Speaker 1: Welcome to tex Stuff, a production from I Heart Radio.
Speaker 1: Hey there, and welcome to tech Stuff. I'm your host,
Speaker 1: Johan Strickland. I'm an executive producer with I Heart Radio.
Speaker 1: And how the tech are you? It's time for a
Speaker 1: tech Stuff tidbits. And I thought it would be a
Speaker 1: good idea to do an episode to talk about bits
Speaker 1: and bytes, largely because I think a lot of folks
Speaker 1: can confuse the two, include myself in that, and to
Speaker 1: be fair, it is confusing, like even when you're in
Speaker 1: the computer science field, this can get confusing. It's totally understandable.
Speaker 1: So we talk about data transfer rates in terms like
Speaker 1: megabits or gigabits per second, but we talk about data
Speaker 1: storage in terms of gigabytes or terabytes. And then we
Speaker 1: talk about you know, memory in terms of megabytes or gigabytes,
Speaker 1: and we mean different negabytes and gigabytes that we do
Speaker 1: with data storage. So it's not hard to get this
Speaker 1: stuff mixed up. But let's start with the bit. It's
Speaker 1: the easiest one to understand. So in computer terms, a
Speaker 1: bit is the smallest unit of information. So in computer data,
Speaker 1: you know analogies, you would call a bit the same
Speaker 1: thing as an atom. As like the building block for
Speaker 1: computer information, and a bit is a binary digit. It's
Speaker 1: how we, you know, can talk about individual pieces of
Speaker 1: data and we represent it as being either a zero
Speaker 1: or a one. It's base two. It's a zero or
Speaker 1: a one. And I often say you can think of
Speaker 1: a bit kind of like an on or off switch,
Speaker 1: and you can say like, well, one means the switches
Speaker 1: on and zero means the switches off. John Wilder, two
Speaker 1: key mathematician, suggested the term bit back in n So
Speaker 1: we're talking about the very early days of modern computer science.
Speaker 1: I mean a lot of groundwork had been laid by
Speaker 1: people like you know, Charles Babbage and Ada Lovelace. But
Speaker 1: the late forties is really where we start getting the
Speaker 1: foundation of modern computer science, and computers had been around
Speaker 1: a little bit, byn not by a lot. We were
Speaker 1: pretty young, um, and a lot of the computer technology
Speaker 1: actually evolved from earlier machines that were meant to do
Speaker 1: everything from count ballots to guide a loom when weaving
Speaker 1: a specific pattern. The evolution of the bit involves stuff
Speaker 1: like punch cards. But to get into all of that
Speaker 1: would be a little bit too much for a Tidbits episode.
Speaker 1: So two key coined this term, but it was Claude
Speaker 1: Shannon who really popularized it in his work titled A
Speaker 1: Mathematical Theory of Communication. He credited credited two Key in
Speaker 1: that work, so Shannon didn't try and pass this all
Speaker 1: phys his own idea. I think that's awesome because I
Speaker 1: don't see that a lot, you know, I see people
Speaker 1: using terms and not indicating that, hey, someone else actually
Speaker 1: thought this up. That wasn't Claude Shannon's style. Shannon was
Speaker 1: quick to credit to Key with coming up with the
Speaker 1: idea anyway. Shannon laid out the that a device capable
Speaker 1: of two stable positions or states such as off and on.
Speaker 1: There's the off state and the on state. Well, something
Speaker 1: like that can store one bit of information, and that
Speaker 1: this meant for in number of such devices you can
Speaker 1: store in bits of information. So, in other words, if
Speaker 1: you have twenty switches right, and each of the switches
Speaker 1: has an on or off position, you can store up
Speaker 1: to twenty bits with that system. From there, Shannon dives
Speaker 1: into how this approach can be used to communicate on
Speaker 1: a computational basis. The paper itself is free to read online.
Speaker 1: You can find it again. You just just search for
Speaker 1: the title, which was a mathematical theory of communication. It'll
Speaker 1: pop right up and you can read it. Uh, it's
Speaker 1: a technical document, and honestly, it's the kind of paper
Speaker 1: where I need to have a separate tab open so
Speaker 1: I can look up terms and meanings just to try
Speaker 1: to keep up. And even that is being generous. It
Speaker 1: it is. Uh, someone in computer science totally makes sense
Speaker 1: to them, like, no no brainer. For someone like me
Speaker 1: with my background in English literature, it requires a bit
Speaker 1: more homework on my part. But it is a truly
Speaker 1: fascinating and foundational piece of work in the computer science discipline.
