Speaker 1: Still get in touch with technology with text stuff from
Speaker 1: com Hey everyone, and welcome to text stuff. I'm I'm sorry,
Speaker 1: there's a little bug in my throat Jonathan Strickland and
Speaker 1: I'm Lauren focal Bomb. You know, I've just been having
Speaker 1: trouble all the day, Lauren. It just feels like something
Speaker 1: very basic and the very code of me is just
Speaker 1: not right. And now everything's just diligion all over the blade,
Speaker 1: almost as though there's there's some kind of a programming
Speaker 1: error or not error but over sight. Yeah, like like
Speaker 1: someone to cut short and now things aren't working. Also
Speaker 1: building up to something terrifying. Yeah, it's gonna build up
Speaker 1: to a NonStop replay of Prince over and over again,
Speaker 1: which it starts out awesome, but as it goes on,
Speaker 1: let me tell you that gets old. Okay, we're talking
Speaker 1: about a Y two K bug obviously, people, Yes, yes,
Speaker 1: that is what our episode is about. To day, all
Speaker 1: of our fans who hate it. Whenever I do cheesy humor,
Speaker 1: I apologize, You don't really apologize. It is who I am.
Speaker 1: So the reason why we're talking about Y two K
Speaker 1: bug years after the whole issue happened is because you know,
Speaker 1: we ask you guys what you want to hear. And
Speaker 1: in this case, a listener named James sent us a
Speaker 1: message on Twitter and said, hey, guys, you should do
Speaker 1: an episode on the Y two K Bug. Heart heart James. Well, James,
Speaker 1: we heart heart you two. Now we're going to do
Speaker 1: our episode on the Y two K Bug. It's a
Speaker 1: pretty interesting story because it's one of those things where,
Speaker 1: you know, it really illustrates a few basic things about
Speaker 1: computing and human nature in general. One of those things
Speaker 1: is that when something new is created, no one who
Speaker 1: is around has any idea of how long it's gonna last,
Speaker 1: and they don't have any any appreciation of things that
Speaker 1: they do then lasting into well into the future, right, well,
Speaker 1: especially things like computer programming. I mean, no one in
Speaker 1: say the nineteen sixties or seventies was expecting any of
Speaker 1: the programs that they were writing to last for forty years. Yeah,
Speaker 1: computers were developing very quickly, and the general thought was that,
Speaker 1: you know, this is changing so fast that programming is
Speaker 1: going to change in at a crazy speed too. But
Speaker 1: as it turns out, while the hardware changed, the practices
Speaker 1: that were established early on remained pretty much standard, and
Speaker 1: also a lot of this old programming would find its
Speaker 1: way into subsequent generations of software. So even if it
Speaker 1: wasn't something that people were continuing to do later on, uh,
Speaker 1: there'd still be these old fragments of code incorporated into
Speaker 1: stuff that did have it. Now we're kind of dancing
Speaker 1: around what that old thing was. Oh, oh, the old thing,
Speaker 1: of course being I just got really excited that I
Speaker 1: knew the answer to this um being the digits in
Speaker 1: the year. Yeah, So here was the issue back in
Speaker 1: the fifties and six these when programmers were having to
Speaker 1: put a code in for the year, which is important
Speaker 1: for certain types of calculations, right, anything that's time based, obviously,
Speaker 1: you need to have a way of recording the time
Speaker 1: so that you can compare times from different points and
Speaker 1: draw your calculations based on that. You know, for for
Speaker 1: for example, when people have been depositing paychecks or right,
Speaker 1: so if you if you have a bank account that
Speaker 1: has interest, for example, time is obviously a factor there.
Speaker 1: It's not just the amount of money that you've been
Speaker 1: continuously putting into or taking out of that bank account.
Speaker 1: It's also the amount of times since you established that
Speaker 1: bank account. And there's some complicated calculations that are very
Speaker 1: time sensitive, so you have to have that kind of
Speaker 1: stuff built into your algorithm, right right, Or in other cases,
Speaker 1: you know, records of dates of birth or dates of
Speaker 1: medical surgery or all kinds of things. Yeah, so many
Speaker 1: different applications, to the point where there were even technologies
Speaker 1: that you wouldn't imagine would ever need to know what
Speaker 1: year it is that had the stuff built into it.
