Latest / Ridiculous History / Ada Lovelace, Part Two: The Analytical Engine

Transcript

Ada Lovelace, Part Two: The Analytical Engine · Ridiculous History

0:00
Speaker 1: Ridiculous History is a production of I Heart Radio. Welcome
0:28
Speaker 1: back to the show Ridiculous Historians. Thank you, as always
0:32
Speaker 1: so much for tuning in. Shout out to our super producer,
0:35
Speaker 1: Max Williams. Add a very special shout out to our
0:38
Speaker 1: guest super producer returning again, the one, the only Mr Lowell, Brilliante.
0:44
Speaker 1: I've been your your nal. And this is part two
0:48
Speaker 1: of a two part series, isn't it. It is indeed
0:52
Speaker 1: part two of Ada Lovelace and her journey into mathematics
0:58
Speaker 1: and computation and you know, standard bearing, trail blazing, all
1:03
Speaker 1: that good stuff. Where where do we leave off, ben,
1:06
Speaker 1: if I'm not mistaken, She had just kind of returned
1:09
Speaker 1: to the fray of of of computer science after a
1:13
Speaker 1: brief stint in the domestic realm. Yes, after just a
1:18
Speaker 1: few months after the birth of her third child back
1:22
Speaker 1: in eighteen thirty nine, Aida decided to dive back into
1:27
Speaker 1: the world of numerousy and the world of mathematics. And
1:32
Speaker 1: it's interesting because we mentioned in part one. Will pause,
1:35
Speaker 1: everybody listen to part one. Do do do Do Do
1:38
Speaker 1: Do Do Do do do and you're back. So in
1:41
Speaker 1: part one we're still here in part one. Uh, she
1:45
Speaker 1: met the man who would become her mentor, Charles Babbage,
1:48
Speaker 1: and just before she got married in eighteen thirty five
1:54
Speaker 1: she got married, So a year before then, in eighteen
1:56
Speaker 1: thirty four, Babbage had finally and to mess around with
2:01
Speaker 1: something he called not the difference machine, but something he
2:06
Speaker 1: called an analytical engine. This is the old trope you
2:10
Speaker 1: might hear of punch cards being used in the first computers, right,
2:15
Speaker 1: that's right. UM. It was the earliest form of kind
2:20
Speaker 1: of large mainframe type computer systems that continue to use
2:24
Speaker 1: punch card systems well into the eighties. I believe, like
2:27
Speaker 1: you know, big massive UM room filling systems that use
2:31
Speaker 1: these punch cards to uh instruct the computer on what
2:36
Speaker 1: to do. UM. I'm a little hazy on exactly how
2:40
Speaker 1: that works. It's all kind of magic to me and
2:42
Speaker 1: in some ways, but essentially the punch cards are the instructions.
2:47
Speaker 1: In this situation, it was very rudimentary UM tasks and
2:50
Speaker 1: computations that could multiply and divide numbers UM and other
2:56
Speaker 1: more simplistic data related tasks using these punch cards as
3:01
Speaker 1: the programming instructions. UM really quickly. But do you remember
3:05
Speaker 1: back in probably the nineties, maybe the early to mid nineties,
3:08
Speaker 1: there used to be a chain of computer stores called
3:10
Speaker 1: babbage Is, was it? You know, always thinking about that
3:14
Speaker 1: was turn remember if they were computer stores or music stores?
3:18
Speaker 1: And I'm pretty sure you're right there, Uh they were
3:20
Speaker 1: computer stores, if I'm not mistaken. Babbage Is ultimately became
3:27
Speaker 1: game Stop. Babbage Is was the initial um, you know concept,
3:32
Speaker 1: and then it gradually uh mutated into the game Stop
3:36
Speaker 1: and movie Stopped and all of the various stops. Um.
3:40
Speaker 1: But but I might be mistaken, but I think that's right.
3:42
Speaker 1: It was a very popular chance of stores in the
3:44
Speaker 1: eighties and nineties, but named after Charles Babbage. I just
3:47
Speaker 1: always thought it was a funny word when I was
3:49
Speaker 1: a kid. Didn't founding partner of that or one of
3:53
Speaker 1: the early investors was Ross Pero, which is a deep
3:57
Speaker 1: cut for a lot of people. He was one of
3:59
Speaker 1: the he was one of the politicians in recent US
4:03
Speaker 1: history who actually got close to being a member of
4:07
Speaker 1: or candidate for viable third political party spoiler it didn't happen. No,
4:13
Speaker 1: And he was also one of the you know, more
4:15
Speaker 1: fledgling candidates that um was quite fun in his um
4:20
Speaker 1: portrayal on Saturday Night Live. I think it was Dana
4:23
Speaker 1: Carvey that did Ross Pero and he did the Whole
4:25
Speaker 1: Life Canna fanish Cana, fantis cana, fanish cana, fanish chap. Anyway,
4:30
Speaker 1: it was a thing, um, but it's true. So Babbage
4:33
Speaker 1: at this point has started to develop this system called
4:36
Speaker 1: the Analytical engine. Um. Initially it was just a concept.