Speaker 1: But then, what can you represent if you have just
Speaker 1: a single bit with a switch that's off or on. Well,
Speaker 1: with just two states, you can't really represent anything terribly
Speaker 1: useful for communication. Uh, you could do yes, no, but
Speaker 1: that's it. Like you couldn't form a question. You could
Speaker 1: just maybe given answer that's very very very simple, But
Speaker 1: you couldn't really process information with a single bit, like
Speaker 1: a processors that can only handle one bit would be useless.
Speaker 1: So let's look at what happens when we have more
Speaker 1: bits in our disposal. Well, each bit again has two
Speaker 1: potential states off on zero, one. But if you have
Speaker 1: two bits together, well, then you can get a shaven haircut. Sorry,
Speaker 1: that's a very ill dated dad joke. If you happen
Speaker 1: to know the whole shaven a haircut two bits, good
Speaker 1: for you. You might have appreciated that very bad joke
Speaker 1: I made. No. No. If you have two bits, you
Speaker 1: technically can represent four states with those two bits, right,
Speaker 1: you can have zero zero, that's the first one. You
Speaker 1: can have zero one, you could have one zero, or
Speaker 1: you could have one one. So with two bits you
Speaker 1: can represent four things. Well, what if you had four bits, Well,
Speaker 1: that means you could represent sixteen different outcomes and they
Speaker 1: would range from zero zero, zero zero to one one
Speaker 1: one one, and there will be sixteen different ones. If
Speaker 1: you had eight bits, you could represent up to two
Speaker 1: hundred fifty six versions or outcomes. So the easy way
Speaker 1: to represent this is to take the number two. That
Speaker 1: represents the number of states that each bit can have.
Speaker 1: You know, a zero or a one, that's two states.
Speaker 1: So you take the number two and you raise that
Speaker 1: too to a power equivalent to the number of bits
Speaker 1: you're talking about. So eight bits is the same as
Speaker 1: saying two to the eighth power or two hundred fifty
Speaker 1: six potential values. So this means that as you double bits,
Speaker 1: you are you know, or as you increase bits, you
Speaker 1: are logarithmically increasing the number of potential states. So if
Speaker 1: we double eight bits to get sixteen bits, that doesn't
Speaker 1: mean that we double two hundred fifty six to twelve. No, no, no, no,
Speaker 1: it is two to the power of sixteen. That that
Speaker 1: is sixty five thousand ft six. So you see that
Speaker 1: as you add bits to a system, you dramatically increase
Speaker 1: the number of states. In fact, every time you add
Speaker 1: a bit two systems capability of handling bits, you double
Speaker 1: the number of of potential values you can represent. So
Speaker 1: this is what I meant by a logarithmic increase. All right,
Speaker 1: So once you go with binary digits, you start to
Speaker 1: look at how many bits you need to do whatever
Speaker 1: it is you need to do. So let's say that
Speaker 1: you want to start off just by representing the Latin alphabet, right,
Speaker 1: You want to be able to use bits to designate
Speaker 1: letters of the alphabet and say this combination of bits
Speaker 1: means A, this one means B. Well, if you're just
Speaker 1: looking at the number of letters in the Latin alphabet,
Speaker 1: we would need at least twenty six values. Right, we
Speaker 1: would need twenty six different combinations in order to represent
Speaker 1: the just the basic alphabet. Full were bits would let
Speaker 1: us sixteen values, so that's not enough, But five bits
Speaker 1: would give us thirty two as because two to the
Speaker 1: fifth power is thirty two. So with five bits we
Speaker 1: could represent all the letters of the alphabet, and we'd
Speaker 1: have a couple of values left over where we could
Speaker 1: represent simple punctuation. However, we wouldn't be able to have
Speaker 1: upper and lower case letters. All letters would have to
Speaker 1: be the same case because each case would be a
Speaker 1: state or a value of its own. So capital J
Speaker 1: and a lower case J would each require their own designations,
Speaker 1: and we don't have enough bits to do that. If
Speaker 1: we have thirty two, we we would have have to
Speaker 1: have at least fifty two in order to do that,
Speaker 1: and we don't have that. We've got thirty two plus.