Speaker 1: And here's the problem when you have two digits for
Speaker 1: your year. See the computer programming getting started in the
Speaker 1: nineteen fifties and nineteen sixties, they figured, hey, we've got
Speaker 1: practically half a century before we have to worry about
Speaker 1: two digits turning into zero zero. Clearly we're gonna totally
Speaker 1: fix this later. And computer memory right now is incredibly expensive,
Speaker 1: so let's let's let's be really conservative and just use
Speaker 1: two digits for the year, and we'll be fine until
Speaker 1: these other problems work themselves out. Oh and and I
Speaker 1: mean computer memory was so precious and saving especially across
Speaker 1: the course of for example, an entire spreadsheet full of
Speaker 1: interest calculations, saving two digits per year was big. So
Speaker 1: so just by doing a month, month, day, day, year, year,
Speaker 1: you know, just just the two digits each, you could
Speaker 1: save a huge time and hassle for yourself at the
Speaker 1: at that current moment, right right, because I mean, you know,
Speaker 1: think about just a few years ago how expensive it
Speaker 1: was to buy say a terrabyte for a hard drive,
Speaker 1: compared to today. Now it's much more affordable. Oh well,
Speaker 1: you know, as as opposed to when I was a kid,
Speaker 1: when a tearabyte was and a completely unimaginable amount of information. Yeah,
Speaker 1: when I was a kid, I couldn't imagine ever filling
Speaker 1: up a megabyte of space. So you know, as time
Speaker 1: has gone on, memory has become less and less of
Speaker 1: a problem in the sense that we were able to
Speaker 1: make more of it more affordably. But back then very
Speaker 1: expensive and precious stuff that you only had so much
Speaker 1: to work with, and it was expensive to use. So
Speaker 1: cutting it down to two digits made sense of the time.
Speaker 1: But the problem was that when you roll over from
Speaker 1: nineteen nine to two thousand, in the computer terms, it
Speaker 1: goes from n to zero zero, which meant that people
Speaker 1: weren't really sure what was going to happen. Right, Would
Speaker 1: the computer think that it was all of a sudden
Speaker 1: would that completely bark all of your calculations for for example,
Speaker 1: interest rates, yeah, or the the age of a person.
Speaker 1: So your example, if it's figuring out the age by
Speaker 1: subtracting the current date from your date of birth, or
Speaker 1: the date of birth from the current data, I should say, so,
Speaker 1: let's say it's ninety nine and you were born in ninety.
Speaker 1: Then that's pretty easy. It's years old. Okay, got it.
Speaker 1: But then let's say it goes zero zero and you
Speaker 1: were born in ninety, so it's zero zero minus ninety. Suddenly,
Speaker 1: like oh um am, I getting negative numbers because now
Speaker 1: a negative age that doesn't make sense. And so you
Speaker 1: can have all sorts of computer problems, ranging from the
Speaker 1: financial industry to health to all pretty much everything that
Speaker 1: had any sort of code in it that included the year,
Speaker 1: which extends to things like like elevators that had microchips. Yes, yeah, elevators.
Speaker 1: I mean that's pretty that that was a real concern.
Speaker 1: People are like, I do not want to be in
Speaker 1: an elevator on New Year's Eve because you don't know
Speaker 1: if that thing is going to make it to the floor.
Speaker 1: You want by two, right, And I mean, and of course,
Speaker 1: you know, they weren't afraid that the elevator was going
Speaker 1: to slow down to a rate, to a negative motion
Speaker 1: rate or anything like that. But they were afraid that
Speaker 1: the code and the microchip crashing would I don't know,
Speaker 1: cause a fire and make the elevator drop or just
Speaker 1: or just stop or just stop entirely, and refused to open.
Speaker 1: People had a lot of just uncertainty about exactly what
Speaker 1: was going to happen to code and whether or not
Speaker 1: it was going to crash an entire system. When this
Speaker 1: this year changed, over right, and so this this fear
Speaker 1: started to kind of rear its head in the ninety nineties. Uh,
Speaker 1: it really reached a fever pitch in nine. That was
Speaker 1: when I think the general public became really aware of it.
Speaker 1: Before that due to media complete over saturation. Yeah, yeah,
Speaker 1: I got a little, a little crazy, a lot crazy,
Speaker 1: depending upon where you lived in the United States, it
Speaker 1: certainly became crazy. So you had you had the computer
Speaker 1: scientists who were and programmers who were saying earlier than this, like, hey, guys,
Speaker 1: maybe we should should fix this. This is you know,
Speaker 1: this is a problem, and instead of perpetuating it across
Speaker 1: multiple industries at infinitum, maybe we should address it. And
Speaker 1: that way just establish a new rule going forward. Now,
Speaker 1: computer memory not such a big deal, Now, why don't
Speaker 1: we Why don't we fix it before we get Hello? So, anyway,
Speaker 1: is this thing on? Hello? And the problem was that
Speaker 1: a lot of people didn't listen until it started getting
Speaker 1: closer to two thousand, and people began to really worry
Speaker 1: about the possibility that this could bring about, if not
Speaker 1: some sort of technological armageddon, at least a lot of
Speaker 1: glitches and problems that could have been avoided. So then
Speaker 1: they had to say, well, what are we going to
Speaker 1: do about it? The obvious solution was also the most
Speaker 1: time consuming and expensive one, which was the manually go
Speaker 1: through and start updating code and changing it so that
Speaker 1: it's a four digit year instead of a two digit
Speaker 1: year and uh and then thus increasing the usefulness till
Speaker 1: at least nine thou right, Yeah, I mean, I mean,
Speaker 1: you know, the alternate there's to recode just so that
Speaker 1: programs would recognize that zero zero probably meant two thousand
Speaker 1: instead of nineteen hundred. But that's a less effective solution.
