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Speaker 1: Brought to you by the reinvented two thousand twelve Camray.

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Speaker 1: It's ready. Are you get in touch with technology with

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Speaker 1: tex Stuff from how stuff works dot Com. Hello again, everyone,

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Speaker 1: and welcome to the three hundred episode of text Stuff.

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Speaker 1: My name is Chris Poulette and I am an editor

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Speaker 1: here at how stuff works dot com and sitting across

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Speaker 1: from me as usual as senior writer Jonathan Strickland. You

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Speaker 1: know Jonathan, three episodes madness. This is text Stuff, all right.

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Speaker 1: Now that I've kicked Chris down a well, we can.

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Speaker 1: Oh he climbed up. Man. Dude has got some serious

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Speaker 1: forearm strength. Actually was all the fingertips. Yeah, yeah, yeah,

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Speaker 1: he's a baller. So we're gonna talk today about something

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Speaker 1: that you've had requested pretty much since episode one. Yep, yep.

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Speaker 1: And it's it's an involved topic. We could we could

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Speaker 1: talk about any one of the sub things we're about

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Speaker 1: to talk about for an entire episode of of tex Stuff.

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Speaker 1: So I think we're going to give give this sort

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Speaker 1: of an overview. Yeah yeah, So we're going to talk

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Speaker 1: today about programming languages, and to really get us started,

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Speaker 1: I have a quote here from C. A. R. Who

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Speaker 1: are h O A R E. Oh, And he says,

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Speaker 1: I conclude that there are two ways of constructing a

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Speaker 1: software design. One way is to make it so simple

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Speaker 1: that there are obviously no deficiencies, and the other way

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Speaker 1: is to make it so complicated that there are no

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Speaker 1: obvious deficiencies. And yeah, we're gonna talk about programming languages,

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Speaker 1: and that does apply to programming languages. Now, first of all,

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Speaker 1: you might ask, why do we have programming languages? Hey, Jonathan, Yeah,

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Speaker 1: why don't we have programming languages? Well, I'm glad you

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Speaker 1: asked that, Chris, because I was gonna have to wait

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Speaker 1: around a long time before the emails started coming in. Uh. Yeah.

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Speaker 1: The reason why we have it is because machines understand

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Speaker 1: a very well on the surface, a simple language, but

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Speaker 1: it's one that humans are not able to read easily.

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Speaker 1: Machine code is not something that humans easily read, right,

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Speaker 1: And ultimately, when you get down to it, a computer

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Speaker 1: understands basically two things on and off. Now, the type

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Speaker 1: of machine code is dependent on the kind of machine.

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Speaker 1: And when we say machine code, that doesn't necessarily just

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Speaker 1: mean computers. No, no, not at all. Yeah, because the

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Speaker 1: first machine codes were really for things like looms, right

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Speaker 1: looms and player pianos where that's another example. It's a

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Speaker 1: machine code that the coding translated to which notes played

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Speaker 1: when yes, uh, if you will remember a long time

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Speaker 1: ago we talked about how looms were mechanical. Looms were

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Speaker 1: programmed by using punched cards, um. And this was done

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Speaker 1: hundreds of years ago now um. So basically, the loom

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Speaker 1: would follow the instructions on the card. Where there was

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Speaker 1: a hole, it would do one thing, and when there

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Speaker 1: was a non hole, it would not do that thing

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Speaker 1: right again one or zero exactly. It also led to

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Speaker 1: the first episodes of sabotage, Sabo being a shoe that

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Speaker 1: someone would throw in the loom to break it because

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Speaker 1: they didn't want their jobs taken over by the machines.

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Speaker 1: Had times haven't changed manual weavers who uh did not

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Speaker 1: want to be displaced by an automatic loom unbeweavable. Yes,

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Speaker 1: it wasn't. I thought I could get through that, but

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Speaker 1: I couldn't. So yeah, machine code is this stuff that that, again,

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Speaker 1: machines can understand humans, humans can understand it, don't get

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Speaker 1: me wrong, It's just it takes so much effort to

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Speaker 1: understand it that it's not efficient for humans to to

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Speaker 1: write in machine code. I know people who can read binary,

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Speaker 1: I'm not one of them, right, Yeah, And there there

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Speaker 1: are people out there who are have what to me

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Speaker 1: would seem a mysterious gift to be able to read

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Speaker 1: and write in machine code in a way that you know,

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Speaker 1: I just can't comprehend. Um. So programming languages are a

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Speaker 1: way of of addressing that problem. It's it's an attempt

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Speaker 1: to create a language that is easier for humans to

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Speaker 1: uh to comprehend, and to create a set of instructions

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Speaker 1: for a machine that don't require you to think in

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Speaker 1: machine code. Yes, yes, um, I am Actually I have

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Speaker 1: actually been taking a a Python class over the past

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Speaker 1: few weeks, right. Uh, actually that's where it got its name.

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Speaker 1: I didn't really Yeah. Uh, Python is We'll get into

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Speaker 1: this later, but I just want to set this up.

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Speaker 1: Python is an object oriented programming language. Um. But I'm

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Speaker 1: actually in LESSNSE with the instructors Scott Turnbull, who's a

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Speaker 1: who's a friend, and uh, he was explaining that it's

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Speaker 1: not it's not that you're people are are afraid to

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Speaker 1: learn programming languages because they seem kind of complex. But

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Speaker 1: it's not that's it's not that you're not smart enough,

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Speaker 1: he says, it's actually that you're not dumb enough because

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Speaker 1: the computer doesn't really understand things. And the computer language

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Speaker 1: is there too to be sort of an interface between

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Speaker 1: you and the computer to give it specific instructions. Because

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Speaker 1: it doesn't know what you're trying to do. You have

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Speaker 1: to be very specific, and that's what the languages are

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Speaker 1: trying to do. But the thing is that depending on

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Speaker 1: the machine, as Jonathan was saying before, and depending on

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Speaker 1: what you're trying to do. Uh, people keep writing new

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Speaker 1: languages because one language maybe too sophisticated for the particular

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Speaker 1: kind of machine, or as machines become more sophisticated, you

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Speaker 1: might need something to take advantage of that where you

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Speaker 1: can really use the capabilities of those machines. Yeah, if

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Speaker 1: you look at some of the older programming languages, they

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Speaker 1: just weren't designed to to deal with the operations that

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Speaker 1: modern machines can can execute, and so you end up

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Speaker 1: having to if you're using those older languages, the programs

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Speaker 1: get more and more complex and larger and larger because

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Speaker 1: you have to have more lines of code in order

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Speaker 1: to facilitate these operations. Um or you have a language

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Speaker 1: that's so complex that it takes you three days just

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Speaker 1: to figure out how to write one line of code

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Speaker 1: to get what you what you want done done. So yeah,

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Speaker 1: it's a little um, it's a little daunting for the layman. Uh.

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Speaker 1: From a high level point of view, there are two

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Speaker 1: main features that programming languages have to have, or that

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Speaker 1: all languages really have, um. And these are not the

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Speaker 1: only two features, but two main features. One is semantics,

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Speaker 1: which is the meaning of what you are saying, and

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Speaker 1: then the other syntax, which is the form of what

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Speaker 1: you're saying. And the syntax and the semantics together are

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Speaker 1: kind of the set of rules that you have to

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Speaker 1: follow in order for a language to be understandable. And

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Speaker 1: that really goes for human languages as well. Yes, yeah,

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Speaker 1: all words have to go in a certain order for

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Speaker 1: somebody else to understand them, right, And you can play

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Speaker 1: without a little bit and humans are still able to

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Speaker 1: understand it. For example, so if you speak like Yoda,

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Speaker 1: that's exactly what I was thinking when you said that. Right.