Speaker 1: We wouldn't be able to represent any numerals, or at
Speaker 1: least not all of them. Would just thirty two bits,
Speaker 1: unless we were to sacrifice some letters of the alphabet,
Speaker 1: because otherwise the alphabet takes up too many of the
Speaker 1: states or values. Now, the term by began to pop
Speaker 1: up a little bit around this time to describe the
Speaker 1: number of bits engineers were using to represent a character set. So,
Speaker 1: for example, if we used five bits to represent all
Speaker 1: the characters in our set, which I mean again, we
Speaker 1: would be limited to thirty two characters, then we would
Speaker 1: naturally refer to five bits as a byte in our system.
Speaker 1: And you've probably heard that eight bits are a byte.
Speaker 1: Well they are now, but in the early days, what
Speaker 1: you're referred to as a byte depended upon the system
Speaker 1: architecture you were working with at the time, so the
Speaker 1: bite was not always in forever on men. Uh, you know,
Speaker 1: eight bits, that's not the way that worked. There were
Speaker 1: five bit bytes, six bit bytes, seven bit bytes. Uh.
Speaker 1: These were all kind of hashing out over time as
Speaker 1: various companies were building out computer systems. Also in the
Speaker 1: early days of computing, designers created machines that had to
Speaker 1: for an instruction set. Architectures, and some systems used a
Speaker 1: five bit sized word, which is a collection of bits
Speaker 1: that becomes the native unit of storage. By storage, we're
Speaker 1: not just talking about storing data like in a hard drive.
Speaker 1: We're really talking about storage in the sense of a
Speaker 1: computer has to be able to hold onto a certain
Speaker 1: amount of information in order to process the information, you know,
Speaker 1: to execute some sort of operation on the data. So
Speaker 1: you're you're essentially talking about was the processor's capacity, how
Speaker 1: much information can it hold in order to do operations
Speaker 1: on that data. So smaller word size means you are
Speaker 1: working with smaller amounts of information that the processor can handle,
Speaker 1: and it limits what your processor can do and thus
Speaker 1: limits what your computer can do. So when we talk words,
Speaker 1: we're talking about stuff like CPU registers, which temporarily store
Speaker 1: small pieces of information while the CPU executes some sort
Speaker 1: of process on that data. Some early systems used five
Speaker 1: bit words, some used six bit words. Uh, and then
Speaker 1: they grew very quickly from there because that was so
Speaker 1: limited that you couldn't do much with them. All Right,
Speaker 1: we were just getting started. We're gonna take a quick break.
Speaker 1: When we come back, we will continue to talk about
Speaker 1: bits and bites. Okay, So in the early days of computing,
Speaker 1: the technological limitations would determine word length. So let's let's
Speaker 1: review really quickly. A bit is a single unit of information.
Speaker 1: It's either a zero or a one. A bite is
Speaker 1: a consecutive group of bits, which we used to represent characters,
Speaker 1: and a word refers to a consecutive number of bits
Speaker 1: or bites, used primarily for CPU registers, and you can
Speaker 1: think of word size as being an indication of how
Speaker 1: much information on computers CPU can handle for individual operations,
Speaker 1: large word size means the computer can handle bigger operations effectively.
Speaker 1: By the nineteen fifties, various companies began using a character
Speaker 1: set called b c D, which had you know at
Speaker 1: least forty eight characters in it, and to encode for
Speaker 1: the eight characters you would need to have at least
Speaker 1: six bits, So the six bit bite became kind of
Speaker 1: a standard for a while. By the time IBM was
Speaker 1: ready to introduce the System three sixty, the company had
Speaker 1: gravitated towards an eight bit size for bites. Now, technically
Speaker 1: the three sixty could get by with just seven bits
Speaker 1: to represent all the characters that it was going to use,
Speaker 1: but programming is way easier if you're dealing with bites
Speaker 1: and words that are based on powers of two. Seven
Speaker 1: is not a power of two, but eight is, so
Speaker 1: bumping up the bite size from seven bits to eight
Speaker 1: bits made more practical sense, and it also meant you
Speaker 1: had two hundred fifty six values to play with instead
Speaker 1: of a hundred twenty eight, which is what you would
Speaker 1: get if you were using seven bits to a byte.