4:40
Speaker 1: It was these sketches of this massive machine that literally
4:44
Speaker 1: used you know, mechanical pieces, mechanical components like costs very
4:50
Speaker 1: much so uh. And again they filled up rooms or
4:54
Speaker 1: would ultimately go into Philip rooms. What it would become
4:56
Speaker 1: of this lovelace was essentially the acting as a consultant
5:02
Speaker 1: on this project. She seemed to understand the idea behind
5:06
Speaker 1: it or the potential behind it, maybe even more so
5:09
Speaker 1: than Babbage himself. Yeah, and this is a theme that
5:13
Speaker 1: we saw earlier in part one of this series. She
5:16
Speaker 1: saw the potential for uh, for this to be a
5:20
Speaker 1: representation of what she called poetical science, which goes back
5:24
Speaker 1: to the earlier conflict with her mother about you know,
5:29
Speaker 1: math versus poetry. Please don't let my daughter turn into
5:32
Speaker 1: Lord Byron, because he's you know, kind of out there
5:37
Speaker 1: so Babbage goes to Turin to promote his work, to
5:43
Speaker 1: promote his ideas, and while he's promoting this, he realizes
5:49
Speaker 1: he needs a lot of financial support to make this
5:52
Speaker 1: trip happen. And Lovelace had already served as the primary
5:55
Speaker 1: interpreter of these drawing board ideas essentially, and to be clear,
6:00
Speaker 1: it's the building of the machine that requires a lot
6:04
Speaker 1: of money, so this is this is kind of a
6:07
Speaker 1: pitch trip for him as well. That's where he meets
6:11
Speaker 1: a mathematician with the wonderful name Luigi Fererico Menabrea, and
6:17
Speaker 1: this guy says, all right, your ideas check out, Charlie,
6:21
Speaker 1: I am gonna. I'm going to write a paper about
6:24
Speaker 1: this machine. And the paper gets published in October two
6:28
Speaker 1: in a Swiss journal. Lovelace translates it from French, and
6:33
Speaker 1: then while she's translating, she also adds her own notes.
6:37
Speaker 1: And the paper itself that this guy Luigi writes is
6:41
Speaker 1: about eight thousand words long, not bad, but the translation
6:46
Speaker 1: and the commentary that Lovelace creates comes in at about
6:50
Speaker 1: twenty thousand words, and Charles Pappage is saying, the notes
6:55
Speaker 1: of the Countess of Lovelace extend to about three times
6:58
Speaker 1: the length of the original memoir. And uh, he's again
7:03
Speaker 1: very very impressed with the quality of her thought and
7:06
Speaker 1: her scholarship. Yeah, it's true, and he certainly sees that
7:11
Speaker 1: in her. And despite you know, it being a very
7:15
Speaker 1: chauvinistic and patriarchal world, you know, the society in general,
7:19
Speaker 1: but also just the idea that men were the only
7:22
Speaker 1: people that had ideas worth paying attention to. UM. And
7:25
Speaker 1: you needed to get this Luigi Federico Montabrea to co
7:29
Speaker 1: sign on it. It wasn't enough for Lovelace to have
7:32
Speaker 1: done it, even though she obviously could have done it
7:33
Speaker 1: herself and clearly massively improved upon Um Montabree's ideas, UM
7:39
Speaker 1: by a significant margin. UM. But her notes were published,
7:44
Speaker 1: you know, our translation and the notes were published in
7:45
Speaker 1: eighteen forty three, UM. And according to Lovelace, you know,
7:49
Speaker 1: scholars and historians, this was her most important contribution to
7:55
Speaker 1: the burgeoning field of computer science, which really wasn't even
7:59
Speaker 1: they weren't even calling it that. Actually are are good
8:03
Speaker 1: friend Alex Williams, who composed our theme. His father, UM
8:07
Speaker 1: and mother are both computer scientists, and I briefly was
8:11
Speaker 1: talking to his dad about Lovelace UM and he just
8:15
Speaker 1: mentioned how you know, they were still using a punch
8:18
Speaker 1: card systems when he was coming up in you know,
8:21
Speaker 1: the computer science world, and how early on there was
8:24
Speaker 1: actually a programming language that was named after Lovelace. It
8:27
Speaker 1: was called Ada that was used by military UM computer
8:30
Speaker 1: scientists for military systems. But that you know, like similar
8:34
Speaker 1: with the whole Hidden Figures film, This like group of
8:36
Speaker 1: women that were very responsible for kind of cracking a
8:40
Speaker 1: lot of the science behind UM space travel, but we're
8:44
Speaker 1: largely relegated to kind of the shadows since the name.
8:46
Speaker 1: And this is very much the case for Lovely. She
8:48
Speaker 1: definitely didn't get her do until much much much later UM,
8:51
Speaker 1: but was clearly one of the most important figures in
8:55
Speaker 1: the development of this technology, more so even maybe than
8:58
Speaker 1: the guy who kind of envisioned it. Yeah, and quick
9:01
Speaker 1: note this will be if for any fellow ridiculous historians
9:04
Speaker 1: who are also fans of etymology. The original down computer
9:09
Speaker 1: described a person, not a machine from the sixteen forties,
9:13
Speaker 1: one who calculates or a reckon er, which I always thought,
9:17
Speaker 1: I always thought was so fascinating. You're right there, she's
9:20
Speaker 1: working against tremendous misogyny, she said earlier. In fact, her
9:23
Speaker 1: translation in her notes when they're published in eighteen forty three,
9:29
Speaker 1: the authorship is attributed to just a series of initials A, A, L.
9:34
Speaker 1: And and this is this is kind of a this
9:38
Speaker 1: kind of a kick in the pants because it is
9:42
Speaker 1: still considered one of her greatest contributions to to the field.
9:47
Speaker 1: And she walks through not just the possibilities of how
9:52
Speaker 1: it could work, but she also walks through the context
9:55
Speaker 1: leading to its creation. And she specifically shouts out the
10:00
Speaker 1: Jacquard loom, which was a silk weaving machine and it
10:04
Speaker 1: could create images using a chain of punched cards and lovelace.