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Speaker 1: If you hear Yoda talk in the Star Wars movies,

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Speaker 1: you know Yoda has his own syntax. He he throws

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Speaker 1: words in in odd odda order all the time, particularly

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Speaker 1: more in the prequels. I noticed his syntax got funkier

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Speaker 1: the younger he was. As he got older, I guess

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Speaker 1: he cut that crap out anyway, So, uh, nice Frank

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Speaker 1: OSes in the office everyone. So yeah, humans can actually

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Speaker 1: deal with a little variation in syntax. Computers not so much.

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Speaker 1: Computers are not good at adapting to new situations. They

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Speaker 1: have to, you know, you have to be able to

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Speaker 1: program it in a way that it makes sense to

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Speaker 1: the computer, so it can't really interpret if you start

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Speaker 1: messing with the syntax. There are two main categorizations, I

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Speaker 1: would say for for programming languages. There are low level

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Speaker 1: programming languages and high level programming languages. Yes, Now, a

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Speaker 1: low level programming language is one that is based on

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Speaker 1: mnemonic devices that are easy for a relatively easy for

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Speaker 1: humans to understand and remember. And they are, but they

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Speaker 1: correspond very closely with machine code, so it's almost like

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Speaker 1: your programming in machine code, but it's just a slight

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Speaker 1: tweak from machine code so that it's not as monumental

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Speaker 1: a task to remember you know, which what is you know,

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Speaker 1: what makes up the letter A as opposed to the

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Speaker 1: you know, the the group of zeros and ones that

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Speaker 1: would normally use that in say binary code. So um,

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Speaker 1: assembly language is an example of a low level computing language.

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Speaker 1: So if you were to write something in assembly, you'd

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Speaker 1: be writing it in a mnemonic style that closely models

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Speaker 1: machine language. Now, high level programming languages introduce a concept

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Speaker 1: called abstraction. Now, abstraction means you step a little further

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Speaker 1: away from these these specific steps the computer has to

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Speaker 1: go through in order to to execute the operation you're

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Speaker 1: you are telling it to do, and you can get

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Speaker 1: a little more free with the language. Now, the biggest

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Speaker 1: advancement would be if you created some sort of natural

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Speaker 1: language computer language where you would just type in a

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Speaker 1: sentence and the computer would be able to interpret that

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Speaker 1: as an actual command. So, you know, you would type in, uh,

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Speaker 1: I need you to add these two numbers together, and

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Speaker 1: then I need you to add this set of numbers together,

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Speaker 1: and then I need you to add both sums together,

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Speaker 1: and then I need you to give me an average.

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Speaker 1: You know, if you just type that in, then the computer,

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Speaker 1: if it had a way of interpreting natural language, would

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Speaker 1: give you the results you wanted. But we aren't really

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Speaker 1: there right. Well, let me let me take this from

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Speaker 1: the opposite side here for just a moment. You don't

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Speaker 1: necessarily want that because hit me with it, because again,

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Speaker 1: as Scott says, programming can be really repetitive, so you're

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Speaker 1: not going to want to type out, um, you know,

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Speaker 1: I want you to add these two numbers together. And

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Speaker 1: then you know you wanted to actually be as simple

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Speaker 1: as possible, So you don't want it to be literally

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Speaker 1: like that, just that, and I know you know that,

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Speaker 1: but I want to make it sort of clear that

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Speaker 1: it's not you want it to be to express that

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Speaker 1: sentiment in as few words as possible, because you're probably

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Speaker 1: going to have to type out the exact same kind

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Speaker 1: of thing many, many, many times over the course of

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Speaker 1: writing a program. Yeah, and if you were to write

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Speaker 1: a complicated program in assembly language, you would discover that

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Speaker 1: it's going to be enormous. This is gonna be lines

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Speaker 1: and lines and lines of code because with a language,

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Speaker 1: you are telling the computer what to do step by step.

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Speaker 1: And when I mean what to do, I'm talking about

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Speaker 1: not just telling it which operations to use, but when

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Speaker 1: to access memory, where it has to access it, what

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Speaker 1: information it has to pull up. I mean every single

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Speaker 1: set of instructions you can think about, you would pretty

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Speaker 1: much have to include there and the computer. If you

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Speaker 1: don't tell it to do something, the computer will not

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Speaker 1: do it. So think of it like a two year old. Yeah, alright,

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Speaker 1: so Chris, you've you've had experience with two year olds.

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Speaker 1: So let's say you tell your two years this is

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Speaker 1: like a Bill Cosby routine. In fact, this is a

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Speaker 1: Bill Cosby routine. You tell the two year old, all right,

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Speaker 1: you need to go upstairs, take a shower, and go

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Speaker 1: to bed. No, you can't do that because if you

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Speaker 1: just tell the kid to go upstairs, take a shower

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Speaker 1: and go to bed, the kid goes upstairs, gets in

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Speaker 1: the shower fully closed, turns on the water, then turns

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Speaker 1: off the water, and then gets into bed soaking wet.

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Speaker 1: So what you have to do is say, all right,

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Speaker 1: walk up the stairs, open the door to the bathroom,

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Speaker 1: go inside the bathroom, close the door to the bathroom,

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Speaker 1: take off your clothes, get in the shower, turn on

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Speaker 1: the water, wash shampoo, rents, get out of the shower, etcetera, etcetera.

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Speaker 1: You have to give it every single instruction or else

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Speaker 1: it skips steps or in the case of computers, it

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Speaker 1: may not skip steps. It may just say, well, I

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Speaker 1: don't know what to do because you haven't told me.

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Speaker 1: Well see I I uh, I don't know that that's

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Speaker 1: necessarily true of all two year olds. I have difficulty

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Speaker 1: weaning mind from the iPad long enough to do anything right.

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Speaker 1: But um, yeah, but you're if you're familiar with the

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Speaker 1: Cosby routine I'm talking about, I am, and that of course, well,

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Speaker 1: you know, being a stand up or sit down comedian.

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Speaker 1: In his case, uh, you know, he exaggerates a tiny bit,

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Speaker 1: but you're you're, you're onto something. And it also reminds

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Speaker 1: me a little bit of the text games when you

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Speaker 1: have to be very specific. It's like, no, open the

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Speaker 1: door and go in right. Well, yeah, the text based

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Speaker 1: games that that Chris is talking about, there were these

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Speaker 1: these games that like uh, info games used to do,

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Speaker 1: like games that were all they would give you a

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Speaker 1: paragraph of text that would explain the situation, and then

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Speaker 1: you would type in what you wanted to do next

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Speaker 1: and go left right and there might go left correct,

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Speaker 1: There might be a there might be a very specific

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Speaker 1: way that the game will allow you to move forward.