Speaker 1: IBMS move would end up creating the foundation for bites
Speaker 1: moving forward, though it didn't catch on immediately. So by
Speaker 1: the time I was a kid learning about personal computers
Speaker 1: in the late seventies and early eighties, a byte was
Speaker 1: pretty firmly established as being eight bits, and in fact,
Speaker 1: I don't remember ever seeing anything that suggested that had
Speaker 1: not always been the case. So I walked away with
Speaker 1: the impression that, you know, a bit was always a
Speaker 1: zero or a one, and a byte had always been
Speaker 1: eight bits, but the eight bit byte really wasn't standardized
Speaker 1: until say, the early nineteen seventies. So you've got your bit,
Speaker 1: you've got your bite, which is eight bits and super quick.
Speaker 1: We should reference what prefixes like kilo, mega, giga, terra
Speaker 1: or killa. This is that's the way most people say it,
Speaker 1: and when they're talking about bytes and bits what those mean,
Speaker 1: And they come from metric prefixes, but bits and bytes
Speaker 1: are not metric units, and when it comes to bites
Speaker 1: in particularly gets real confusing. So kilo or killa means
Speaker 1: one thousand, Mega means million, Giga means billion, Tera means trillion,
Speaker 1: and you can go further. I mean, petta would be quadrillion,
Speaker 1: exa would be quintillion. So if you hear something like
Speaker 1: an exabyte, they're talking about the quintillion bytes and then
Speaker 1: it keeps on going up from there. But for the
Speaker 1: average person, terra is kind of where we max out
Speaker 1: when we're talking about modern personal computers, like a terabyte
Speaker 1: hard drive, that kind of thing. Now, let's talk about
Speaker 1: data transfer speeds and computer storage and computer memory and
Speaker 1: why we use terms like gigabit or gigabyte and what
Speaker 1: does actually mean. So when we're talking about transmission speeds,
Speaker 1: we are framing the discussion in terms of bits per second. Uh.
Speaker 1: This also can kind of get a little confused with bandwidth. UH,
Speaker 1: that's pretty easy to confuse with transmission speed. Bandwidth describes
Speaker 1: the capacity of a network. UH. In other words, the
Speaker 1: amount of data that network can handle or transmit at
Speaker 1: any give and time. And networks are not infinitely capable
Speaker 1: of handling data, they do have a cap This is
Speaker 1: one of those things that I s p s like
Speaker 1: to reference when they're talking about having to charge people
Speaker 1: in arm in a leg to access the Internet because
Speaker 1: there are capacity limits that a network will hit. Uh,
Speaker 1: most of the time we don't get to the full
Speaker 1: capacity limit. But that's still the story we get told whenever,
Speaker 1: whenever it's time to pay the bill. So um, there's that.
Speaker 1: But transmission speed is literally the rate at which data
Speaker 1: crosses from one point in a network to another, and
Speaker 1: that depends on a whole bunch of stuff, Like it
Speaker 1: can depend upon the distance between the two points, right,
Speaker 1: Like if you are transferring data from a computer that's
Speaker 1: on the opposite side of the world where from where
Speaker 1: you are, that's going to affect the transmission speed as
Speaker 1: opposed to like a computer that's you know, a mile away.
Speaker 1: Then like the kinds of connections, like what kinds of
Speaker 1: wires are connecting you as a copper is it fiber?
Speaker 1: You know, that sort of stuff also determines the transmission speed.
Speaker 1: There are lots of other elements that do too, but
Speaker 1: ultimately you figure out, you know, what your transmission speed is.
Speaker 1: Here in the United States, the Federal Communications Commission currently
Speaker 1: defines broadband internet speed as twenty five megabits per second down.
Speaker 1: That means the that's the data transfer rate that applies
Speaker 1: to information that's coming from the Internet to your computer.
Speaker 1: That that if it's twenty five megabits per second or faster,
Speaker 1: then that means you have broadband access at least on
Speaker 1: the down download side, and three megabits per second up.