Speaker 1: And b I mean, you just need to change it
Speaker 1: over at the next and of the century, not that
Speaker 1: probably those same programs were going to be in use,
Speaker 1: but you never know. The thing is that, you know,
Speaker 1: you have these legacy systems that certain companies rely on
Speaker 1: that were originally programmed, you know, thirty forty years ago,
Speaker 1: and you know they continue to rely on them because
Speaker 1: they do exactly what the company needs them to do,
Speaker 1: right and Okay, so so either way, these changes might
Speaker 1: have to be entered by hand thousands of times or
Speaker 1: hundreds of thousands of times in a single program um,
Speaker 1: and each change then has to be tested against errors.
Speaker 1: Of course, eventually code was developed to help automate the process,
Speaker 1: but you know, I mean it was just a big undertaking. Yeah.
Speaker 1: You might remember if you watch the documentary Office Space
Speaker 1: that the characters at in a tech the company and
Speaker 1: office space where they that was their job. They went
Speaker 1: into other companies and helped update their code to meet
Speaker 1: the y two K issue, which kind of raises another question,
Speaker 1: which is what was this company going to do after
Speaker 1: or the year two thousand. But at any rate, that
Speaker 1: was actually a very real concern. I mean, The Spaces
Speaker 1: is a great parody of all of that kind of sure,
Speaker 1: but but there was a concern that you know, with
Speaker 1: with all of these extra programming jobs that were going
Speaker 1: to be created, that that businesses would crash and burn,
Speaker 1: and some of them did. I mean, most of them
Speaker 1: just moved on to other things and found freedom and
Speaker 1: not having to do this incredibly tedious work anymore. Right,
Speaker 1: And then there was a lot of other crashing and
Speaker 1: burning in the tech industry for unrelated reasons. Yes, that
Speaker 1: was the whole dot com bubble burst, but it didn't
Speaker 1: have anything to do with Y two K directly. So, uh,
Speaker 1: here's the other problem is that a lot of these
Speaker 1: programs didn't recognize even if even if two thousand was
Speaker 1: going to be fine, even if they could recognize the
Speaker 1: fact that was two thousand was a four digit year,
Speaker 1: they didn't necessarily recognize that two thousand was going to
Speaker 1: be a leap year. Right, And here's the reason why.
Speaker 1: So leap years actually follow an algorithm, a set of rules. Obviously,
Speaker 1: so the the basic rule is that for every four years,
Speaker 1: you added an extra day, a leap day, at the
Speaker 1: end of February to balance out the calendar year with
Speaker 1: the solar year. Because the solar year is close to
Speaker 1: three hundred sixty five point to five days, not quite
Speaker 1: point to five, almost point to five, which is important. Yeah,
Speaker 1: so if you stretch out over an incredibly long time
Speaker 1: for us humans, let's say a few centuries, your calendars
Speaker 1: will start to become misaligned because it's not quite three
Speaker 1: hundred sixty five point to five days in the solar year.
Speaker 1: So that means that occasionally you have to ignore the
Speaker 1: leap year. And the way the rule goes is that
Speaker 1: if the let's see if I can get this right,
Speaker 1: if the century is divisible by one hundred but not
Speaker 1: by four hundred, it would not be a leap year.
Speaker 1: So if it's divisible by both one hundred and four hundred,
Speaker 1: it's a leap year. So, in other words, sevent hundred,
Speaker 1: eighteen hundred, and nineteen hundred were not leap years. Was
Speaker 1: because sixteen hundred is divisible by four hundred. Two thousand
Speaker 1: also divisible by four hundred, so it should be a
Speaker 1: leap here. However, because you gut just have zero zero
Speaker 1: as the digits, if the computer thinks it's nineteen hundred,
Speaker 1: the computers also knows the rule that nine is not
Speaker 1: a leap year, so so it says, hey, this, this
Speaker 1: big zero kind of number is totally not a leap year, right,
Speaker 1: So it's only three days not three hundred, you know,
Speaker 1: three and we we don't have a fevery twenty nine
Speaker 1: this year, is what I would say. But there was
Speaker 1: totally a fevery twenty nine here, which meant that other
Speaker 1: calculations would get thrown off because it wouldn't take that
Speaker 1: leap day into account. So all these calendar applications weren't
Speaker 1: also had to be corrected. So suddenly people were like,
Speaker 1: oh boy, this is a big old mess here. We've
Speaker 1: got to fix this and uh and so, so a
Speaker 1: lot of time and effort and attention was directed to this.
Speaker 1: And there was a third problem as well. Wasn't there
Speaker 1: having to do with all of the nines? Oh yeah,
Speaker 1: Oh I totally forgot about that. I'm glad you brought
Speaker 1: that up. Yes, So, okay, in the old days, children
Speaker 1: gather around this, gather around the digital fireplace, you know,
Speaker 1: if Netflix still has that digital fireplace, ahead and start
Speaker 1: started up back in the old days, children Sometimes programmers,
Speaker 1: in order to designate the end of a program, would
Speaker 1: just type out a string of nines. It was essentially
Speaker 1: just the code to say this is where stuff ends, y'all.