10:10
Speaker 1: How poetically scientific is this? She says, Look, folks, this
10:13
Speaker 1: engine that Babbage has made is doing the same thing,
10:17
Speaker 1: but it's weaving mathematical problems. It's weaving patterns. They're just
10:23
Speaker 1: nu miracle. She also wrote how it could how it
10:28
Speaker 1: could work in a specific case test, like, here's an
10:30
Speaker 1: example of how you would use these punch cards to
10:34
Speaker 1: create a long sequence. And this outline that she that
10:40
Speaker 1: she thought up, that she created this is considered to
10:43
Speaker 1: be the very first computer program, and and she has
10:49
Speaker 1: this beautiful line where she says, the science of operations,
10:52
Speaker 1: as derived from mathematics more especially, is a science of
10:55
Speaker 1: itself and has its own abstract truth and value. Chef's kiss. Oh, indeed,
11:01
Speaker 1: just back to the Jacquard loom really quickly that was
11:03
Speaker 1: developed by Joseph Mulley Jacquard Um. And to me, this
11:09
Speaker 1: is a really great way to kind of understand somewhat
11:12
Speaker 1: how punch cards work. Uh, you know, I think it
11:14
Speaker 1: was clearly a next level use of this technology when
11:18
Speaker 1: it started to be used for more difficult you know,
11:21
Speaker 1: algorithms and mathematical equations solving and things like that. But
11:25
Speaker 1: it's sort of almost like a player piano or a
11:28
Speaker 1: music box, where like, if you have a music box,
11:31
Speaker 1: you create the programming or the instructions for what individual
11:35
Speaker 1: musical times will be plucked to create a melody by
11:38
Speaker 1: punching out sequences of notes like on a scale on
11:41
Speaker 1: a staff that is on a roll of paper, in
11:44
Speaker 1: the same way that a player piano. You feed these
11:46
Speaker 1: roles of punched out paper into it, and that blocks
11:49
Speaker 1: the keys from being played when they shouldn't be played
11:52
Speaker 1: and allows it to play the keys when they are
11:54
Speaker 1: supposed to be played. So to me, that's sort of
11:56
Speaker 1: like a rudimentary understanding of the basis of how punch
11:59
Speaker 1: cards work. But any computer science folks out there, please
12:02
Speaker 1: correct me if that's absolutely off base. But that's kind
12:05
Speaker 1: of how I understand it. But she wanted to take
12:07
Speaker 1: it even further. Uh. She wanted to weave what would
12:11
Speaker 1: are called Bernoulli numbers, the sequences of Bernoulli numbers. Um.
12:15
Speaker 1: And that's exactly what she did. Uh. And that's what
12:17
Speaker 1: that quote is describing, and that would have been considered
12:20
Speaker 1: the first computer program. You're absolutely right, ben Um and
12:24
Speaker 1: s Singer. Uh in his biography of Love Lace wrote,
12:28
Speaker 1: Ada here is seeking to do nothing less than invent
12:31
Speaker 1: the science of computing and separate it from the science
12:34
Speaker 1: of mathematics. What she calls the science of operations is
12:38
Speaker 1: indeed in effect computing at a time where they didn't
12:42
Speaker 1: have a name for it. Uh, didn't even understand the
12:44
Speaker 1: full ramifications of what this would ultimately be, you know,
12:47
Speaker 1: the Pandora's box for good or bad that this would
12:50
Speaker 1: open up. She was very aware of that very high
12:53
Speaker 1: level stuff that wouldn't even come into play for many,
12:57
Speaker 1: many years, much more so I think than Babbage himself. Yeah,
13:01
Speaker 1: a language of the world, a language that describes reality,
13:06
Speaker 1: she she said, so to put a fine point on it.
13:10
Speaker 1: At one point, she writes, this science constitutes the language
13:14
Speaker 1: through which alone we can adequately express the great facts
13:18
Speaker 1: of the natural world. So this is figuring out how
13:22
Speaker 1: to how to translate reality, and that's that's an amazing thing.
13:29
Speaker 1: At that level, we are getting to what Arthur C.
13:34
Speaker 1: Clark famously refers to in his quote about the difference
13:37
Speaker 1: between science and magic. Right, any science sufficiently advanced may
13:42
Speaker 1: as well be magic. And this is really what she's doing.
13:51
Speaker 1: If you look at something called the Ada Initiative, which
13:55
Speaker 1: is a nonprofit organization that arranges conferencing and training programs
14:00
Speaker 1: to elevate women working in STEM, you'll see the executive director,
14:05
Speaker 1: Valerie Aurora, says that Babbage possessed this technical ingenuity, this inventiveness,
14:14
Speaker 1: but in his partnership with Lovelace, she is the one
14:17
Speaker 1: who propelled his invention into the world of computing, because
14:22
Speaker 1: she was the one to see the true potential. There's
14:26
Speaker 1: an excellent article that talks about this Ada Lovelace First
14:30
Speaker 1: Tech Visionary by Betsy Murray's which is in The New
14:34
Speaker 1: York Or from and unlike sad to say, many other
14:41
Speaker 1: male inventors or scientists, Babbage had absolutely no problem hyping
14:48
Speaker 1: and supporting Lovelace and her her work and her ability
14:52
Speaker 1: as a computer scientists. He called her Lady Ferry, He
14:57
Speaker 1: called her the Enchantress of numbers, and Aida leaned into this.
15:01
Speaker 1: She once called herself the high Priestess of Babbage's engine,
15:05
Speaker 1: which is cool. It sounds like it could be really
15:07
Speaker 1: fun to be a fly on the wall in their conversations.
