atmospheric conditions are truly random. And the reason why there's
Speaker 1: a debate is that there's still a debate on is
Speaker 1: everything deterministic, meaning that things happen and those things cause
Speaker 1: other things to happen, and those things cause other things
Speaker 1: to happen. And if you know the whole system. You
Speaker 1: can predict everything that's going to happen. Versus nondeterministic which
Speaker 1: allows for random occurrences. Fish still not not aplicy I
Speaker 1: knew that was going to happen, so that's real, that's
Speaker 1: not random. Good point. So now in a deterministic system,
Speaker 1: what you could argue is that the conditions of the
Speaker 1: atmosphere are in fact predictable if you know all the
Speaker 1: factors that are going into making that condition. But that's
Speaker 1: if there is a low pressure system. You could say, well,
Speaker 1: you know, there is a good possibility that is going
Speaker 1: to rain today, and so I by that I could
Speaker 1: say it is more likely to rain than not rain
Speaker 1: because the pressure is low. So there are things factors
Speaker 1: taken a new cap, but what about the smog in
Speaker 1: the area, or whether there is dust from any interference
Speaker 1: from electromagnetic radiation Exactly these things can factor into it
Speaker 1: to uh to change the probability that something will happen.
Speaker 1: That's why we're talking about these incredibly complex systems. Now,
Speaker 1: if there were some way for you to know all
Speaker 1: the factors that were going into making the atmosphere behave
Speaker 1: a particular way at any particular time, you could no
Speaker 1: longer say that that was a random number. It's almost
Speaker 1: just an academic argument because there's no way you can
Speaker 1: know all those factors. It's just too complex, and especially
Speaker 1: if you start to pull in things like chaos theory. Now,
Speaker 1: if you've heard of chaos theory, you know that chaos
Speaker 1: theory states that very small events can contribute to enormous events.
Speaker 1: And the thought experiment that is always referred to is
Speaker 1: that a butterfly flaps its wings and John Travolta gets
Speaker 1: a movie no, I'm sorry, tsunami wipes out some city
Speaker 1: somewhere across the world. So the wind uh generated, the
Speaker 1: tiny little movement of air molecules generated by that butterfly's
Speaker 1: wings flapping in Brazil sets off a chain of events
Speaker 1: that ultimately leads to a catastrophically huge weather phenomena somewhere
Speaker 1: across the globe. UH. And of course, not like, not
Speaker 1: like instantaneously. Not I'm not suggesting that Brazilians go out
Speaker 1: in massacre butterflies, but rather that these tiny events are
Speaker 1: what contribute to enormous events. So in that sense, anything
Speaker 1: that's going on in the atmosphere at any given time
Speaker 1: is is the product of so many different tiny factors
Speaker 1: that it's mind boggling right, right, So that uh, it's
Speaker 1: it's so complex essentially then that while it is not
Speaker 1: that is essentially random, right, it may or may not
Speaker 1: be truly random. But one, we are not capable of
Speaker 1: knowing that because it's so complex. And two it doesn't
Speaker 1: matter because we're not capable of knowing that. So even
Speaker 1: if even if you were to somehow philosophically argue that
Speaker 1: it's not truly random, it's as close to truly random
Speaker 1: as it needs to be, or in order for us
Speaker 1: to go ahead and say, you know, it's just an
Speaker 1: academic argument. Um, And that's not the only the the atmosphere,
Speaker 1: observing the atmosphere is not the only method that people
Speaker 1: have used to try and generate a random number. No,
Speaker 1: not at all. And it's um. And as a matter
Speaker 1: of fact, the one I think you were thinking of
Speaker 1: would be, uh, the quantum mechanics version of determining random numbers.
Speaker 1: That one that was a cool one. It's a really
Speaker 1: cool idea. Uh, we're talking about by using particles that
Speaker 1: are smaller than an atom to determine the randomness of
Speaker 1: an event or in this case, generate random numbers. Yeah,
Speaker 1: we're talking here about these quantum particles are behaving in
Speaker 1: a way that we cannot predict at this time. Now, again,
Speaker 1: this could mean that either the quantum particles behave in
Speaker 1: a truly random fashion, or it may mean that we
Speaker 1: don't understand them well enough to be able to recognize
Speaker 1: the patterns or a series of events that are going on.