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Speaker 1: And if you type in something that's similar to that,

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Speaker 1: like Let's say you type in go north, but the

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Speaker 1: game would only recognize walk north, even though both of

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Speaker 1: those things mean the same thing. You know, if you

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Speaker 1: don't type in the right command right the same thing

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Speaker 1: to us, it means the same thing to us, it

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Speaker 1: doesn't mean the same thing to the computer because it

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Speaker 1: just doesn't it doesn't have that vocabulary. So a similar language,

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Speaker 1: like I said, is more or less the step by

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Speaker 1: step set of directions for a computer. So that's a

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Speaker 1: low level language. The high level languages, they abstract languages,

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Speaker 1: get a little more free because you have a you

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Speaker 1: have a sort of a step between the programming language

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Speaker 1: you've built a program in and that the way the

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Speaker 1: computer actually executes the code. There's a there's a step

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Speaker 1: in between there, which can vary depending upon which programming

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Speaker 1: language you're using. Um So, whereas in the first example,

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Speaker 1: you know, I have to go and tell the two

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Speaker 1: year old step by step what needs to happen in

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Speaker 1: order for the desired result that to come out with

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Speaker 1: a high level language, because we've previously defined certain uh

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Speaker 1: operations and certain data sets. Because that stuff has been

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Speaker 1: defined previously, I might have the freedom to say, go upstairs,

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Speaker 1: take a shower and go to bed, and then the

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Speaker 1: computer because those that set of data and the set

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Speaker 1: of operations have been previously defined will know to follow

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Speaker 1: its step by step, even though I did not lay

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Speaker 1: it all out piece by piece by piece. Yeah, the

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Speaker 1: more sophisticated languages will let you define those parameters. You

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Speaker 1: might say, I've got I want you to do these

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Speaker 1: fifteen things, and you're gonna have to do these fifteen

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Speaker 1: things seventy five times over the course of this. Well,

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Speaker 1: you might be able to create, uh m, a basically

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Speaker 1: a string of commands and say, when I say do this,

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Speaker 1: that means make all these fifteen things happen, so that

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Speaker 1: it's it's essentially like a shorthand you're yeah, exactly, that's

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Speaker 1: a better that's even better. Um, so you're going, okay,

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Speaker 1: so every time, So at first you might have to

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Speaker 1: do some some defining. You're gonna have to to explain,

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Speaker 1: uh in the language what you want these these things

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Speaker 1: to do, and then it will be able to execute

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Speaker 1: those those steps. But you know, it hasn't really always

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Speaker 1: been that way. Um. There are many, many, many languages,

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Speaker 1: some of which are are now famous, um, some of

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Speaker 1: which people still need to know because their legacy systems

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Speaker 1: out there that still run on these languages. Uh. Yeah.

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Speaker 1: I I have a friend who uh um works for

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Speaker 1: as a programming uh programmer, and she basically said, yeah,

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Speaker 1: I work with a language that not only is it

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Speaker 1: older than I am, but it has been mothballed for

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Speaker 1: almost as long as I've been alive. Uh And the

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Speaker 1: only reason they use it is because we're using these

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Speaker 1: computers and this is the language they understand. You happen

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Speaker 1: to know which one it was? No, I don't, Well,

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Speaker 1: I mean there's not There are thousands of programming languages

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Speaker 1: out there, which is one of the reasons why we

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Speaker 1: can't really do a full episode on programming languages period

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Speaker 1: because there are a lot of flavors, and they don't

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Speaker 1: you know, they take a lot of different approaches to programming. Now,

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Speaker 1: their goal is pretty much the same across the board.

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Speaker 1: The goal is to create a language that is easy

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Speaker 1: for humans to program in in such a way that

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Speaker 1: they can build applications for computers. But some of these

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Speaker 1: are designed with specific applications in mind. Some of them

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Speaker 1: are things like business applications or banking applications, and or

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Speaker 1: air traffic control systems. Systems that have a very specific

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Speaker 1: set of parameters that you would want to program for,

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Speaker 1: and then the others are more free form, right that

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Speaker 1: the designed for programs that maybe don't have as specific

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Speaker 1: a use scenario. And uh, it's kind of interesting to

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Speaker 1: talk about the history of these. UM there's actually I

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Speaker 1: wanted to mention before we really get into it. I

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Speaker 1: found a kind of neat timeline. It's an interactive timeline

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Speaker 1: that um you can move your cursor around the timeline.

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Speaker 1: The timeline itself is miniaturized, so when you look at

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Speaker 1: it just looks like a white bar with some gray

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Speaker 1: shading in it. And it turns out the reason for

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Speaker 1: that is because it's an enormous timeline and so when

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Speaker 1: you move your cursor it zooms in. I don't know,

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Speaker 1: it's got to be like twenty times or something. And

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Speaker 1: or if you to actually read what the the the

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Speaker 1: various languages are, but it said you can find that

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Speaker 1: at www dot l e V E n e Z

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Speaker 1: dot com, slash l A n G so Levinez dot com,

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Speaker 1: slash lang and it's a neat it's a neat time line.

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Speaker 1: I really do recommend you checking out out if you're

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Speaker 1: interested in seeing sort of the development of programming languages,

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Speaker 1: especially if you want to see which ones were descended

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Speaker 1: from the earliest languages, because that's it's kind of like

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Speaker 1: a family tree, except it's it's laid out horizontally as

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Speaker 1: opposed to vertically. Right now, Um, when i i'm I'm

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Speaker 1: old enough to remember when people used some of the

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Speaker 1: older languages, and so do you know the oldest one

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Speaker 1: is UM? The the oldest one. The on is credited

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Speaker 1: as the oldest language, even though it was not implemented

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Speaker 1: until for for computer programming. Yes, it is called plunk

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Speaker 1: a cool. Wow, what a catchy name. Plank a cool.

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Speaker 1: It was developed by Conrad Zuza. It was for the

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Speaker 1: Z three computer. Yeah, so program It was created back

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Speaker 1: around so in the so this is a German computer

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Speaker 1: in the forties. It was created but not implemented, so

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Speaker 1: the language was never actually used until two thousands somewhere

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Speaker 1: around there. This is the Z three came up on

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Speaker 1: in a way earlier podcast that that was before the

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Speaker 1: three hundreds. Oh wait, this is the first of the

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Speaker 1: three hundreds. So if you're talking about the first you know,

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Speaker 1: sort of commercially available UM programming language that wasn't just

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Speaker 1: for a very specific proprietary device, and that's all it

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Speaker 1: was for, because there were some things they're programming languages

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Speaker 1: that are unique to a specific piece of hardware. Yeah,

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Speaker 1: but you were talking about a different one. I was

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Speaker 1: the first one that that comes to mind when I

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Speaker 1: think of historical languages is for Tran, right, which was

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Speaker 1: we talked about that a little bit in our our

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Speaker 1: epic series on IBM. Yeah. John Bacchus actually helps create

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Speaker 1: the language in nine in n so Actually it wasn't

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Speaker 1: that long after the Z three. I think they actually

349
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Speaker 1: started developing it even earlier, like in the early fifties.

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Speaker 1: But but yeah, fifty seven was the introduction to the market. Yep, yep.