15:10
Speaker 1: I agree, and I think it's neat. You know, we're
15:12
Speaker 1: gonna see this relationship sort of changes a little bit.
15:15
Speaker 1: And it does appear Babbage and may have been difficult
15:17
Speaker 1: in some other respects, but he was pretty progressive given
15:22
Speaker 1: the time and all of the you know, other stuff
15:23
Speaker 1: that we've been talking about, the kind of patriarchal societal
15:27
Speaker 1: model and um, all of that stuff and the misogyny
15:30
Speaker 1: that existed. But um, you know, it's not like he
15:33
Speaker 1: pressed for her. He definitely associated her with these uh
15:38
Speaker 1: improvements in the paper, and he wasn't trying to like
15:41
Speaker 1: brush her aside. But I don't know, Uh, we'll just see,
15:45
Speaker 1: let's see how things progress. Um, So Lovelace does become
15:48
Speaker 1: fascinated with the potential for the analytical engine and these algorithms,
15:53
Speaker 1: which I don't even know if they were calling them
15:55
Speaker 1: that at the time, but it essentially is what we
15:57
Speaker 1: would call algorithms today, these pieces of code that are
16:00
Speaker 1: designed to do like a particular task. Um. Unfortunately, she
16:06
Speaker 1: didn't continue working with Babbage or wasn't more involved. She
16:11
Speaker 1: was sort of relegated to the sidelines a little bit. Um.
16:14
Speaker 1: I think that's maybe where I'm what I'm getting at
16:16
Speaker 1: is that he definitely listened to her. He hyped her up,
16:19
Speaker 1: and he you know, gave her a megaphone and a
16:22
Speaker 1: platform to kind of try out some of the ideas,
16:24
Speaker 1: but it ultimately was his thing. Right. Yeah, this is
16:28
Speaker 1: where we see an unfortunate complication in their collaboration. So
16:33
Speaker 1: in August of eighteen forty three, Lovelace writes a letter
16:39
Speaker 1: to Babbage and she says, hey, why don't you let
16:42
Speaker 1: me help you by putting me in charge of anything
16:47
Speaker 1: related to the analytical project that requires us influencing important people,
16:54
Speaker 1: kind of like, let me go talk to these folks,
16:56
Speaker 1: let me go help get some approval, some funding, get
17:01
Speaker 1: some other assistance. And this was a pretty long letter.
17:05
Speaker 1: Historians still don't know why, but Babbage, in very terse
17:10
Speaker 1: terms rejected her offer. You'll see that the best guests
17:15
Speaker 1: people tend to have is that he approved of her
17:18
Speaker 1: work in publicizing his engine, but with this particular project
17:25
Speaker 1: he felt uncomfortable for some reason about letting her be
17:28
Speaker 1: involved in the project itself. Does that mean maybe he
17:31
Speaker 1: thought she might outshine him. Did his misogyny come into play?
17:37
Speaker 1: I don't know. But ever since that point, due impart
17:41
Speaker 1: to this conflict they had, Oh they stayed friends, by
17:44
Speaker 1: the way. Part of yeah, conflict they had, you'll find
17:48
Speaker 1: some folks say that she was not a programmer at all,
17:52
Speaker 1: but I tend to disagree. Well, yeah, it's interesting. I
17:56
Speaker 1: think maybe if she had been more involved in the
17:59
Speaker 1: project itself instead of just kind of relegated to interpreting
18:03
Speaker 1: and adding some more clarity around that original paper, then
18:07
Speaker 1: I think she would have become more influential in actual programming.
18:12
Speaker 1: She certainly had the chops and the imagination, which is
18:16
Speaker 1: really what that poetical science concept is all about, is
18:19
Speaker 1: kind of combining those two things. Um, it was Babbage
18:22
Speaker 1: himself that created the first what essentially could be called
18:25
Speaker 1: the first operating system or operating instructions uh for the system. Um,
18:31
Speaker 1: she may well have done a better job. You know,
18:34
Speaker 1: it seems like it. But I understand what you're saying,
18:37
Speaker 1: been and I kind of agree that maybe he was
18:39
Speaker 1: worried that, um, she might have stolen his thunder a
18:42
Speaker 1: little bit. Um. The thing is not to beat the
18:45
Speaker 1: dead horse here. She is the one who sort of
18:47
Speaker 1: understood the potential for this stuff more than Babbage. Where
18:51
Speaker 1: she understood that it could do things other than just
18:54
Speaker 1: simple calculations. She understood the more modern uh, you know
18:59
Speaker 1: concept of computing um, in that it can be multi purpose,
19:02
Speaker 1: it can create these you know, have like systems running
19:05
Speaker 1: in tandem that can do multiple things. The idea of
19:07
Speaker 1: you know, apps or like individual piece of software that
19:10
Speaker 1: can run at the same time. Certainly more of a
19:12
Speaker 1: rudimentary version of that concept, but definitely approaching that in
19:16
Speaker 1: a really important way. UM. Babbage believed that these machines
19:21
Speaker 1: would be exclusively used for computing numbers. Uh. But she
19:26
Speaker 1: had more of a vision. She believed there could be
19:28
Speaker 1: music involved or like, you know, she she envisioned word processing.
19:33
Speaker 1: She envisioned the idea of them using being being used
19:35
Speaker 1: to make sound, whether that's along the lines of the
19:38
Speaker 1: music box kind of version that I was describing before,
19:41
Speaker 1: which is very similar to what MIDI ultimately is. MIDDI
19:44
Speaker 1: is a language, a computer language that that basically is
19:47
Speaker 1: a set of instructions the different electronic devices can understand
19:51
Speaker 1: to tell it what to do to play different notes.