Speaker 1: Or it may be that we we just don't have
Speaker 1: the instruments capable of measuring that. So it may be
Speaker 1: that the behavior is in fact predictable if we have
Speaker 1: enough information instant of enough uh instruments. But as it
Speaker 1: stands right now, it appears to be completely random. So
Speaker 1: if you base a random number generator off of quantum events,
Speaker 1: then you would get results that to us appear to
Speaker 1: be completely random, and you could generate enormous numbers, I
Speaker 1: mean numbers that are so big that you know you
Speaker 1: you would if you were to try and write one
Speaker 1: down on a sheet of paper, would take up the
Speaker 1: entire sheet and and it would have no apparent repeating
Speaker 1: integers at all. As you're going through there. Um Yeah,
Speaker 1: hot fits actually is a website um a project from
Speaker 1: a an organization in Switzerland Formulab, and UH they have
Speaker 1: connected a Geiger Mueller tube to a computer to basically
Speaker 1: UH their drag racing decaying atoms. Right, because adams decay
Speaker 1: at an unpredictable rate, right, So that so by measuring
Speaker 1: the decay rate, UH, that can in turn generate a
Speaker 1: random number. Yeah, they take two, they take a pair
Speaker 1: of decaying atoms and UH basically when when when one
Speaker 1: of them decays and and releases particles, then that helps
Speaker 1: them generate random numbers. And pretty amazing stuff really to
Speaker 1: to be measuring that and to be using that for
Speaker 1: a number. But the thing is, as as Jonathan mentioned earlier,
Speaker 1: it is not something that happens very quickly. You have
Speaker 1: to submit a series of numbers. You say, I want
Speaker 1: fifty six random numbers, and they have to be no
Speaker 1: larger than you know, forty three digits long, and things
Speaker 1: like that. You have to you have to program this
Speaker 1: in advance, and they will return and set of numbers
Speaker 1: to you. But it will not happen instantaneously. Now do
Speaker 1: you know what my favorite, uh version favorite way of
Speaker 1: generating random numbers is? What's that? My favorite one was
Speaker 1: a project and unfortunately don't have the name in front
Speaker 1: of me. But my favorite one was a project where
Speaker 1: it was using a webcam pointed at a lava lamp
Speaker 1: and by measuring the shapes of the lava quote unquote
Speaker 1: in the lava lamp, it generated random numbers. So the
Speaker 1: yes as the lava lamp, as the the wax inside
Speaker 1: the lava lamp changed shape, the webcam would measure that,
Speaker 1: you know, it would get an image of it, and
Speaker 1: it would be analyzed by the computer to create a
Speaker 1: random number. And because the shape was constantly changing, you
Speaker 1: could generate random numbers at any given time. And I
Speaker 1: love that. The simplicity and the elegance of it is amazing.
Speaker 1: Oh yes, so you've got it in front of you. Yes,
Speaker 1: I don't have my glasses on, so I can't read it.
Speaker 1: Lava Lava RAND, Lava RAND, Yes, l A v A
Speaker 1: r n D. That project is still still exists, although
Speaker 1: they are no longer generating random numbers based off lava lamps.
Speaker 1: As far as I understand, that's pretty neat. Though I
Speaker 1: had never heard of it before. Now it is a
Speaker 1: neat neat concept. I thought that was you know again,
Speaker 1: mathematicians are wacky, crazy, awesome people and we're talking about
Speaker 1: like mathematicians, who are you know, studying math for things
Speaker 1: like number theory. Yes, stuff that's so far beyond my understanding,
Speaker 1: as the Aida Love Lace podcast illustrated to Great Lakes. Um.
Speaker 1: But yeah, that these are the folks who are are
Speaker 1: coming up with the various theories about how to generate
Speaker 1: random numbers if in fact it is truly possible. Yes,
Speaker 1: and I think that their work proves that our days
Speaker 1: are numbered. Well, with that, how about we move on
Speaker 1: to a little listener mail? Is it? This really isn't
Speaker 1: listener mail. This is a message that comes to us
Speaker 1: courtesy of our Facebook group. So, uh, Elizabeth, Elizabeth, we're
Speaker 1: gonna call this Facebook facts and then uh putting put
Speaker 1: in the sound of a hand slapping someone's face. Owl.