351
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Speaker 1: And it's you know, there are still people who program

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Speaker 1: in FORTRAN. I would imagine, Yeah, there's some legacy systems

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Speaker 1: out there running on for trend. Yeah, you know. I mean,

354
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Speaker 1: here's the other thing is that if you create a

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Speaker 1: business or any really if you create any system that's

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Speaker 1: dependent upon a legacy system, it's really hard to move

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Speaker 1: off of that system because you know, the modern systems

358
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Speaker 1: may not be able to emulate the old system, and

359
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Speaker 1: so you have to keep supporting something that is otherwise

360
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Speaker 1: obsolete and perpetually unless you just completely revamp the way

361
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Speaker 1: you do things. And that's that's intimidating. It's a tough

362
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Speaker 1: thing to do. Yeah, I can't imagine anyone booting up

363
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Speaker 1: their IBM system Stroke three sixty and uh starting to

364
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Speaker 1: run a Java app on it. I just don't think

365
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Speaker 1: it's gonna happen. Probably not. UM another one of the

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Speaker 1: languages I was thinking about. UM. There are three really

367
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Speaker 1: that come to mind, Like when I think of old

368
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Speaker 1: programming language is tons of others. COBALL is another one,

369
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Speaker 1: which is the common business oriented language, which is very

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Speaker 1: business heavy. It was a procedural language that was designed

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Speaker 1: for programming business applications. Uh. And actually COBAL was one

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Speaker 1: of those programming languages that that came into demand again

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Speaker 1: about a little over a decade ago. Do you know

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Speaker 1: why what happened a little over a decade ago? M M.

375
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Speaker 1: I'm thinking you're probably talking about the major world shaking

376
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Speaker 1: event that was the Y two K problem exactly. There

377
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Speaker 1: were a lot of legacy systems that were running Cobal.

378
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Speaker 1: They were running Cobal programming, you know, it was it

379
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Speaker 1: was the systems themselves were programmed in Cobal. And we

380
00:21:38,680 --> 00:21:41,280
Speaker 1: were coming up on the Y two K problem, which,

381
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Speaker 1: if you guys don't remember, was the issue of the date,

382
00:21:44,600 --> 00:21:48,239
Speaker 1: not it was only the date was being expressed as

383
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Speaker 1: a two digit numbers, which meant that when nine nine

384
00:21:50,840 --> 00:21:54,800
Speaker 1: became zero zero, that some of these systems might interpret

385
00:21:54,880 --> 00:21:57,159
Speaker 1: that to mean that the years no longer. It's not

386
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Speaker 1: two thousand, but is nineteen hundred. But it presupposes the

387
00:22:00,920 --> 00:22:03,520
Speaker 1: first two digits were one nine. And that's actually sort

388
00:22:03,560 --> 00:22:07,480
Speaker 1: of important because, um, you know, not only do programmers

389
00:22:07,520 --> 00:22:11,159
Speaker 1: look for ways to be very concise. When a lot

390
00:22:11,240 --> 00:22:13,720
Speaker 1: of people were programming in Cobal when it was first

391
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Speaker 1: released in ninety nine, Um, you had to be as

392
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Speaker 1: simple and precise as possible because, uh, you know, a

393
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Speaker 1: thumb drive, a flash drive has more memory than those

394
00:22:29,000 --> 00:22:31,480
Speaker 1: machines had at that point. Yeah, you're super computers back

395
00:22:31,520 --> 00:22:37,280
Speaker 1: then were pitiful compared to the handheld devices we have today. Yeah,

396
00:22:37,320 --> 00:22:39,440
Speaker 1: so they had to you know, lopping off the first

397
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Speaker 1: two digits of the year. Uh, you don't need them,

398
00:22:42,320 --> 00:22:45,080
Speaker 1: that's two extra digits I don't have to worry about. Well. Yeah,

399
00:22:45,119 --> 00:22:48,080
Speaker 1: and you gotta remember also, these guys when they were programming,

400
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Speaker 1: they knew that the field they were in. And when

401
00:22:50,760 --> 00:22:54,359
Speaker 1: I say these guys, there were female programmers to back

402
00:22:54,400 --> 00:22:56,720
Speaker 1: in the day. But all of these people they knew

403
00:22:57,040 --> 00:22:59,040
Speaker 1: back when they were getting into it that this was

404
00:22:59,080 --> 00:23:03,040
Speaker 1: a field that was evolving rapidly. Um, there were a

405
00:23:03,080 --> 00:23:06,159
Speaker 1: lot of different people working on programming languages and and

406
00:23:06,440 --> 00:23:09,160
Speaker 1: operating systems, and the sky was the limit. I mean,

407
00:23:09,200 --> 00:23:11,960
Speaker 1: there was nowhere to go but but up and out.

408
00:23:12,040 --> 00:23:15,439
Speaker 1: I mean it was just brand new frontier. And I

409
00:23:15,480 --> 00:23:18,600
Speaker 1: don't think anyone thought we're still going to be dependent

410
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Speaker 1: upon this old system, you know, three or four or

411
00:23:21,960 --> 00:23:24,480
Speaker 1: five decades from now, where this will be a problem.

412
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Speaker 1: By then will be on totally different systems and this

413
00:23:26,520 --> 00:23:29,000
Speaker 1: stuff will be a long forgotten memory. It's just this

414
00:23:29,080 --> 00:23:32,199
Speaker 1: is the stepping stone for us to get there. Not thinking, no,

415
00:23:32,440 --> 00:23:35,880
Speaker 1: there's gonna be companies out there. You still using these

416
00:23:35,880 --> 00:23:39,879
Speaker 1: old systems because the business, the business reality is that

417
00:23:39,920 --> 00:23:45,840
Speaker 1: you can't revamp every with every new development, new technological development.

418
00:23:46,240 --> 00:23:49,360
Speaker 1: Was the old folks, he saying, says, if it ain't broke,

419
00:23:49,720 --> 00:23:54,400
Speaker 1: don't fix it. And even if it is broken, I'm

420
00:23:54,400 --> 00:23:57,359
Speaker 1: looking at my laptop, all right. Yeah. The other one

421
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Speaker 1: I was thinking about is Pascal episode three. I still

422
00:24:00,440 --> 00:24:04,360
Speaker 1: have a broken laptop well, which came around around nineteen.

423
00:24:05,240 --> 00:24:09,080
Speaker 1: I'm just saying it's not working at all. Oh, Pascal,

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Speaker 1: I'm sorry, we're on Pascal. Well. I was just mentioning.

425
00:24:11,240 --> 00:24:14,720
Speaker 1: I mean, I'm leaving out tons and tons of languages UM,

426
00:24:15,200 --> 00:24:17,880
Speaker 1: which was very popular in the seventies and eighties, which

427
00:24:17,920 --> 00:24:19,560
Speaker 1: you know, as I was growing up, I just heard

428
00:24:19,560 --> 00:24:22,800
Speaker 1: a lot of people programming in pascal UM and it

429
00:24:22,920 --> 00:24:25,320
Speaker 1: was just a very very It was actually sort of

430
00:24:25,320 --> 00:24:31,640
Speaker 1: a descendant UM of four tran and in some ways UM.