19:53
Speaker 1: She almost foresaw something like that, um processing photographs and
19:58
Speaker 1: things like that, Like all of these a modern concepts,
20:00
Speaker 1: she already kind of had her head around them. Yeah,
20:04
Speaker 1: it's enormously prescient. This level of accuracy and a prediction
20:11
Speaker 1: is somewhat rare, and it should be acknowledged as such.
20:16
Speaker 1: I also, I'm not sure the right way to say this.
20:22
Speaker 1: I vibe with these kind of predictions, and and it's
20:26
Speaker 1: interesting to me that there are still people who are
20:30
Speaker 1: so Folks who say that this person's role in history
20:32
Speaker 1: is overblown are met with responses from other historians who
20:38
Speaker 1: have studied Aida Lovelace their entire lives, and those folks say,
20:42
Speaker 1: what's happening now is there's still people in the modern
20:46
Speaker 1: day who are trying to discredit her achievements. And they say, look,
20:50
Speaker 1: this doesn't just happen to prominent historical figures like Aida Lovelace.
20:55
Speaker 1: This happens to women working in tech today, many of
20:58
Speaker 1: whom are in the audio now and thank you, by
21:01
Speaker 1: the way for tuning in. As always ridiculous historians. Uh,
21:05
Speaker 1: people are starting to guess they're they're saying, like, well,
21:08
Speaker 1: what what happened after this? Because as we found, you know,
21:12
Speaker 1: history textbooks sometimes teach us that people exist for one
21:16
Speaker 1: great moment, that it's that one great speech they did,
21:19
Speaker 1: that one eureka uh second that defines their life. But
21:24
Speaker 1: that's not true. People are people, just like everyone else.
21:27
Speaker 1: They have their ups and downs. And some folks say
21:30
Speaker 1: that because Aida hit this wall in the world of tech,
21:36
Speaker 1: she may have it may have led her into the
21:41
Speaker 1: gambling halls. And we do know that in the eighteen
21:44
Speaker 1: forties she did pick up a gambling habit, and some
21:49
Speaker 1: people speculate that this gambling habit forced her to secretly
21:53
Speaker 1: pawn the family's precious stones. I'm gonna have family jewels.
21:58
Speaker 1: But that feels like it's more euphanism. I think it is.
22:01
Speaker 1: But but it's an uphanism for a reason. I think
22:03
Speaker 1: it comes from situations like that is the prize possession
22:06
Speaker 1: of like you know, your legacy kind of and yeah,
22:08
Speaker 1: when you're when you're that low that you have to
22:11
Speaker 1: resort to that, Um, it's definitely a sad, a sad
22:14
Speaker 1: place to be. Uh. And she, you know, reportedly lost
22:18
Speaker 1: thousands of pounds betting on horses UM at the EPSOM Derby. UM.
22:24
Speaker 1: She had relationships, like often people do that get deep
22:28
Speaker 1: into the gambling world with con men and loan sharky
22:31
Speaker 1: types you know of the time, who were essentially using her,
22:36
Speaker 1: uh for her smarts, for some sort of mathematical way
22:41
Speaker 1: of predicting horse races. Uh. And I think we all
22:45
Speaker 1: know that that's not a thing. Maybe there's you know,
22:48
Speaker 1: ways of calculating odds and stuff like that, and like
22:51
Speaker 1: you know, algorithms that can kind of help guide you
22:54
Speaker 1: in the right direction. But if someone had it's like
22:56
Speaker 1: the I always think of the sports Almanac from back
22:59
Speaker 1: to the few tre two. You know, somebody had that
23:01
Speaker 1: ability to predict the outcome of sports games, there would
23:06
Speaker 1: be no rhymer reason to to betting it, wouldn't there.
23:09
Speaker 1: There'll be no need for it anymore unless that secret
23:11
Speaker 1: was you know, just kept just by Biff from the past,
23:14
Speaker 1: you know, who is now a Donald Trump asked figure
23:16
Speaker 1: living in his high rise keeping the sports on the
23:18
Speaker 1: neck in a in a under lock and key, And
23:21
Speaker 1: unfortunately that's not what happened with a. We know their
23:25
Speaker 1: friendship continued. We know that she met other notable figures
23:30
Speaker 1: like Charles Dickens. Yes, that Charles Dickens. He was friends
23:34
Speaker 1: with Babbage. He met Lovelace through her. There's before we
23:38
Speaker 1: move on from gambling, there's this really cool conspiratorial passing
23:41
Speaker 1: the book story between her and Babbage, but no one's
23:45
Speaker 1: actually found the book. It'd be great to see what
23:47
Speaker 1: that program was, though, wouldn't if they actually were able
23:50
Speaker 1: to do it. Uh, the book being the book being
23:53
Speaker 1: some secret code or some secret algorithm that could predict
23:57
Speaker 1: these outcomes. Yeah. So the idea is that, and you
24:03
Speaker 1: can you can read some of this in a book
24:06
Speaker 1: called Lady Byron and Her Daughters. Uh. The idea is
24:09
Speaker 1: that about once a week, during the height of her gambling,
24:13
Speaker 1: Lovelace and Babbage would exchange a book that was believed
24:17
Speaker 1: to contain a program that attempted to predict those results.