Speaker 1: So this would be the speed at which your computer
Speaker 1: sends data back up to the Internet. So if you
Speaker 1: have twenty five megabits down and three megabits up, that
Speaker 1: counts as broadband in the United States. Uh. And since
Speaker 1: mega means millions, that means million bits per second downloading,
Speaker 1: three million bits per second uploading. By the way, there
Speaker 1: are a lot of folks out there, including myself, who
Speaker 1: say this definition is way too low and we should
Speaker 1: have a higher standard to qualify for broadband designation. And
Speaker 1: that is important. It's not just semantics. It's important because
Speaker 1: there are various government initiatives that are dedicated to extending
Speaker 1: broadband service too underserved regions and populations in the United States,
Speaker 1: because people have recognized access to the Internet is one
Speaker 1: of the most important elements to participating in modern society,
Speaker 1: particularly during a pandemic. And so if you define broadband
Speaker 1: as a very low standard, you're you're not really helping
Speaker 1: out people with these programs to get access to that
Speaker 1: very low standard, like companies are going to do the
Speaker 1: bare minimum they need to do in order to get
Speaker 1: that access to those people. So you could argue that
Speaker 1: this definition would keep people at a technological disadvantage and
Speaker 1: that we really should uh change the definition and to
Speaker 1: be more reflective of what broadband really is. Anyway, transfer
Speaker 1: speeds are all in bits per second, and the prefixes kilo, mega, giga,
Speaker 1: and so on are very straightforward. Kill a bit is
Speaker 1: a thousand bits, so I kill a bit per second.
Speaker 1: Transfer speed would be terrible, but it would be a
Speaker 1: thousand bits per second, and a mega bit is a
Speaker 1: million bits, so very easy to follow. But it is
Speaker 1: a very different story when we talk about bites, and
Speaker 1: it's confusing, is all heck to a lot of folks,
Speaker 1: including folks in computer science. All right, So in the
Speaker 1: early days, there was this real need to stick to
Speaker 1: powers of two when you were talking about bites. Again,
Speaker 1: this dates all the way back to the introduction of
Speaker 1: the IBM system three sixty where executed IBM, we're saying no, no, no,
Speaker 1: let's let's just deal with powers of two. It simplifies things.
Speaker 1: Otherwise stuff breaks down. So rather than describe one thousand bites,
Speaker 1: you know that a killer bite is a thousand bights.
Speaker 1: It was more elegant within the computer science model to
Speaker 1: describe a kilo bite as one thousand twenty four bites.
Speaker 1: A thousand twenty four is the same thing as two
Speaker 1: to the tenth power, but two to the tenth power
Speaker 1: or one thousand twenty four. There there's no easy naming
Speaker 1: convention to use for to describe one thousand twenty four bites,
Speaker 1: and the computer science world kind of appropriated kill a
Speaker 1: bite to describe it, because a thousand twenty four is
Speaker 1: kind of like a thousand if you squint your eyes
Speaker 1: a little. From a computational standpoint, sticking with powers of
Speaker 1: two made things easier. From a semantic standpoint, it done
Speaker 1: mess things up because I kill a bit is a
Speaker 1: thousand bits, But to kill a bite at least originally
Speaker 1: was a thousand twenty four bites bud weight. It'll get worse,
Speaker 1: I'll explain after we come back from this quick break. Okay,
Speaker 1: a kilobyte is a thousand twenty four bytes because we
Speaker 1: wanted to stick to that power of two things. Well,
Speaker 1: then we get to megabyte. Well, mega means million, so
Speaker 1: megabyte should mean one million bytes. But in those same
Speaker 1: little areas of computer science, particularly those dealing with like
Speaker 1: computer memory, that kind of stuff, a megabyte was really
Speaker 1: seen as actually being one million, forty eight thousand, five
Speaker 1: hundred seventy six bytes. And you might say, what, what why?
Speaker 1: Well again, it's those powers of two, So a kilobyte
Speaker 1: was two to the tenth power. A megabyte was two
Speaker 1: to the twenty power or one thousand, twenty four squared.
Speaker 1: But hey, one million, forty eight thousand, five d seventy
Speaker 1: six bytes is kind of hard to say, right, So
Speaker 1: let's just call it a megabyte, right, It's called a megabyte.
Speaker 1: Who's gonna care. By the late nineties, the International Electrochemical
Speaker 1: Commission had had enough of this nonsense because it was
Speaker 1: causing tons of confusion. I mean, the computer science world
Speaker 1: was going all humpty dumpty on the rest of us. Uh,
Speaker 1: if you don't understand that reference, Okay, And Alice and
Speaker 1: through the looking glass there's this encounter she has with
Speaker 1: Humpty dumpty, you know, the egg that sat on the wall,
Speaker 1: and Humpty Dumpty says words mean whatever he wants them
Speaker 1: to mean. He says, like, you know, the only question
Speaker 1: is who who is to be the master the words
Speaker 1: or me? And I'm not letting the words push me around.