Speaker 1: So this comes from Dan, and Dan says, uh, says,
Speaker 1: how about late a history of broken English and long
Speaker 1: forgotten keyboard keys. I would like to see how it
Speaker 1: came about. Also popular terms like pound. Thanks all right, Dan,
Speaker 1: So you're talking about let speak leap being short for
Speaker 1: elite and really this kind of grew out of the
Speaker 1: bulletin board system culture. So you had on bulletin board systems,
Speaker 1: you normally had not Normally, a lot of bulletin boards
Speaker 1: had multiple um levels of access, and there might be
Speaker 1: a general access where you can log in and you
Speaker 1: can access certain things that everyone has access to. But
Speaker 1: then you might have to pay or be invited to
Speaker 1: become part of a more restricted access community, and that
Speaker 1: might get you stuff like access to two different files
Speaker 1: or games or whatever. And because you're part of an
Speaker 1: inner community, you of course would began to develop a
Speaker 1: sense of elitism because that's just that's kind of how
Speaker 1: we humans work. Well, yes, we uh, we do tend
Speaker 1: to enjoy being part of an exclusive club. Yes, and uh.
Speaker 1: When you are part of an exclusive club and you're
Speaker 1: interested in being part of an exclusive club, you might
Speaker 1: try to find ways to maybe disguise what you're doing
Speaker 1: so that not everyone could find it via simple keyword search. Right,
Speaker 1: So you start to develop your own language, and we
Speaker 1: see this across human societies outside of the computer realm,
Speaker 1: of course. Well slang, I mean, if you find a
Speaker 1: slang dictionary and and the slang terms go from generation
Speaker 1: to generation and region the region, and region the region.
Speaker 1: So you might find a certain group has their own
Speaker 1: kind of vocabulary. Well, the same thing with lead speak.
Speaker 1: Lead speak, as Chris was pointing out, part of it
Speaker 1: was to kind of obvious skate what they were talking
Speaker 1: about so that you couldn't easily find it with a search. UM.
Speaker 1: This was particularly important if they were trying to share
Speaker 1: things like software that had been under copyright. If you
Speaker 1: had an a copy of a program and you had
Speaker 1: cracked it so that you didn't need any kind of UH,
Speaker 1: there was no longer any DRM attached to it, there
Speaker 1: was no sort of copy protection attached to it, and
Speaker 1: you wanted to share this with all of your lead friends,
Speaker 1: but you didn't want people to figure out that you
Speaker 1: were doing something illegal. You might go through and change
Speaker 1: a few little figures, a little some of the letters
Speaker 1: to different symbols so that you know, you could still
Speaker 1: read it, because the you know, we look at it
Speaker 1: and we're like, okay, well that that that UH dollar
Speaker 1: sign is supposed to stand for an S or three
Speaker 1: for any yeah, or five for an s um or
Speaker 1: four for an A, that kind of thing. But you know,
Speaker 1: if you were to search for that term, it wouldn't
Speaker 1: come up because the computer doesn't know that the uh
Speaker 1: the symbols are standing in for letters UH that that's
Speaker 1: a human thing. That's one of those things that humans
Speaker 1: do really well that computers don't do well unless you
Speaker 1: go through in program and a whole new database of words.
Speaker 1: I mean, anybody who's who's done the sorry, go ahead,
Speaker 1: anyone who's done the the calculator thing where you type in,
Speaker 1: you know, certain numbers and then flip it over and
Speaker 1: realize that they look a lot like you know, the
Speaker 1: numbers actually look sort of like a word. You can
Speaker 1: spell very few simple words using a calculator, but um,
Speaker 1: you know, it's it's instantly recognizable to somebody who has
Speaker 1: a grasp of the language, which is why a lot
Speaker 1: of the words that they used gradually shifted from just
Speaker 1: using numbers in place of letters to actually being spelled
Speaker 1: differently as well. Right, uh so the first lead speaks
Speaker 1: probably there for again, off you skate what they're doing.
Speaker 1: But then it kind of came a way to communicate
Speaker 1: with other LEAK members and to exclude neubs, the new folks,
Speaker 1: even if you were in the public areas, because the
Speaker 1: new folks were they were it was completely foreign to them.