24:22
Speaker 1: But at the same time she's struggling with this gambling,
24:26
Speaker 1: she's also struggling with her health, which had been a
24:28
Speaker 1: problem at different points in her adulthood. Uh, it seemed
24:32
Speaker 1: to take a turn for the worst. In the eighteen
24:34
Speaker 1: forties she suffered from uterine cancer, and in August of
24:41
Speaker 1: eighteen fifty two, Charles Dickens, who by this point is
24:44
Speaker 1: like super famous, he visits. He visits her while she
24:48
Speaker 1: is ailing, and then she asked him to read some
24:52
Speaker 1: of his work to her, and so he reads a
24:56
Speaker 1: scene from a novel called Dombi and Son. Dombi and
25:00
Speaker 1: Son was published in eighteen and the scene he reads
25:05
Speaker 1: is the part where spoiler alert, I guess is the
25:08
Speaker 1: part where the six year old character Paul Dombie dies.
25:14
Speaker 1: It's kind of somber stuff. Three months after that, Ada
25:18
Speaker 1: Lovelace herself will will pass away on November two, rewind
25:29
Speaker 1: ever so slightly well quite quite a ways to her birth.
25:32
Speaker 1: In the situation with her father, Lord Byron, Um, I
25:35
Speaker 1: think we made this pretty clear, but just want to
25:37
Speaker 1: emphasize that they never had a relationship at all. He
25:40
Speaker 1: was kind of this like you know, specter in her life,
25:43
Speaker 1: who loomed large in his own right. Um. She was
25:46
Speaker 1: fascinated with him from afar uh and with his poetry
25:50
Speaker 1: but for all intents and purposes, her mother's mission to
25:54
Speaker 1: keep you know, their daughter from becoming like um, you know,
25:57
Speaker 1: her lecherous uh father worked. She very much led a
26:02
Speaker 1: life much more in the image of her her mom.
26:05
Speaker 1: But it's interesting that she still had that fascination and
26:07
Speaker 1: kind of kept up with him. But it's like you said,
26:09
Speaker 1: been on his deathbed, Lord Byron expressed some um regrets
26:14
Speaker 1: you know, over not having had a relationship with his daughter,
26:17
Speaker 1: who he seemed to also be aware of her reputation
26:21
Speaker 1: and legacy and the seemed to respect her. But after
26:25
Speaker 1: her death, she requested to be buried in the Byron
26:29
Speaker 1: family plot or vault rather, which was inside the church
26:32
Speaker 1: of St. Mary Magdalen in a very small English town
26:36
Speaker 1: called Hucknall, and her coffin was placed right beside her father's,
26:41
Speaker 1: Lord Byron's, and she too passed away at a very
26:45
Speaker 1: early age. She was only thirty six. Um, I believe
26:49
Speaker 1: it was the same exact age that Lord Byron died.
26:52
Speaker 1: Same exact age. Yeah, she was, uh, she was close
26:56
Speaker 1: to turning thirty seven, but they did. They were the
27:00
Speaker 1: same age when they passed away, and her mother built
27:04
Speaker 1: a memorial for her that included a sonnet that Ada
27:08
Speaker 1: Lovelace had written herself, and that I believe was a
27:12
Speaker 1: beautiful thing for her to do, given that she had,
27:16
Speaker 1: you know, spent so much of her daughter's childhood trying
27:19
Speaker 1: to convince the kid not to write poetry. Uh so
27:24
Speaker 1: she passes away. Why how did the world deal with
27:28
Speaker 1: it when this occurred? Well, it may not surprise many
27:31
Speaker 1: of us in the audience today to note that no
27:36
Speaker 1: one really acknowledged her contributions for almost a hundred years.
27:41
Speaker 1: They like, nobody really paid attention to her awesome insightful
27:45
Speaker 1: notes on the analytical Engine when they were first published.
27:49
Speaker 1: It wasn't ntil author named B. V. Bowden publishes a
27:53
Speaker 1: book called Faster Than Thought, a symposium on digital computing machines,
27:58
Speaker 1: and that's when people start paying attention to Love leases again, tremendously,
28:05
Speaker 1: tremendously insightful work. Picture her like a mathematical Nostradams. If
28:11
Speaker 1: no Stradomas ever actually made any successful predictions, which he didn't,
28:17
Speaker 1: not so much, but but Lovelace absolutely did. And even
28:21
Speaker 1: in the fifties, you know, like like I said, when
28:23
Speaker 1: I was talking to Alex and Max's dad, Um the
28:28
Speaker 1: machines that existed still were very much along the lines
28:31
Speaker 1: of what Babbage and Lovelace had kind of worked on together,
28:34
Speaker 1: and still not even close to approaching what potential that
28:41
Speaker 1: she saw. That wouldn't really happen until you started getting
28:44
Speaker 1: into the personal computer era, when like individuals can start
28:47
Speaker 1: using them for more creative endeavors, you know, at least
28:50
Speaker 1: that part of her predictions, you know, the idea of
28:52
Speaker 1: using them for music, and using them for multitasking and things,
28:56
Speaker 1: and to be more of like a staple of like
28:58
Speaker 1: everyday life instead of relegate it into these like massive
29:01
Speaker 1: server rooms, you know, and being so prohibitably expensive that
29:04
Speaker 1: only UM organizations like the U. S. Department of Defense
29:09
Speaker 1: could afford to house them, which is exactly what they
29:12
Speaker 1: did in the nineteen seventies. I spent billions of dollars
29:16
Speaker 1: UM embedding these computer systems with code uh that they
29:21
Speaker 1: a coding language that they dubbed Ada, and it changed
29:24
Speaker 1: the trajectory of computer science UM in a very meaningful way. Yeah.
29:30
Speaker 1: It was actually one of the one of the most
29:33
Speaker 1: expensive coding projects ever. I think it was the most
29:37
Speaker 1: expensive coding project up to that time. In the nineteen seventies.