431
00:24:31,680 --> 00:24:34,280
Speaker 1: But you know, also in the seventies, I have this

432
00:24:34,320 --> 00:24:36,840
Speaker 1: feeling we need to to start tightening up because we're

433
00:24:36,840 --> 00:24:42,040
Speaker 1: probably getting shorter on time. Uh see the the snow

434
00:24:42,320 --> 00:24:48,000
Speaker 1: seat not see um. Yeah see that just a letter

435
00:24:48,160 --> 00:24:52,680
Speaker 1: c UM started to enter usage. And I remember when

436
00:24:52,680 --> 00:24:54,560
Speaker 1: I got my Amiga that a lot of people were

437
00:24:54,560 --> 00:24:56,960
Speaker 1: starting to get into a descendant of C. You know,

438
00:24:57,000 --> 00:25:01,520
Speaker 1: C plus you got C plus plus yeah. Yeah. See

439
00:25:02,240 --> 00:25:05,240
Speaker 1: see we're having around types of language. But yeah, the

440
00:25:05,280 --> 00:25:07,960
Speaker 1: C language was one of those that was kind of

441
00:25:08,000 --> 00:25:11,679
Speaker 1: intended as a system programming language for uh, for the PDP,

442
00:25:11,840 --> 00:25:14,040
Speaker 1: and then it ended up kind of exploding beyond that

443
00:25:14,119 --> 00:25:16,880
Speaker 1: and some programmers will tell you that it got out

444
00:25:16,880 --> 00:25:19,280
Speaker 1: of control, that people were using it well beyond what

445
00:25:19,320 --> 00:25:20,880
Speaker 1: it was supposed to be used for. And that's kind

446
00:25:20,880 --> 00:25:22,760
Speaker 1: of why we have the development of C plus and

447
00:25:22,800 --> 00:25:25,680
Speaker 1: then C plus plus. These were enhancements to that C

448
00:25:25,880 --> 00:25:30,320
Speaker 1: programming language to take into account new capabilities of machines

449
00:25:30,440 --> 00:25:33,359
Speaker 1: that CE just did not support. And you know, you

450
00:25:33,359 --> 00:25:36,159
Speaker 1: could program and see if you wanted to for these

451
00:25:36,200 --> 00:25:39,560
Speaker 1: these capabilities, but it would mean that your program would

452
00:25:39,600 --> 00:25:42,480
Speaker 1: have to be that many more lines of code to

453
00:25:42,520 --> 00:25:45,000
Speaker 1: be able to incorporate all the stuff that you could

454
00:25:45,040 --> 00:25:47,360
Speaker 1: do now. And C plus and C plus plus meant

455
00:25:47,440 --> 00:25:49,439
Speaker 1: to try and make that a little more elegant. But

456
00:25:49,520 --> 00:25:53,400
Speaker 1: even then you still have programmers saying that's out of control. Um,

457
00:25:53,440 --> 00:25:55,000
Speaker 1: I do want to backtrack just one second. I want

458
00:25:55,000 --> 00:25:58,560
Speaker 1: to mention one major programming language that was never really

459
00:25:58,560 --> 00:26:00,679
Speaker 1: meant to be a big programming which was meant to

460
00:26:00,680 --> 00:26:05,000
Speaker 1: be a teaching tool. Basic. Yeah. I was going to

461
00:26:05,200 --> 00:26:08,640
Speaker 1: mention that I did some of my research UM from

462
00:26:08,640 --> 00:26:14,439
Speaker 1: Britannica and uh it had listed UM fortran and see

463
00:26:14,600 --> 00:26:19,480
Speaker 1: as UM algorithmic languages and COBAL as a business oriented language.

464
00:26:19,480 --> 00:26:23,200
Speaker 1: But Basic was definitely and Pascal too, were both education

465
00:26:23,400 --> 00:26:28,000
Speaker 1: oriented languages. Yeah. Basic stands for beginners all purpose symbolic

466
00:26:28,080 --> 00:26:34,720
Speaker 1: instruction code. Yeah, this is this is old by today's standards. Yeah. Yeah.

467
00:26:34,760 --> 00:26:38,120
Speaker 1: And I found a great quote. It's an anonymous quote,

468
00:26:38,119 --> 00:26:40,359
Speaker 1: so I don't you know, it's kind of hard to

469
00:26:40,480 --> 00:26:42,080
Speaker 1: call it a quote in that case. This is the

470
00:26:42,080 --> 00:26:44,400
Speaker 1: one you're gonna did you already shared with me? Yeah? Yeah,

471
00:26:44,440 --> 00:26:47,840
Speaker 1: I love this this quote. Though Basic is two computer languages,

472
00:26:48,000 --> 00:26:51,720
Speaker 1: what Roman numerals are too arithmetic? The idea of being

473
00:26:51,720 --> 00:26:56,480
Speaker 1: the Basic teaches you the basic principles of programming, but

474
00:26:56,640 --> 00:27:01,679
Speaker 1: was not meant to actually design complex programs, right. It

475
00:27:01,720 --> 00:27:04,840
Speaker 1: was just meant to give you the the the basic essentials.

476
00:27:06,000 --> 00:27:09,359
Speaker 1: But that didn't stop people from actually programming fairly complex

477
00:27:09,960 --> 00:27:14,200
Speaker 1: applications in Basic, which meant that you had to create

478
00:27:14,280 --> 00:27:16,240
Speaker 1: lots and lots of lines of code in order to

479
00:27:16,440 --> 00:27:19,879
Speaker 1: create these, um, these these programs. Yeah. My my first

480
00:27:19,880 --> 00:27:23,760
Speaker 1: experience in computer programming, actually writing computer programs myself, was

481
00:27:24,000 --> 00:27:26,640
Speaker 1: in Amiga Basic, which I used on my Amigo one thousand,

482
00:27:27,240 --> 00:27:29,880
Speaker 1: UM and I remember it was. It was every bit

483
00:27:29,880 --> 00:27:32,800
Speaker 1: as tedious as you might imagine. I did have a

484
00:27:32,800 --> 00:27:36,639
Speaker 1: lot of friends who coded on Commodore sixty four's and

485
00:27:36,760 --> 00:27:40,240
Speaker 1: Vick twenties for that matter. Um, and they were pretty

486
00:27:40,320 --> 00:27:43,159
Speaker 1: much using Basic too. It's a matter of factored. I

487
00:27:43,160 --> 00:27:45,679
Speaker 1: also can remember the days when you would find basic

488
00:27:45,720 --> 00:27:48,560
Speaker 1: code in the back of computer magazines. Oh yeah, here's

489
00:27:48,560 --> 00:27:49,960
Speaker 1: a great program, and I will teach you how to

490
00:27:50,000 --> 00:27:51,840
Speaker 1: do this, and this is this is one that will

491
00:27:51,880 --> 00:27:56,399
Speaker 1: project your birthday indefinitely. Yes, you know stuff like that,

492
00:27:56,440 --> 00:27:58,280
Speaker 1: you test handy like it would tell you like what

493
00:27:58,440 --> 00:28:00,880
Speaker 1: day of the week your birthday would fall on from

494
00:28:00,920 --> 00:28:03,040
Speaker 1: that point forward. That kind of stuff. I mean, that's

495
00:28:03,359 --> 00:28:05,240
Speaker 1: you know, it sounds kind of silly, but it was

496
00:28:05,359 --> 00:28:09,240
Speaker 1: teaching people to the basics of computer programming. Yeah. Absolutely,

497
00:28:09,280 --> 00:28:13,200
Speaker 1: And there are people who are I've read several accounts

498
00:28:13,200 --> 00:28:14,919
Speaker 1: that there are many people who are in who are

499
00:28:14,960 --> 00:28:19,280
Speaker 1: programmers today who write amazing stuff, right that the video games,

500
00:28:19,359 --> 00:28:21,680
Speaker 1: the three D video games that everybody loves so much.