Speaker 1: Uh so had a date in Exeptember nine that if
Speaker 1: you were to write it would be like n a
Speaker 1: lot of nines. And the worry was that certain programs
Speaker 1: which would see that as meaning this is where stuff
Speaker 1: stops and would stop working. So you had a lot
Speaker 1: of digit problems here. So some of this you could
Speaker 1: count on, you know, just a a kind of a
Speaker 1: jerry rigged system of this is how I'm going to
Speaker 1: designate this is the end of a program, and it
Speaker 1: was just kind of arbitrarily chosen that would be stuff.
Speaker 1: Some of it was more of a practical consideration, the
Speaker 1: idea of we need to save time and money, so
Speaker 1: therefore we're shortening this year to two digits. In either case,
Speaker 1: it ended up meaning lots and lots of for people
Speaker 1: in the late nineteen nineties, and um, you got a
Speaker 1: lot of attention. I mean there were there were things
Speaker 1: like uh, industries that were already taking advantage of the
Speaker 1: time in the nineties to address this. The software industry
Speaker 1: was way ahead of the game. Oh yeah, yeah, I
Speaker 1: mean back by you know, I think six uh, a
Speaker 1: few people were on top of it. Certainly by a
Speaker 1: lot of people had already kind of corrected the problem, right,
Speaker 1: So the software that was being produced from that point
Speaker 1: going forward had already addressed it. Now. Granted there was
Speaker 1: still software that was out previously that had this old
Speaker 1: code in it, but the new code coming out of
Speaker 1: the software industry had had adjusted for this kind of problem.
Speaker 1: But there were other industries that were lagging behind. And
Speaker 1: in fact, according to one study, UH, the cap Jimini
Speaker 1: America consulting firm did a study. They found that the
Speaker 1: state and federal government systems were the furthest behind. And
Speaker 1: when you think of all the information that state governments
Speaker 1: and federal government here in the United States requires to
Speaker 1: operate things like taxes that are dependent upon infrastructure. Infrastructure, yeah,
Speaker 1: your water systems, all sorts of stuff that rely on
Speaker 1: computer systems that are run by satellites, all all of
Speaker 1: the stuff, communications, everything. I mean, there's entire industries that
Speaker 1: are dependent either completely or in part on state and
Speaker 1: federal systems. All of those were at risk because they
Speaker 1: were the firths behind. They had the least amount of
Speaker 1: progress on addressing the Y two K problem. UH. Such
Speaker 1: a huge deal that the president at the time was
Speaker 1: Bill Clinton, assigned the two thousand Information and Readiness Disclosure
Speaker 1: Act into law, and that was designed to create a
Speaker 1: collaborative environment among multiple industries, so that is one industry
Speaker 1: developed the best practices and tools to address the Y
Speaker 1: two K problem. It would be there was an incentive
Speaker 1: to share the information across other industries so that we
Speaker 1: didn't It's not a competition, it's it's hey, let's all
Speaker 1: get this done together, kind of issuing like I would
Speaker 1: like my stuff to continue not being on fire. How
Speaker 1: about I give this information to you guys, and maybe
Speaker 1: that will decrease the chance that my stuff will be
Speaker 1: on fire. In two thousand and that was a that
Speaker 1: was a big motivator. As it turns out, helped a lot. Uh,
Speaker 1: there were other areas of the world that we're also
Speaker 1: being very responsive to this. European Commission issued a report
Speaker 1: about Y two K to the European Union member countries
Speaker 1: that all kind of got them on the same page.
Speaker 1: The British government announced that the British military would be
Speaker 1: on hand to assist local police forces in the event
Speaker 1: of emergency services breaking down as a result of the
Speaker 1: Y two K problem. And there there was so much hype.
Speaker 1: I mean, I mean, yeah, well, we'll talk more about
Speaker 1: hype in a second. The United Nations held a conference
Speaker 1: on it. They were trying to facilitate more sharing of information,
Speaker 1: particularly but you know, that's that's cool, that's that's not hype,
Speaker 1: that's preparedness, right. Well, they were particularly worried about a
Speaker 1: lot of regions in Asia that were there were at
Speaker 1: least thought of to be behind the curve on this
Speaker 1: on addressing the HIT two K problem, So they wanted
Speaker 1: to make sure that everyone in the world had an
Speaker 1: equal chance of catching up so that they could minimize
Speaker 1: any effects that the Y two K problem would have.