29:41
Speaker 1: The folks at the Department of Defense in the US
29:43
Speaker 1: look around and they say, we are spending billions in
29:47
Speaker 1: nineteen seventies dollars, so even more money today. We are
29:50
Speaker 1: spending billions on making computing systems. And these computing systems
29:56
Speaker 1: can't talk with each other. They each have their own language.
30:00
Speaker 1: We're building a weird tower of babble. So instead they say,
30:04
Speaker 1: let's let's consolidate all our military computing. Let's save a
30:08
Speaker 1: little scratch, let's make a language all of these machines
30:12
Speaker 1: can speak together. And when they arrive at this idea,
30:17
Speaker 1: which they do follow through with, that's when that language
30:20
Speaker 1: comes in. There's a U. S. Navy commander named Jack
30:23
Speaker 1: Cooper who's when they're pitching names for it, he says, well,
30:26
Speaker 1: how about we name it Ada in honor of Aida
30:29
Speaker 1: Lovelace in the ninety nine. Everybody looked around and said, yeah,
30:34
Speaker 1: that's an awesome idea, So good for them. Also, Aida
30:39
Speaker 1: is still used across the world today for air traffic control,
30:44
Speaker 1: railroad transit, rockets, even some satellites, military weapons. We don't
30:49
Speaker 1: know how she would feel about, you know, having a
30:54
Speaker 1: language named after her used in warfare. But it's still around,
31:00
Speaker 1: and it's it's definitely less popular now. It's fallen out
31:03
Speaker 1: of favor because technology is always so progressing so quickly.
31:07
Speaker 1: But we also like nuclear plants and military operations sometimes
31:12
Speaker 1: do tend to use outdated uh coading or or computers
31:15
Speaker 1: because they need to be proprietary, so they're harder to
31:19
Speaker 1: hack or they're harder to like break into correct correct
31:22
Speaker 1: for security. And then also another point would be for predictability.
31:27
Speaker 1: If there are bugs in the program, they've been identified,
31:30
Speaker 1: you know, in the intervening decades. So this is a
31:33
Speaker 1: testament to Aida lovelas his life and work, and it's
31:38
Speaker 1: a testament that not a lot of people can say
31:42
Speaker 1: that they have achieved, you know what I mean. Everybody
31:44
Speaker 1: gets a statue, right if you're a leader of old
31:47
Speaker 1: or your prominent figure. But to get a new kind
31:51
Speaker 1: of language, a computer language named after you, that's pretty impressive.
31:55
Speaker 1: That's up there with having your face on the money.
31:57
Speaker 1: I would say even more important, I think so too
32:00
Speaker 1: quick footnote, there is an Ada Lovelace Day. In two
32:04
Speaker 1: thousand nine, a British social media grew named Sue Chairman
32:09
Speaker 1: Anderson in order to encourage young women to go into
32:12
Speaker 1: stem fields and all of that. They decided to create
32:17
Speaker 1: an Ada Lovelace Day. UM that was on October eleven
32:21
Speaker 1: of each year. UM. And it's weirdly not Ada Lovelace's birthday,
32:26
Speaker 1: nor is it the day that she died. Um, it's
32:29
Speaker 1: just the second Tuesday in October because it was convenient. Um.
32:33
Speaker 1: And one thing I just wanted to say, because I
32:34
Speaker 1: thought it was really funny. I think I mentioned the
32:37
Speaker 1: first episode UM a YouTube talk I listened to or
32:41
Speaker 1: we we listened to about a book that was written
32:45
Speaker 1: to commemorate the two anniversary of her uh birth and
32:50
Speaker 1: UM it was had to do with Oxford Press. And
32:52
Speaker 1: I'm sorry I'm spacing on the name of it right now,
32:55
Speaker 1: but in the presentation, one of the authors mentioned that
33:00
Speaker 1: when they had access to all these letters she wrote,
33:01
Speaker 1: she wasn't very good at keeping track of dates like
33:04
Speaker 1: she UM oftentimes would would say that a letter was
33:08
Speaker 1: be dated for like Sunday, November the second, and the
33:11
Speaker 1: next one would be dated for Monday, November the second.
33:13
Speaker 1: The punchline of the of the bit that the author
33:16
Speaker 1: said was and it turns out that that date was
33:18
Speaker 1: actually a Tuesday. So UM, it's I think fitting that
33:22
Speaker 1: this date is a little bit arbitrary. I love a
33:25
Speaker 1: Loveli day, right right right there we go, that's that's
33:29
Speaker 1: poetic as well. One thing we do want to end
33:32
Speaker 1: done that we teased earlier in part one is that
33:37
Speaker 1: when we say Loveliest was prescient and how to how
33:41
Speaker 1: to sharp mind for future trends, we need to talk
33:44
Speaker 1: a little bit about the concept of machine consciousness sometimes
33:48
Speaker 1: called artificial intelligence or AI. Where do you think she
33:52
Speaker 1: fell on on the side of this argument ridiculous historians? Well, uh,
34:00
Speaker 1: she was. She was against it. She said, the analytical
34:04
Speaker 1: engine has no pretensions whatsoever to originate anything. It can
34:08
Speaker 1: do whatever we know how to order it to perform.
34:11
Speaker 1: It can follow analysis, but has no power of anticipating
34:14
Speaker 1: any analytical relations or truths. And so you have to wonder.