501
00:28:21,960 --> 00:28:26,159
Speaker 1: And they started writing basic on their home computer, which was,

502
00:28:26,240 --> 00:28:28,760
Speaker 1: you know, a tiny little machine, you know, like an

503
00:28:28,800 --> 00:28:32,919
Speaker 1: Apple to E or something six four. You've got, Um,

504
00:28:33,000 --> 00:28:35,320
Speaker 1: you gotta start somewhere, just start somewhere, and it's kind

505
00:28:35,359 --> 00:28:38,360
Speaker 1: of it's it is pretty fascinating. Did you have a

506
00:28:38,520 --> 00:28:40,720
Speaker 1: p L on your list. A p L. Yeah, it

507
00:28:41,000 --> 00:28:45,480
Speaker 1: stands for a programming language. I'm not joking. You know

508
00:28:45,560 --> 00:28:49,040
Speaker 1: the computer people really like those those uh yeah, those

509
00:28:49,080 --> 00:28:52,160
Speaker 1: those acronyms that when you when you break it down,

510
00:28:52,200 --> 00:28:54,520
Speaker 1: you're like, come on, it's it's late in the day

511
00:28:54,520 --> 00:28:57,000
Speaker 1: on Friday, and I can I forgot what that. Technically,

512
00:28:57,040 --> 00:28:58,600
Speaker 1: it's not an acronym. We're going to get someone to

513
00:28:58,640 --> 00:29:00,920
Speaker 1: write in because acronym has to no, it has it

514
00:29:00,960 --> 00:29:03,400
Speaker 1: has a name. And I'm because I'm hungry and it's

515
00:29:03,440 --> 00:29:05,080
Speaker 1: the end of the day, I can't remember what it is. Yeah,

516
00:29:05,080 --> 00:29:07,280
Speaker 1: we usually do this in the morning, but because this

517
00:29:07,360 --> 00:29:10,040
Speaker 1: is Madness and episode three hundred, we're actually doing this

518
00:29:10,080 --> 00:29:12,200
Speaker 1: in the afternoon. Also, I had something else I had

519
00:29:12,240 --> 00:29:15,160
Speaker 1: to do this morning, so anyway, but yeah, a programming language.

520
00:29:15,200 --> 00:29:18,200
Speaker 1: It was mostly used for accounting packages and air traffic

521
00:29:18,200 --> 00:29:22,000
Speaker 1: control systems. But the thing about a p L is

522
00:29:22,000 --> 00:29:25,280
Speaker 1: that it had an enormous character set. Now, most programming

523
00:29:25,320 --> 00:29:29,920
Speaker 1: languages use your basic letters, numbers, and symbols for like

524
00:29:29,960 --> 00:29:32,200
Speaker 1: the things you find on the keyboard basically as key

525
00:29:32,320 --> 00:29:35,640
Speaker 1: character exactly. A p L is not like that. It

526
00:29:35,800 --> 00:29:38,240
Speaker 1: is a whole set of characters that you're not You

527
00:29:38,240 --> 00:29:41,000
Speaker 1: can look at that keyboard all day long, you are

528
00:29:41,080 --> 00:29:43,520
Speaker 1: not going to find the symbols that appear in an

529
00:29:43,840 --> 00:29:46,720
Speaker 1: line of ap L code. But because it has this

530
00:29:46,920 --> 00:29:51,600
Speaker 1: enormous character set, it also is able to uh incorporate

531
00:29:51,640 --> 00:29:55,800
Speaker 1: lots of different operations into a single character. So a

532
00:29:55,840 --> 00:30:00,280
Speaker 1: program that might take five thousand lines of code mode

533
00:30:00,360 --> 00:30:02,680
Speaker 1: in some other programming language may only have to take

534
00:30:02,720 --> 00:30:04,960
Speaker 1: a couple of dozen lines of code in a p

535
00:30:05,240 --> 00:30:08,400
Speaker 1: L if you know the character set. But that character

536
00:30:08,440 --> 00:30:10,960
Speaker 1: I mean, it's a huge learning curve, right, I mean,

537
00:30:11,360 --> 00:30:15,080
Speaker 1: with this it's almost as difficult, not really, but from

538
00:30:15,080 --> 00:30:17,520
Speaker 1: a layman's perspective, it's almost as difficult as programming in

539
00:30:17,600 --> 00:30:21,360
Speaker 1: machine code itself, just because it's so dense. Um. I

540
00:30:21,400 --> 00:30:24,880
Speaker 1: actually looked at some code for a program that was

541
00:30:24,920 --> 00:30:28,080
Speaker 1: an early basic program and I and it. I forget

542
00:30:28,120 --> 00:30:29,959
Speaker 1: how many lines it was, but it was. It was.

543
00:30:30,720 --> 00:30:32,640
Speaker 1: It was a lot like a hundred lines and it

544
00:30:32,640 --> 00:30:35,120
Speaker 1: had been summarized into a single line of a p

545
00:30:35,320 --> 00:30:39,800
Speaker 1: L code. Yeah, it was. It was. No, I had

546
00:30:39,840 --> 00:30:43,480
Speaker 1: to take the word for it because I don't read

547
00:30:43,480 --> 00:30:45,600
Speaker 1: a p L code, so I can't really tell. Also,

548
00:30:45,640 --> 00:30:48,480
Speaker 1: this was making me think of Jonathan Coulton's song code

549
00:30:48,480 --> 00:30:53,560
Speaker 1: Monkey because his his code is not functional or elegant. Well,

550
00:30:54,840 --> 00:30:56,920
Speaker 1: this is also where hackers come from, right, I mean,

551
00:30:57,280 --> 00:31:00,440
Speaker 1: besides the physical hacking of machine, usually had actors who

552
00:31:00,440 --> 00:31:02,720
Speaker 1: would say, I want to make a program that does

553
00:31:03,560 --> 00:31:07,120
Speaker 1: desired outcome number one, and in order to do that,

554
00:31:07,160 --> 00:31:10,040
Speaker 1: I'm gonna code it this way. And it may not

555
00:31:10,120 --> 00:31:13,160
Speaker 1: be the most direct or elegant route. It may be

556
00:31:13,320 --> 00:31:16,160
Speaker 1: kind of cluji that you make your way through there

557
00:31:16,160 --> 00:31:17,760
Speaker 1: and you finally get to where you're going, but you

558
00:31:17,800 --> 00:31:20,800
Speaker 1: took the path less traveled. Robert Frost would have loved

559
00:31:20,800 --> 00:31:24,480
Speaker 1: your computer program. But uh yeah, you know that a

560
00:31:24,480 --> 00:31:26,520
Speaker 1: lot of hackers learned how to program this way. They

561
00:31:26,520 --> 00:31:28,840
Speaker 1: would have their their set outcome and they would program

562
00:31:28,840 --> 00:31:30,520
Speaker 1: their way to it, but the code might not be

563
00:31:30,600 --> 00:31:34,840
Speaker 1: the most elegant. So uh yeah, we we should mention

564
00:31:34,920 --> 00:31:39,440
Speaker 1: to the object oriented type programming languages, which is one

565
00:31:39,480 --> 00:31:42,640
Speaker 1: of the more modern I would say phases of programming

566
00:31:42,640 --> 00:31:46,280
Speaker 1: and more common today. Um not just to skip over

567
00:31:46,280 --> 00:31:48,360
Speaker 1: any others, I know there's probably other a couple other

568
00:31:48,680 --> 00:31:50,720
Speaker 1: of the earlier variety that you would like to mention.