Speaker 1: Not keep in mind, this is still at a time
Speaker 1: where no one was really sure what was going to happen,
Speaker 1: at least not on a global scale. There were some
Speaker 1: people were saying like, well, you know, this system over
Speaker 1: here is probably gonna be okay because it's not really critical,
Speaker 1: and even even if it were, you know, it would
Speaker 1: just be something that we could adjust by writing a
Speaker 1: couple of extra lines of code to correct that problem
Speaker 1: other systems. People are like, I don't know if that
Speaker 1: airplane will stay in the air. I mean, that wasn't
Speaker 1: legitimate fear some people, I don't know, Okay, maybe fear
Speaker 1: that people people absolutely and and you know, on a
Speaker 1: on a person to person basis. The amount of panic varied,
Speaker 1: um and problem they were depending on how much media
Speaker 1: they had consumed about it, and excitable they were to
Speaker 1: begin with. I want to say towards the end of night,
Speaker 1: a lot of the media coverage lent leaned more towards
Speaker 1: the satirical and the the kind of jokey up, world's
Speaker 1: gonna end next month kind of stuff, less less of
Speaker 1: the actual fearmongering style, and more of the no one's
Speaker 1: really sure, but you know, the worst case scenario could
Speaker 1: be that kind of thing. So it wasn't at least
Speaker 1: as as bad as you know, next month, everything you
Speaker 1: know will be different because nothing's going to work, and
Speaker 1: you know, start building your bomb shelter now. Um. You know,
Speaker 1: there weren't a whole lot of serious reports that were
Speaker 1: coming out like that, and I'm sure the Onion had
Speaker 1: a lot of fun with it. Um. But anyway, so
Speaker 1: we're leading up to what actually happened from the switch
Speaker 1: over to two thousand and I know you're all dying
Speaker 1: to know how it turned out, but you're just gonna
Speaker 1: have to wait a second because we need to take
Speaker 1: a quick break to thank our sponsor. Alright, So we're
Speaker 1: back now the clock is ticking down. I know you've
Speaker 1: been waiting, waiting all episode to learn what would happen
Speaker 1: about to turn to two thousand? What half? Okay, so
Speaker 1: technically we're all still here, so I guess we can
Speaker 1: draw some conclusions right off the bat. And and and
Speaker 1: I mean, this event is in our relatively recent past.
Speaker 1: It was really years ago, and most of you guys
Speaker 1: are probably remembering this, some of you and some of
Speaker 1: some of you folks who are in maybe middle school
Speaker 1: or whatever, maybe this is all new to you, in
Speaker 1: which case, hey, welcome to the ridiculous panics that the
Speaker 1: rest of the world went through before you were born.
Speaker 1: Your parents were silly. Yeah. So, as it turns out,
Speaker 1: a lot of the work that was being done leading
Speaker 1: up to two thousand was successful. I mean, and it
Speaker 1: was a lot of work. It was. Uh. One estimate
Speaker 1: said that globally the world spent about three hundred billion
Speaker 1: dollars that's billion with a B to address the Y
Speaker 1: two K problem, and about just a little less than
Speaker 1: half of that was spent in the United States alone
Speaker 1: to address this issue. And that ranged from everything from
Speaker 1: wide computer networks to like we were saying, microprocessors that
Speaker 1: control things like microwaves, and you know, really in that case,
Speaker 1: it was more of testing it to see, you know,
Speaker 1: if you were to to digitally alter the clock of
Speaker 1: the machine, would it continue to operate properly? That kind
Speaker 1: of stuff, right, And and in the most most cases
Speaker 1: things things were absolutely fine. And and people people kind
Speaker 1: of knew that, I mean know that there was a
Speaker 1: little bit of this media frenzy, but um but a
Speaker 1: p Poles indicated that Americans expected minor problems at worst, um,
Speaker 1: but that some thirty percent had planned stockpiles just in case. Yeah, yeah,
Speaker 1: that the food money, that kind of that was. Yeah,
Speaker 1: they weren't necessarily creating an armed militia, although there was
Speaker 1: some of that going on too at the time. Um,
Speaker 1: but you know, it's it's one of those things where
Speaker 1: I think a lot of people were jokingly saying, like, yeah,
Speaker 1: I mean, everything's gonna be fine, nothing's gonna be a problem.
Speaker 1: But then like, you know, but just in case, I
Speaker 1: think I'm gonna take it easy this year, uh or
Speaker 1: just that day specifically that yeah, New Year's Eve to
Speaker 1: two thousand, to make sure that you know, let's let's
Speaker 1: not let's not put ourselves in danger unnecessarily, but nothing's
Speaker 1: going to happen, you know. Cautious optimism is probably how
Speaker 1: I would describe it. Yeah, and basically, none of those
Speaker 1: big doomsayer kind of things, the worldwide power failures, the
Speaker 1: total breakdown of transportation infrastructure, that planes falling out of
Speaker 1: the sky, none, none of that. None of that happened. Now,
Speaker 1: to be fair, one reason a lot of that may
Speaker 1: not have happened is because so much work was done
Speaker 1: addressing the problem. Right, I still don't think that every
Speaker 1: computer in the world would have simultaneously caught on fire
Speaker 1: and started eating your face. No, that's the likelihood of
Speaker 1: that was very low, pretty low. I mean, some other
Speaker 1: spooky stuff would have had to have been going, but
Speaker 1: that we're talking some paranormal activity stuff at that point.