Speaker 1: So when I use words, they mean exactly what I
Speaker 1: want them to mean. That's kind of what the computer
Speaker 1: science world was doing to the rest of us, And
Speaker 1: the brave among us said, Yo, you can't do that.
Speaker 1: Words mean things. So anyway, the I e C made
Speaker 1: a recommendation that KILLO, mega, giga, etcetera. Would mean the
Speaker 1: same thing they mean in metric systems. So in other words,
Speaker 1: if you use the word megabyte, you meant one million bytes.
Speaker 1: And if you wanted to go to the power of
Speaker 1: two route like if you if you really wanted to
Speaker 1: call one million, forty eight thousand bytes something, the I
Speaker 1: e C said, well, don't use megabyte. That's confusing. Will
Speaker 1: create a new designation. Call it a membe bite, m
Speaker 1: E B I byte b y t E. So the
Speaker 1: one thousand, twenty four version that wouldn't be called a
Speaker 1: kilobyte anymore, that'd be called a kippi byte. And they
Speaker 1: also went ahead and said the one thousand to twenty
Speaker 1: four to the third power or two to the thirty
Speaker 1: power would no longer be a gigabyte. That would be
Speaker 1: a gimby byte, and one thousand twenty four to the
Speaker 1: fourth power or two to the power would be a
Speaker 1: tabby byte, not a terabyte, and so on, and so
Speaker 1: if you said gigabyte, you meant a billion bytes, and
Speaker 1: terabyte would be a trillion bytes. This was meant to
Speaker 1: clarify things so that everyone knew what people were talking
Speaker 1: about when they were using a specific designation, and that
Speaker 1: would clear everything up, except the computer science world at
Speaker 1: large kind of ignored the suggestion. So there remains this
Speaker 1: use of the terminology that, depending upon the context, will
Speaker 1: mean one number of bites or a different number of bites.
Speaker 1: Like if you're talking about RAM, for example, you're really
Speaker 1: referring to the power of two version the base to
Speaker 1: description in other words, like the one twenty four for
Speaker 1: kill a byte. But if you're talking about hard drives,
Speaker 1: while you're typically talking about the base ten version, because
Speaker 1: these days hard drives when they're marketed, are marketed toward that.
Speaker 1: So a five hundred gigabyte hard drive is supposed to
Speaker 1: be five hundred billion bytes, although it's usually slightly off
Speaker 1: from that, but it's supposed to be in that neighborhood,
Speaker 1: and it's not you know, the the power of two
Speaker 1: variation of of that. So yeah, it's all clear as mud. Right,
Speaker 1: So kill a bit is different from a kilobyte, and
Speaker 1: sometimes a kilobyte is different from a different kilobyte depending
Speaker 1: on the context. Hurts main things here, science geeks, Now,
Speaker 1: I'm not I'm actually I'm not so sure about that
Speaker 1: anymore the more I read into this, uh, and it
Speaker 1: got more muddy too, because there's not really a universal
Speaker 1: standard on how to abbreviate things like megabits versus megabytes,
Speaker 1: so it can be confusing when you're reading a document
Speaker 1: about whether or not the author means megabits or megabytes. Now,
Speaker 1: some folks will tell you it all depends on which
Speaker 1: letter in the abbreviation happens to be capitalized, but really
Speaker 1: that's not universal. You you really need to define those
Speaker 1: abbreviations upfront for any given piece, because there's no formal
Speaker 1: agreement on which one should be used. Where there are
Speaker 1: some schools and some scientists who have a preference that
Speaker 1: they demand folks follow, but again, it's not universal, so
Speaker 1: it doesn't really help. All right, But let's let's talk
Speaker 1: quickly about using bytes and bits in a practical example,
Speaker 1: why you would care. Let's say that you had a
Speaker 1: single sided, single layer DVD and d v D has
Speaker 1: a data storage capacity of four point seven gigabytes, and
Speaker 1: in this case we do mean the base ten version,
Speaker 1: so gigga does mean billion, not one thousand, twenty four
Speaker 1: to the third power, so we're talking four point seven
Speaker 1: billion bytes of data. Now, let's say we want to
Speaker 1: send a copy of the data that's on this DVD
Speaker 1: to a computer that's on our network. And let's say
Speaker 1: that the connection between the two computers has a transmission
Speaker 1: speed of three hundred megabits per second, which means it
Speaker 1: can transfer three hundred million bits every second. How long
Speaker 1: will it take us to transfer the information on the
Speaker 1: DVD to the other computer. Well, we have to remember
Speaker 1: that a bite is eight bits, so four point seven
Speaker 1: billion bytes is actually thirty seven point six billion bits,
Speaker 1: and we can move three hundred million bits per second.