569
00:31:50,920 --> 00:31:52,800
Speaker 1: I've got one that I'll talk about at the end.

570
00:31:53,080 --> 00:31:54,960
Speaker 1: But um, but that's but it sort of builds on

571
00:31:55,000 --> 00:31:58,640
Speaker 1: that idea basically that you are. It's a way to

572
00:31:58,680 --> 00:32:03,280
Speaker 1: manage how complex your programming is getting. Yeah, Usually if

573
00:32:03,320 --> 00:32:06,080
Speaker 1: you were to create let's say you create a program

574
00:32:06,280 --> 00:32:10,120
Speaker 1: in some and one that's not an object oriented programming language,

575
00:32:10,800 --> 00:32:12,880
Speaker 1: you have this for example, Yeah, you have the set

576
00:32:12,920 --> 00:32:15,880
Speaker 1: of data, and the entire program has access to that

577
00:32:15,960 --> 00:32:20,000
Speaker 1: same set of data. With object oriented programming, you actually

578
00:32:20,040 --> 00:32:24,760
Speaker 1: specify in which cases certain certain data gets used and

579
00:32:24,800 --> 00:32:28,440
Speaker 1: how it is used. So you have very specific methods

580
00:32:28,600 --> 00:32:30,959
Speaker 1: of dealing with that data and they can only be

581
00:32:31,040 --> 00:32:36,040
Speaker 1: used in that in that scenario within a program. And

582
00:32:36,120 --> 00:32:39,440
Speaker 1: this kind of cuts down on the possibility of having

583
00:32:39,600 --> 00:32:43,200
Speaker 1: these weird coding errors because you you know, because of

584
00:32:43,200 --> 00:32:46,880
Speaker 1: the rules of the programming language, you cannot misuse data

585
00:32:47,880 --> 00:32:52,200
Speaker 1: at least in theory. Give a person enough time and

586
00:32:52,240 --> 00:32:55,880
Speaker 1: there will find a way, right. But you might be

587
00:32:55,920 --> 00:32:57,480
Speaker 1: able to speak more to it than I can. Like,

588
00:32:58,040 --> 00:33:02,200
Speaker 1: my knowledge of programming is really from an academic standpoint,

589
00:33:02,240 --> 00:33:04,120
Speaker 1: but I don't have a lot of experience with it.

590
00:33:04,240 --> 00:33:07,480
Speaker 1: So did you want to elaborate anymore? I honestly, that's

591
00:33:07,480 --> 00:33:09,240
Speaker 1: about as far as I can get in depth for

592
00:33:09,320 --> 00:33:13,000
Speaker 1: object oriented programming, right right, Well, it's it's hierarchical and

593
00:33:13,080 --> 00:33:17,280
Speaker 1: it it basically it's a lot more elegant simply because

594
00:33:17,320 --> 00:33:18,720
Speaker 1: and I don't want to get the idea that I'm

595
00:33:18,760 --> 00:33:21,640
Speaker 1: a master program or anything like that, but it is

596
00:33:21,680 --> 00:33:24,800
Speaker 1: fascinating to be able to build this yourself. It's it does,

597
00:33:24,920 --> 00:33:28,840
Speaker 1: as you said, get into that hacker uh philosophy, it's not.

598
00:33:29,080 --> 00:33:31,480
Speaker 1: It's about taking things apart and trying to make something

599
00:33:31,760 --> 00:33:35,800
Speaker 1: better with it. And of course those the people who

600
00:33:36,120 --> 00:33:40,480
Speaker 1: hack into networks are doing using the same kinds of

601
00:33:40,480 --> 00:33:43,960
Speaker 1: tools for purposes that may or may not be illegal,

602
00:33:45,120 --> 00:33:49,600
Speaker 1: probably are not necessarily moral, all infiltration and manipulation, but

603
00:33:49,680 --> 00:33:52,400
Speaker 1: of course you know they're the ones who get all

604
00:33:52,440 --> 00:33:55,080
Speaker 1: the pressed, so that that that's where the negative connotation

605
00:33:55,080 --> 00:33:57,600
Speaker 1: for hacker gets in. But yeah, I mean this is

606
00:33:57,920 --> 00:34:01,800
Speaker 1: these these are the more sophisticated languages it you see today, Um,

607
00:34:01,920 --> 00:34:05,080
Speaker 1: you know, stuff like C plus plus uh. Simula actually

608
00:34:05,120 --> 00:34:08,240
Speaker 1: was the first, according to Britannic in nineteen sixty seven.

609
00:34:09,680 --> 00:34:12,160
Speaker 1: But you know there are others. You know, Java, Let's

610
00:34:12,200 --> 00:34:15,719
Speaker 1: say I thought Java was at least a semi object oriented. Yeah,

611
00:34:15,760 --> 00:34:19,120
Speaker 1: programming language and Python. There are many many others. I

612
00:34:19,160 --> 00:34:21,480
Speaker 1: know that you are interested in one of them, just

613
00:34:21,560 --> 00:34:25,520
Speaker 1: as from a historical standpoint, it's a it's a governmental language,

614
00:34:25,600 --> 00:34:27,320
Speaker 1: is A yes, it is. That was the one that

615
00:34:27,360 --> 00:34:29,720
Speaker 1: was going to mention. Yeah. Ada is the programming language.

616
00:34:29,719 --> 00:34:31,719
Speaker 1: It was commissioned by the Department of Defense in the

617
00:34:31,800 --> 00:34:34,879
Speaker 1: nineteen eighties, and the reason for commissioning it was they

618
00:34:34,920 --> 00:34:39,200
Speaker 1: wanted to have, uh, their own computer programming language for

619
00:34:39,280 --> 00:34:42,560
Speaker 1: their their systems. And Ada is kind of a descendant

620
00:34:42,680 --> 00:34:50,480
Speaker 1: of the Pascal language. Um, you, miss Lovelace. It's not

621
00:34:50,800 --> 00:34:53,680
Speaker 1: a lot of people's favorite language. I understand it can

622
00:34:53,719 --> 00:34:57,839
Speaker 1: be a little tricky at times, um, but you know,

623
00:34:58,560 --> 00:35:01,399
Speaker 1: it's it's funny shifting between languages. Uh. You know, I'm

624
00:35:01,440 --> 00:35:04,759
Speaker 1: also trying to learn Php at the same time, and

625
00:35:05,400 --> 00:35:09,120
Speaker 1: some of the constructs in PHP are completely removed in

626
00:35:09,160 --> 00:35:12,239
Speaker 1: Python as I'm learning, and that makes trying to learn

627
00:35:12,239 --> 00:35:15,160
Speaker 1: two languages simultaneously a little daunting. It's kind of like

628
00:35:15,239 --> 00:35:20,240
Speaker 1: learning two languages that are related but not perfectly in sync.