Speaker 1: But no, I think you know, here's here's the problem
Speaker 1: with assessing how Y two K worked out, because a
Speaker 1: lot of people said, oh, it was a lot of
Speaker 1: worry over nothing, nothing really big happened. But part of
Speaker 1: that was because so much work had been done to
Speaker 1: address the issue on a on a code level, to
Speaker 1: make sure that the code in some very critical systems
Speaker 1: was updated to not have this problem. So you could
Speaker 1: argue that the reason why there wasn't a problem was
Speaker 1: because we caused such a fuss in the first place.
Speaker 1: It's also possible that if we had never done anything
Speaker 1: and someone in two thousand said, hey, guys, I just
Speaker 1: thought of something that we probably should have thought about before.
Speaker 1: That everything's fine now, but you know what could have
Speaker 1: happened was blah blah blah. Sure that might have happened
Speaker 1: to yeah, yeah, like this is that's what really happened.
Speaker 1: But here's what could have happened. That's kind of the
Speaker 1: opposite of the clue endings. But yes, um, yeah, so
Speaker 1: the the you know, it's hard, it's impossible to say
Speaker 1: in hindsight, right, how it would have turned out differently
Speaker 1: had nothing happened. I imagine that we would have seen
Speaker 1: a lot of other glitches and systems that would have
Speaker 1: been time consuming to fix. And we did see some glitches, right,
Speaker 1: It wasn't like everything went off without a hitch, right, Well, okay,
Speaker 1: most of the glitches were kind of preemptive. Some some
Speaker 1: large chemical plants and oil pipelines were shut down preemptively
Speaker 1: during the transition and rebooted. UM service was suspended on
Speaker 1: like major freight railroads and Amtrak on New Year's Eve
Speaker 1: for for a final round of equipment and signal checks. Um. Yeah, uh,
Speaker 1: you know, the workload on programmers over the past couple
Speaker 1: of years had had been increased like twenty to sixty
Speaker 1: percent in order to solve the problems. So that was
Speaker 1: an effect anyway. Uh yeah, I mean there there were
Speaker 1: you know, some of the some of the problems that
Speaker 1: came up were very comical in nature. Yeah, there were,
Speaker 1: I mean, okay, there were legitimate, like a few hundred
Speaker 1: reports of errors amongst small businesses, but needs most most
Speaker 1: of them were resolved in a matter of hours after
Speaker 1: they had been reported. Um. There was the temporary shutdown
Speaker 1: of a Defense Department ground station that that processed info
Speaker 1: from a from a satellite from a spy satellite. Um.
Speaker 1: But it didn't have any major consequences. There were there
Speaker 1: were a couple of really good ones. Um for Okay.
Speaker 1: So so this was when uh Al Gore was the
Speaker 1: vice president. My favorite of the ye two K problems,
Speaker 1: by the way, Um, for for a minute, his town
Speaker 1: hall web page informed visitors that it was January three, uh,
Speaker 1: nineteen thousand, one hundred if they arrived via Netscape and
Speaker 1: January three, nineteen thousand eight D. I'm sorry if they
Speaker 1: were coming in via Futurama. We know that by that
Speaker 1: time Al Gore's head is in a jar. So maybe
Speaker 1: it was accurate. It could be. It could have been
Speaker 1: like this was a glimpse into the Futurama future. Um um,
Speaker 1: there was a there was a glitch in the New
Speaker 1: York Times. Oh I love this one, dude, No, this
Speaker 1: one's my favorite. I retract by earlier statement, this one's
Speaker 1: my favorite. They can both be your favorite. Um okay. So,
Speaker 1: so there was a telephone service that would read an
Speaker 1: automated selection of the New York Times and other newspapers
Speaker 1: to um New Yorkers with with vision problems and um.
Speaker 1: It informed clients that they would be hearing the January three,
Speaker 1: nine hundred issues. So where we started recording, I said,
Speaker 1: I could just mention the top headline, dirigible races reach
Speaker 1: inevitable draw for the year running. I think I want,
Speaker 1: I kind of want that alternate history right where you.
Speaker 1: What would have been amazing is if it had actually
Speaker 1: read the headlines from January three, dred at that point. Now,
Speaker 1: that's not exactly that's not what happened. It just had
Speaker 1: the date wrong. On the date part. The actual content
Speaker 1: was the same was the one for January third, two thousand.
Speaker 1: It's not like the computer glitched and went and looked
Speaker 1: up some microfiche and brought it back and read it out.
Speaker 1: I wish that had happened though. That would have been
Speaker 1: so awesome. That would have been delightful. UM. I mean,
Speaker 1: like other stuff, UH that there was some some legal
Speaker 1: battles that arose over all of this. Xerox, Nike, Unitis,
Speaker 1: and a whole bunch of other companies were a few
Speaker 1: major other companies. UM uh sued their insurers for reimbursement
Speaker 1: for having to have spent hundreds of millions of dollars
Speaker 1: on these repairs. UM, citing language from nineteenth century business
Speaker 1: contracts wherein insurers had to repay ship owners for money
Speaker 1: spent trying to prevent ship from sinking. Yeah. Interesting sighting
Speaker 1: of a precedent. Yeah, that didn't work out so well. UM.