34:20
Speaker 1: You have to wonder how long that prediction and soft
34:24
Speaker 1: interpreted as a prediction, how long it will hold. Because
34:27
Speaker 1: I don't know. The whole time we're talking about this,
34:31
Speaker 1: I I kept wondering what she would think now, what
34:35
Speaker 1: she would think of the latest innovations. Everybody has a
34:38
Speaker 1: surveillance device or you know, the majority of people in
34:42
Speaker 1: the developed world have a surveillance device. Who just call smartphone,
34:46
Speaker 1: so it'll seem a little more comfortable. Uh. There are
34:49
Speaker 1: entire multibillion dollar industries based on predicting people's behavior right
34:55
Speaker 1: based on their past activities, their location, the folks they
34:59
Speaker 1: roll with. So it's quite possible. I don't know, what
35:03
Speaker 1: do you what do you think she would think about
35:05
Speaker 1: the modern world of computing. I think she'd with that
35:10
Speaker 1: big old brain of hers, probably be able to predict
35:13
Speaker 1: where we'd be heading, you know another you know, fifty
35:17
Speaker 1: hundred years from now. Um. It just seemed like she
35:20
Speaker 1: really was possessed with a certain prescient ability to kind
35:25
Speaker 1: of just see through, um, the veil, kind of into
35:28
Speaker 1: into what was next. So I think it would be
35:30
Speaker 1: very interesting to have a conversation with her, like Bill
35:32
Speaker 1: and Ted style. UM. I don't want to point out
35:35
Speaker 1: one thing too. I want to make sure I didn't
35:37
Speaker 1: come off sounding as though the difference engine or the
35:40
Speaker 1: analytical engine were successfully built and existed. In the four
35:44
Speaker 1: It was all conceptual. It was all these papers and
35:47
Speaker 1: these analyzes of the concept of these machines. But he
35:51
Speaker 1: never actually got babbaged. Also partly because he was a difficult,
35:55
Speaker 1: dude never got the project off the ground UM fully UM.
35:59
Speaker 1: But into thousand two, the London Science Museum UM, with
36:04
Speaker 1: the under the supervision of Dorn Suede or Swatty UM,
36:09
Speaker 1: they actually built a fully working, full size difference engine UM.
36:15
Speaker 1: And it took seventeen years UM and it is absolutely
36:20
Speaker 1: massive and it represents the completion of this whole legacy
36:24
Speaker 1: that we're talking about. Obviously, the concepts went on to
36:28
Speaker 1: feed computing moving forward, but the original you know, invention
36:32
Speaker 1: never actually was was created until two thousand two. And folks,
36:37
Speaker 1: I think you can I think you can agree with me.
36:40
Speaker 1: Noll well, I think you guys will also agree that
36:43
Speaker 1: maybe the difference engine would have been built in Charles
36:46
Speaker 1: Babbage's lifetime if he had just let someone else talk
36:50
Speaker 1: to the people who could have paid for it. So
36:52
Speaker 1: I think that was a misstep on his You can't
36:54
Speaker 1: put that on Ada man. That's all you saw, you, Charlie.
36:58
Speaker 1: Uh yes, and uh you know this story is equally inspiring,
37:05
Speaker 1: it's equally heartbreaking because we've all heard the old adage
37:09
Speaker 1: you never get the flowers while you can still smell them. Uh.
37:14
Speaker 1: And we we be humanity, oh Ada Lovelace tremendous debt.
37:22
Speaker 1: As we said in the beginning of this series, if
37:25
Speaker 1: you have a smartphone, if you have a computer, heck,
37:28
Speaker 1: if you're listening to this podcast, then there's a very
37:31
Speaker 1: strong argument that you personally oh a little bit of
37:35
Speaker 1: gratitude towards the one and only Ada Lovelace. Indeed, Um,
37:41
Speaker 1: and I certainly learned a lot. I knew a little
37:44
Speaker 1: bit about Aida and her legacy, and a little bit
37:47
Speaker 1: about Babbage, but not nearly as much as we were
37:50
Speaker 1: able to dig into on this two part episode. I
37:53
Speaker 1: hope you all have learned something too, and we are
37:56
Speaker 1: going to call it a day. This is one for
37:59
Speaker 1: the history books. As always, thanks to super producer Max Williams.
38:03
Speaker 1: Special thanks to our returning guest producer Lowell Brilliante Noel.
38:08
Speaker 1: Can you believe he's stuck with us for a second one?
38:11
Speaker 1: I can't, Um, but I am for ever his debt
38:13
Speaker 1: for his patients and uh and and producing acumen. And
38:17
Speaker 1: also don't forget to check out Lowell's amazing podcast Prodigy,
38:21
Speaker 1: available now on the IHRT Radio app, Apple Podcasts, wherever
38:24
Speaker 1: you get podcasts, wherever you get. That's true, That's true.
38:27
Speaker 1: And thanks of course also to Alex Williams who uh
38:32
Speaker 1: rumor has it maybe returning to the show sooner than
38:35
Speaker 1: later act surprised Big thanks to Christopher hassegda Is Big
38:38
Speaker 1: Big thanks to Eve's Jeff Coat and of course Noel
38:44
Speaker 1: Big thanks to you, and I think we can both
38:47
Speaker 1: say big thanks to Gabe Lousier. Keep wanting to say
38:51
Speaker 1: one don't cut this part out. I keep wanting to
38:53
Speaker 1: say the one and only. It just feels so good
38:56
Speaker 1: to say that when you talk true, it feels good
38:58
Speaker 1: and it's true you can. These are all like irreplaceable originals,
39:03
Speaker 1: um all the folks who work with so thanks to
39:05
Speaker 1: all of our one and only and to you, my friend,
39:09
Speaker 1: back at you. We'll see you next time, folks. For
39:15
Speaker 1: more podcasts from my Heart Radio, visit the I Heart
39:18
Speaker 1: Radio app, Apple podcast, or wherever you listen to your
39:21
Speaker 1: favorite shows.