Speaker 1: So we do some division and we see that means
Speaker 1: it will take us about a hundred twenty five seconds
Speaker 1: or just over two minutes to transfer that full DVD
Speaker 1: to the other computer. That's, of course, assuming that we
Speaker 1: have a steady transfer speed, which never happens in real life,
Speaker 1: but you know, for the sake of this example, we'll
Speaker 1: just assume it works. And a lot of different stuff
Speaker 1: effects transmission speed, including how many other devices are transmitting
Speaker 1: data over that same network at that moment um, which
Speaker 1: also again applies to the network's bannedwidth capacity. But yeah,
Speaker 1: you get the idea now. Remembering the bits versus bites
Speaker 1: is really handy if you want to make some rough
Speaker 1: estimates of how long it's going to take you to
Speaker 1: download a specific something. I used the DVD example, but
Speaker 1: perhaps one that would be more applicable to folks listening
Speaker 1: to this show would be if you wanted to download
Speaker 1: a game like, let's say, to your PC or to
Speaker 1: a console. Some games like Call of Duty, Black Ops,
Speaker 1: Cold War are well over one hundred gigabytes in size,
Speaker 1: and since digital download has become a prevalent way that
Speaker 1: gamers get access to games, that means you have to
Speaker 1: download more than a hundred billion bytes or eight hundred
Speaker 1: billion bits of information to your console. And I imagine
Speaker 1: a lot of folks out there don't have access to
Speaker 1: an Internet connection that has a gigabit per second or
Speaker 1: faster transfer speed um. For example, I live in a
Speaker 1: pretty nice area of Atlanta. I mean it's not the nicest,
Speaker 1: but it's it's pretty nice, and and I max out
Speaker 1: and around a hundred megabits per second under ideal conditions.
Speaker 1: Most of the time, I'm somewhere in the fifty to
Speaker 1: sixty megabits per second range. I don't have access to
Speaker 1: gigabit fiber, I cannot get gigabit speeds, so fifty to
Speaker 1: sixty megabits per second is the best I can hope for.
Speaker 1: So knowing your transmission speed plus remembering that it's eight
Speaker 1: bits to a bite, can help you estimate how long
Speaker 1: it's going to take you to download that latest game.
Speaker 1: For me, it usually means I'll download and it'll finish
Speaker 1: shortly before the sequel to whatever it is I'm trying
Speaker 1: to download comes out. Okay, that's hyperbole, but not by
Speaker 1: much anyway. I hope that this episode has cleared up
Speaker 1: bits versus bites for most of you. It's it does
Speaker 1: get way more technical than what I went into. And
Speaker 1: you know, we didn't talk about things like what is
Speaker 1: a thirty two bits system versus a sixty four bit system?
Speaker 1: And you know, what does that mean effectively does that
Speaker 1: Does that have anything to do with the computer speed?
Speaker 1: What about things like processors and and how many bits
Speaker 1: they can handle? Does that mean they're faster? Um? That
Speaker 1: we might cover in a separate Tech Stuff Tidbits episode.
Speaker 1: This was really just more of the basics of bits
Speaker 1: versus bites and the confusing nature once you start getting
Speaker 1: into you know, the kill a byte and megabyte and
Speaker 1: gigabyte world, um, particularly if you're talking about RAM, because
Speaker 1: then you get back to that powers of two things
Speaker 1: and I get it from the computer science world, like
Speaker 1: I get the idea, uh that working within base to
Speaker 1: simplifies things massively and that therefore it makes way more
Speaker 1: sense to to look at large collections of numbers in
Speaker 1: terms of base two. Uh. But using the exact same
Speaker 1: terminology that we use to describe other groups of like
Speaker 1: data storage space. That's where that's where it grinds my gears,
Speaker 1: As some of my fellow podcasters like to say. Anyway,
Speaker 1: hope that that was useful information for you. If you
Speaker 1: have any suggestions for topics I should cover on tech stuff,
Speaker 1: whether it's a tidbit, a company, a trend in tech,
Speaker 1: anything like that, send me a message On Twitter, the
Speaker 1: handle for the show is text Stuff H s W
Speaker 1: and I'll talk to you again really soon. Text Stuff
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