Speaker 1: The suits generally generally settled on on the side of
Speaker 1: the insurance companies because I think arguing that because nothing
Speaker 1: bad happened, then we shouldn't have been forced to prevent
Speaker 1: something bad from happening is a weird argument, because if
Speaker 1: nothing bad happened, that's possibly proof that the thing you
Speaker 1: had to do worked oh well. And even I mean
Speaker 1: even if you if you spend that money preventing a
Speaker 1: ship from sinking or preventing a computer from crashing. Um.
Speaker 1: You know, in this particular case, the companies had seen
Speaker 1: the ship sinking several years before they actually informed the
Speaker 1: insurance company that it was an issue. And so in
Speaker 1: that case, the courts were like, you knew about this beforehand.
Speaker 1: This interesting, this is stuff that you had to take
Speaker 1: care of. And um, I see there were some other
Speaker 1: like practical outcomes that were you know, just the way
Speaker 1: people had reacted to Y two K and started stockpiling stuff.
Speaker 1: That meant that once the new year happened and society
Speaker 1: did not crumble, a lot a lot of people returned
Speaker 1: to space heaters, um, like so many that that SEARS
Speaker 1: started incurring a not incurring but um, but charging stocking
Speaker 1: fee because people so many people were worried that the
Speaker 1: infrastructure would be gone and that they wouldn't have gas
Speaker 1: or electricity, you know, and then they once once that
Speaker 1: those problems went away, like once two thousand came around
Speaker 1: and everything was fine. Then they're well, I don't really
Speaker 1: need this anymore. Uh, charity groups collected a lot of
Speaker 1: extra cand goods that year. Uh. Not so many people
Speaker 1: traveled by airplane on New Year's Day that year, right,
Speaker 1: I mean not that many people travel on New Year's
Speaker 1: Day to begin with, but even yeah, there were some
Speaker 1: of those people who were worried about the whole airplane
Speaker 1: dropping out of the sky thing. And here's the thing
Speaker 1: is that while this hite two K problem sounds like
Speaker 1: it's like, well, yeah, sure it happened once, bill, never
Speaker 1: happen again. Alright, Alright, so there there are a bunch there.
Speaker 1: There are like many, much multiple other problems, like like
Speaker 1: the y t K problem. They're all time dependent and
Speaker 1: they're all code dependent. However, the the year in which
Speaker 1: each one would hit its big old problem is different
Speaker 1: from one example to another, mostly because engineers have a
Speaker 1: wicked sense of humor. Well I'm not sure, okay, So
Speaker 1: so I don't I don't code. I'm not a programmer.
Speaker 1: I I've never used any kind of back end sort
Speaker 1: of thing. I know how to make things bold and
Speaker 1: h ham l on my own, but that's that's about it. Um,
Speaker 1: but so so apparently in various programs, UM, the beginning
Speaker 1: of time starts on various dates. Yeah, the beginning of
Speaker 1: time tends to be the date that whatever was created
Speaker 1: was put into action, although not all of all the time. So,
Speaker 1: and it can depend on the numeracle system that the
Speaker 1: coding is using. UM. I know, for for IBM PCs,
Speaker 1: the beginning of time is January one, up and uh,
Speaker 1: it go the time itself goes up in seconds. So
Speaker 1: the second is the base integer for this whole thing, UM.
Speaker 1: And it's a thirty two bit integer. So that means
Speaker 1: that if you if you do the math and you're thinking, okay,
Speaker 1: it's a thirty two bit integer. Each second is another increment,
Speaker 1: So every second that passes goes up another one. If
Speaker 1: you're limited to thirty two bits and you're starting days
Speaker 1: January one, nineteen eighty, you can extend that out and
Speaker 1: you see that in two thousand one sixteen you have
Speaker 1: hit the limit of of the integers you have. You
Speaker 1: are no longer able to go up without rolling over.
Speaker 1: It's kind of like those old alright, gather around that
Speaker 1: digital fireplace, children, and the old days we had digital
Speaker 1: uh like pinball machines, and once you hit a high
Speaker 1: score at a certain level, it would turn over, meaning
Speaker 1: it would go back to I actually did that on
Speaker 1: the Star Trek one. I'll tell you about some time. Anyway,
Speaker 1: I was, yeah, I had seventeen free replays by the
Speaker 1: end of that. I ended up leaving because I couldn't
Speaker 1: keep playing all day. I was in knowledge at the time,
Speaker 1: money will spent, Mom and Dad. Anyway, two thousand, one
Speaker 1: h and sixteen is when those integers will reach the limit,
Speaker 1: meaning that, uh don't know what's going to happen after that.