Speaker 1: And so if you first start looking at a page
Speaker 1: of Lead speak and you're not familiar with. It just
Speaker 1: looks like gibberish at first glance. You know, you actually
Speaker 1: have to take an effort to kind of say, oh, wait,
Speaker 1: that symbol probably means a you, and that one looks
Speaker 1: like an S, so that's a nest, you know, and
Speaker 1: a casual glance it looks like it's meaningless, which it
Speaker 1: serves the purpose of the lead group very well. But
Speaker 1: then they started to do other things, because these are
Speaker 1: the same sort of folks who kind of have a
Speaker 1: mischief streak a mile wide, and so they began to
Speaker 1: incorporate things like common typos. Typos would become the the
Speaker 1: typo version of a word would become the official version
Speaker 1: of a word, which is why you would see things
Speaker 1: like t e H standing in for the so and
Speaker 1: and you. Misusing words on purpose also became very common,
Speaker 1: so it began to develop its own grammar. So, for example,
Speaker 1: instead of instead of using awesome as a a an adjective,
Speaker 1: you'd use it as a noun and call it too awesome,
Speaker 1: that is too awesome, and uh, things like pooned that
Speaker 1: of course came from the TYPEO version of owned and you,
Speaker 1: you know, owning as in I owned him. In this argument,
Speaker 1: I completely dominated him by showing him that he is
Speaker 1: stupid and is a poor debater, and I am awesome
Speaker 1: and he is not, or I am too awesome and
Speaker 1: he is not um so I pooned him. And most
Speaker 1: of the lead speak is based off one of these
Speaker 1: two things, or or a combination of the two, where
Speaker 1: you substitute a letter for either a symbol or a number,
Speaker 1: something that that resembles it physically but is not it,
Speaker 1: or it is some sort of misspelling or TYPEO version
Speaker 1: of the original word. And I mean most of it
Speaker 1: can be can be pretty easily translated if you if
Speaker 1: you just give yourself a little time. Sometimes if they
Speaker 1: get really, really, really complex, it gets to a point
Speaker 1: where you're like, uh, now, certain symbols are standing in
Speaker 1: for entire um are symbols are standing in for an
Speaker 1: entire syllable? Right? And then some of the others who
Speaker 1: were really into lead speak also incorporated. You could also
Speaker 1: make a t out of certain lines on the keyboard,
Speaker 1: making it a little bit even more obfuscatory, could even
Speaker 1: could tell you'd have to really scrutinize it to go,
Speaker 1: oh wait, those three characters are making up another letter
Speaker 1: for let's say that you wanted to use, use the
Speaker 1: ampersand to stand for the sound and okay, and then
Speaker 1: you put a B in front of it, so it's
Speaker 1: be ampersand and it's banned, right, so you can say, I,
Speaker 1: you know, don't do that, you'll get banned be ampersand
Speaker 1: meaning that, Well, if you really want to go even
Speaker 1: one step further, you would not even use the ampersand
Speaker 1: you would use the seven, which of course is the
Speaker 1: same key that the ampersand is found on, so B
Speaker 1: seven would stand for band. So now now you've gone
Speaker 1: from just replacing letters to actually creating a little minor
Speaker 1: bit of a cipher. Um. It's a pretty simple cipher,
Speaker 1: but it can be very confusing to someone who has
Speaker 1: never encountered it before. Yep, yep. And gradually more people
Speaker 1: became acquainted with it as uh the lead people with
Speaker 1: lead skills UM started playing games online, and they would
Speaker 1: start using lead language in the communication part of the
Speaker 1: game when you were typed comments along with the game. Uh,
Speaker 1: you know, and could interact with the other players online.
Speaker 1: And then uh, from the research I did on it,
Speaker 1: apparently the the comic Mega Tokyo basically made it more
Speaker 1: even more of a popular phenomenon to to speak lead um,
Speaker 1: just to bring it out that much on the open, which,
Speaker 1: of course, for the people who are truly lead uh
Speaker 1: probably drove them absolutely bonkers because suddenly they were no
Speaker 1: longer exclusive, right yeah, so, and of course now it's
Speaker 1: it's pretty much just common parlance on a lot of
Speaker 1: the web, where you know, it's almost it's almost just
Speaker 1: become a parody of itself, um, which is kind of
Speaker 1: funny because it was already sort of the parody at
Speaker 1: any rate. That's pretty much the lowdown on lead speak
Speaker 1: and uh and and why people funny yep. Uh. If
Speaker 1: you have any questions that you would like to pose
Speaker 1: to the tech Stuff group, the grouping Chris um, you
Speaker 1: can do so at our email address, which is tech
Speaker 1: Stuff at how stuff works dot com, or like Dan,
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Speaker 1: that information at our handy dandy PostScript announcement done by
Speaker 1: our very own Chris Pallette. Hey. Then in the meantime,
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