629
00:35:20,280 --> 00:35:23,640
Speaker 1: Like if you were learning say, French and Italian, that

630
00:35:23,680 --> 00:35:25,880
Speaker 1: would be fairly easy. The rules, the rules are very

631
00:35:25,920 --> 00:35:31,160
Speaker 1: similar and right right, but French and Latin might be

632
00:35:31,200 --> 00:35:35,000
Speaker 1: a little more challenging because you have cases in Latin

633
00:35:35,120 --> 00:35:40,040
Speaker 1: that are no longer used in modern French speech. So yeah,

634
00:35:40,160 --> 00:35:43,399
Speaker 1: the further away you get from that common well, in

635
00:35:43,400 --> 00:35:46,560
Speaker 1: this case, Latin is the common ancestor, Latin is the

636
00:35:46,600 --> 00:35:49,839
Speaker 1: ancestor to French. But then you can go uh all

637
00:35:49,880 --> 00:35:52,359
Speaker 1: the way out and say French and Chinese, in which

638
00:35:52,360 --> 00:35:55,520
Speaker 1: case there's no, there's no common ground. No, you don't

639
00:35:55,560 --> 00:35:58,280
Speaker 1: even you're not even using the same symbols to represent

640
00:35:58,360 --> 00:36:02,279
Speaker 1: words Latin and old fresh in for example, that's for

641
00:36:02,400 --> 00:36:04,879
Speaker 1: my that's for my old English peeps. I was gonna say,

642
00:36:04,880 --> 00:36:06,720
Speaker 1: you had to bring the Frissian in it. That loss

643
00:36:06,800 --> 00:36:12,600
Speaker 1: god kinning, y'all, that's how I roll Old English style.

644
00:36:13,080 --> 00:36:15,879
Speaker 1: Um so, so how are we doing on time? Where

645
00:36:15,960 --> 00:36:17,920
Speaker 1: we need to wrap this up? So yeah, this is

646
00:36:17,960 --> 00:36:21,160
Speaker 1: a This was our overview, and we will probably at

647
00:36:21,200 --> 00:36:24,719
Speaker 1: some point go into more depth on specific programming languages,

648
00:36:24,760 --> 00:36:28,120
Speaker 1: maybe talk about their development and and one exactly it

649
00:36:28,200 --> 00:36:32,120
Speaker 1: means to program in those languages. Yeah, yeah, that was that.

650
00:36:32,239 --> 00:36:34,680
Speaker 1: This is another one's topics that's kind of difficult for

651
00:36:34,800 --> 00:36:37,359
Speaker 1: us to tackle in a lot of depth because there

652
00:36:37,480 --> 00:36:40,400
Speaker 1: is a lot of there's a lot of breadth to it.

653
00:36:40,840 --> 00:36:43,239
Speaker 1: There's a wide for I mean even stuff like HTML,

654
00:36:43,719 --> 00:36:46,960
Speaker 1: which which is isn't really a programming language, a markup

655
00:36:47,239 --> 00:36:51,120
Speaker 1: markup language, but it shares some similarities to programming languages

656
00:36:51,160 --> 00:36:54,080
Speaker 1: because it has sets of instructions that tell a computer

657
00:36:54,239 --> 00:36:57,480
Speaker 1: how to do certain things right. And it's for somebody

658
00:36:57,480 --> 00:37:00,360
Speaker 1: who might be tempted to try programming but be afraid

659
00:37:00,360 --> 00:37:03,160
Speaker 1: of it, and he really shouldn't be, uh, but it

660
00:37:03,280 --> 00:37:04,680
Speaker 1: might be a way to get your feet wet, to

661
00:37:04,719 --> 00:37:06,640
Speaker 1: at least get an idea that, hey, this is what's

662
00:37:06,640 --> 00:37:08,920
Speaker 1: going on in the back end, but when it's on

663
00:37:08,960 --> 00:37:12,040
Speaker 1: the front end, it looks completely different. It looks polished.

664
00:37:12,080 --> 00:37:14,359
Speaker 1: You don't see any of this stuff. What's that's a

665
00:37:14,360 --> 00:37:18,880
Speaker 1: lot like what actual computer programming is. Like. Yeah, so yeah,

666
00:37:18,920 --> 00:37:20,520
Speaker 1: I'll tell you what. Why don't you let us know

667
00:37:20,640 --> 00:37:23,480
Speaker 1: on Twitter or Facebook if you have specific languages or

668
00:37:23,480 --> 00:37:27,719
Speaker 1: touch languages, maybe we can revisit it in more detail. Um,

669
00:37:27,760 --> 00:37:29,759
Speaker 1: but yeah, I would encourage people to at least try

670
00:37:29,760 --> 00:37:31,839
Speaker 1: it out because it's it can be a lot of fun,

671
00:37:31,840 --> 00:37:33,840
Speaker 1: and it could be extremely frustrating. But if you like

672
00:37:34,600 --> 00:37:37,200
Speaker 1: frustrating things, that are fun, programming might be for you. Yeah,

673
00:37:37,280 --> 00:37:39,080
Speaker 1: just just remember, at least you don't have to worry

674
00:37:39,080 --> 00:37:42,160
Speaker 1: about punch cards and getting punch cards out of order.

675
00:37:42,320 --> 00:37:44,239
Speaker 1: But we talked about punch cards in the past, so

676
00:37:44,400 --> 00:37:46,440
Speaker 1: that's why I felt good about We felt all right

677
00:37:46,480 --> 00:37:49,640
Speaker 1: about skipping over that. We didn't talk about compilers either. No, no, no,

678
00:37:49,719 --> 00:37:52,360
Speaker 1: But there's so much. I mean, there are entire college

679
00:37:52,400 --> 00:37:55,719
Speaker 1: courses that are based around just the principles of programming

680
00:37:55,760 --> 00:38:00,600
Speaker 1: language and college degrees exactly. So coming it all up

681
00:38:00,600 --> 00:38:02,640
Speaker 1: in a half hour podcast or in this case, a

682
00:38:02,760 --> 00:38:06,160
Speaker 1: thirty eight minute podcast is a little challenging. So if

683
00:38:06,200 --> 00:38:08,640
Speaker 1: you guys want to know more about specific programming languages,

684
00:38:08,680 --> 00:38:10,840
Speaker 1: like let's said, let us know on Twitter or Facebook

685
00:38:10,880 --> 00:38:13,560
Speaker 1: that are handled. There is text stuff h s W,

686
00:38:14,000 --> 00:38:16,400
Speaker 1: or you can send us an email and address is

687
00:38:16,560 --> 00:38:19,839
Speaker 1: tech stuff at how stuff works dot com. Happy three

688
00:38:19,920 --> 00:38:23,960
Speaker 1: hundred episode Chris, Happy three hundred to you too, Jonathan,

689
00:38:24,280 --> 00:38:26,640
Speaker 1: and we hope to talk to you guys again three

690
00:38:26,680 --> 00:38:32,360
Speaker 1: hundred more times really soon for moral news and thousands

691
00:38:32,360 --> 00:38:34,600
Speaker 1: of other topics. Is it how stuff works dot com.

692
00:38:34,800 --> 00:38:37,480
Speaker 1: To learn more about the podcast, click on the podcast

693
00:38:37,640 --> 00:38:41,160
Speaker 1: icon in the upper right corner. Of our homepage, The

694
00:38:41,239 --> 00:38:44,240
Speaker 1: How Stuff Works iPhone app has arrived. Download it today

695
00:38:44,480 --> 00:38:51,760
Speaker 1: on iTunes, brought to you by the reinvented two thousand

696
00:38:51,760 --> 00:38:53,960
Speaker 1: twelve camera. It's ready, are you