Speaker 1: It's not gonna be able to make these these time
Speaker 1: dependent calculations accurately anymore, because it won't be able to
Speaker 1: track time in a in a way that makes sense
Speaker 1: to the computer anymore. So you would think, oh, well, clearly,
Speaker 1: all right, so we've got the Y two K problem
Speaker 1: and the two thousand, one hundred sixteen problem with IBM PCs,
Speaker 1: but after that we're okay, right, well uh well, so
Speaker 1: so Windows NT sets the beginning of time as January
Speaker 1: one s one. So apparently they were thinking, like, okay,
Speaker 1: Shakespeare would totally use Windows INT just before, you know,
Speaker 1: shortly before he dies. So clearly he would have written,
Speaker 1: you know, some of his greatest plays using a machine
Speaker 1: using Windows NT. So let's start the I have no
Speaker 1: idea why they chose January. Yeah, and okay, so, so
Speaker 1: it uses a sixty four bit integer to track time,
Speaker 1: so way more integers than you know, twice as much
Speaker 1: as the thirty two bit intager that IBMPC did, and
Speaker 1: furthermore uses a hundred nanoseconds as its increment. So so
Speaker 1: it's problem is a ye, right, So it's here's the thing.
Speaker 1: It covers a much greater span of time, right because
Speaker 1: it starts in sixteen o one and it won't end
Speaker 1: until four so that's later. But because of that hundred
Speaker 1: nano second problem, that eats up those innagers pretty quickly.
Speaker 1: If it had done it as a second intager, it
Speaker 1: would extend much further out. But hey, good good news
Speaker 1: for Apple users. According to Apple, um mac is okay
Speaker 1: out to the year. Uh yeah, um so, I mean
Speaker 1: not that it matters, because you're gonna update all your
Speaker 1: stuff every year anyway, you Apple fanboys, I'm saying that
Speaker 1: I'll love. I'm not entirely positive that you are. Really.
Speaker 1: My wife has a iPhone I I love her. I've
Speaker 1: got a Mac. I mean, I'm granted my Mac. It's
Speaker 1: like eight years old at this point. It might actually
Speaker 1: be an Apple computer non a Mac. They might have devolved,
Speaker 1: but anyway, Yes, at any rate, all of these problems
Speaker 1: are going to be a little bit easier to fix
Speaker 1: than the Y two K problem, right, And and it's
Speaker 1: one of those things where the Y two K problem
Speaker 1: that was something that was so UH grounded in the
Speaker 1: very basic code that so many different UH systems were using.
Speaker 1: That's probably the scope of it was enormous, right, And
Speaker 1: we didn't have the tools available than that we do
Speaker 1: today for for going in and addressing propagating things. Only that,
Speaker 1: but we've got a greater time scale for all of
Speaker 1: these problems. It's not something that's you know, five years away.
Speaker 1: Although we can't just have the attitude of oh, well
Speaker 1: that's you know, that's like twenty more years. We don't
Speaker 1: need to worry about that. No, we should definitely take
Speaker 1: the steps to address these issues. So, yes, it is
Speaker 1: one of those things where we see it over and
Speaker 1: over again. Does it mean that we are done? That
Speaker 1: no one is ever going to make this kind of mistake?
Speaker 1: Just for the sake of convenience or or efficiency or economics. Uh,
Speaker 1: we're never gonna make old mistake. No, we're human. We
Speaker 1: make mistakes. That's kind of kind of thing. They're they're
Speaker 1: warm and fuzzy. It's us. Yeah, well you know we're
Speaker 1: good at that and making mistakes. I am great. I'm
Speaker 1: like I learned from my mistakes. I can repeat them
Speaker 1: almost exactly. So um, yeah, it's something that will price
Speaker 1: see also pop up, and of course those people will
Speaker 1: eventually be ridiculed like do don't you remember why t K?
Speaker 1: And uh, you know, we'll just we'll relive this drama
Speaker 1: multiple times. But hey, some of these are problems that
Speaker 1: are so far in the future that it's our descendants
Speaker 1: that are gonna be worried about them unless we find
Speaker 1: some digital immortality or something. Yeah. See there you go say,
Speaker 1: I think that what all of this is not taking
Speaker 1: into consideration is that we are clearly going to hit
Speaker 1: the singularity in yes, well you know, uh, we're getting
Speaker 1: We're rapidly approaching what Kurtswil said would be the singularity.
Speaker 1: And I'm a little skeptical right now, but hey, it
Speaker 1: could be proven wrong. But you know, when we see
Speaker 1: problems like this rise up. It does make you wonder
Speaker 1: about that singularity and think maybe that maybe that would
Speaker 1: only be really super awesome for a very relatively short
Speaker 1: time until our code ran out. Oh yeah, exciting stuff, right,
Speaker 1: all right, Well, the interesting thing is we would all
Speaker 1: end together. That's kind of sweet and really nihilistic way.
Speaker 1: I think I've got an idea of our science fiction novel.
Speaker 1: Don't steal it. Okay, So we're gonna wrap up. Guys.
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Speaker 1: get in touch with us. I've had a long day
Speaker 1: and I'm about to go to see s so I'm
Speaker 1: a little loopy. Al Right, guys, that wraps up this discussion.
Speaker 1: Get in touch with us. We will talk to you
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