back to indexGuido van Rossum: Python | Lex Fridman Podcast #6
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The following is a conversation with Guido van Rossum, creator of Python, one of the most popular
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programming languages in the world, used in almost any application that involves computers
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from web back end development to psychology, neuroscience, computer vision, robotics, deep
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learning, natural language processing, and almost any subfield of AI. This conversation is part of
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MIT course on artificial general intelligence and the artificial intelligence podcast.
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If you enjoy it, subscribe on YouTube, iTunes, or your podcast provider of choice, or simply connect
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with me on Twitter at Lex Friedman, spelled F R I D. And now, here's my conversation with Guido van
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Rossum. You were born in the Netherlands in 1956. Your parents and the world around you was deeply
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deeply impacted by World War Two, as was my family from the Soviet Union. So with that context,
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what is your view of human nature? Are some humans inherently good,
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and some inherently evil? Or do we all have both good and evil within us?
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Guido van Rossum Ouch, I did not expect such a deep one. I, I guess we all have good and evil
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potential in us. And a lot of it depends on circumstances and context.
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Peter Bell out of that world, at least on the Soviet Union side in Europe, sort of out of
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suffering, out of challenge, out of that kind of set of traumatic events, often emerges beautiful
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art, music, literature. In an interview I read or heard, you said you enjoyed Dutch literature
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when you were a child. Can you tell me about the books that had an influence on you in your
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childhood? Guido van Rossum
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Well, with as a teenager, my favorite writer was my favorite Dutch author was a guy named Willem
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Frederik Hermans, who's writing, certainly his early novels were all about sort of
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ambiguous things that happened during World War Two. I think he was a young adult during that time.
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And he wrote about it a lot, and very interesting, very good books, I thought, I think.
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Peter Bell In a nonfiction way?
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Guido van Rossum No, it was all fiction, but it was
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very much set in the ambiguous world of resistance against the Germans,
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where often you couldn't tell whether someone was truly in the resistance or really a spy for the
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Germans. And some of the characters in his novels sort of crossed that line, and you never really
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find out what exactly happened.
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Peter Bell And in his novels, there's always a
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good guy and a bad guy, the nature of good and evil. Is it clear there's a hero?
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Guido van Rossum No, his heroes are often more,
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his main characters are often anti heroes. And so they're not very heroic. They're often,
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they fail at some level to accomplish their lofty goals.
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Peter Bell And looking at the trajectory
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through the rest of your life, has literature, Dutch or English or translation had an impact
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outside the technical world that you existed in?
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Guido van Rossum I still read novels.
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I don't think that it impacts me that much directly.
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Peter Bell It doesn't impact your work.
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Guido van Rossum It's a separate world.
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My work is highly technical and sort of the world of art and literature doesn't really
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directly have any bearing on it.
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Peter Bell You don't think there's a creative element
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to the design? You know, some would say design of a language is art.
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Guido van Rossum I'm not disagreeing with that.
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I'm just saying that sort of I don't feel direct influences from more traditional art
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on my own creativity.
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Peter Bell Right. Of course, you don't feel doesn't mean
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it's not somehow deeply there in your subconscious.
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Guido van Rossum Who knows?
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Peter Bell Who knows? So let's go back to your early
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teens. Your hobbies were building electronic circuits, building mechanical models.
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What if you can just put yourself back in the mind of that young Guido 12, 13, 14, was
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that grounded in a desire to create a system? So to create something? Or was it more just
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tinkering? Just the joy of puzzle solving?
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Guido van Rossum I think it was more the latter, actually.
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I maybe towards the end of my high school period, I felt confident enough that that
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I designed my own circuits that were sort of interesting somewhat. But a lot of that
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time, I literally just took a model kit and follow the instructions, putting the things
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together. I mean, I think the first few years that I built electronics kits, I really did
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not have enough understanding of sort of electronics to really understand what I was doing. I mean,
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I could debug it, and I could sort of follow the instructions very carefully, which has
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always stayed with me. But I had a very naive model of, like, how do I build a circuit?
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Of, like, how a transistor works? And I don't think that in those days, I had any understanding
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of coils and capacitors, which actually sort of was a major problem when I started to build
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more complex digital circuits, because I was unaware of the sort of the analog part of
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the – how they actually work. And I would have things that – the schematic looked
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– everything looked fine, and it didn't work. And what I didn't realize was that
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there was some megahertz level oscillation that was throwing the circuit off, because
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I had a sort of – two wires were too close, or the switches were kind of poorly built.
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But through that time, I think it's really interesting and instructive to think about,
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because echoes of it are in this time now. So in the 1970s, the personal computer was
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being born. So did you sense, in tinkering with these circuits, did you sense the encroaching
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revolution in personal computing? So if at that point, we would sit you down and ask
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you to predict the 80s and the 90s, do you think you would be able to do so successfully
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to unroll the process that's happening? No, I had no clue. I remember, I think, in
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the summer after my senior year – or maybe it was the summer after my junior year – well,
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at some point, I think, when I was 18, I went on a trip to the Math Olympiad in Eastern
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Europe, and there was like – I was part of the Dutch team, and there were other nerdy
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kids that sort of had different experiences, and one of them told me about this amazing
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thing called a computer. And I had never heard that word. My own explorations in electronics
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were sort of about very simple digital circuits, and I had sort of – I had the idea that
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I somewhat understood how a digital calculator worked. And so there is maybe some echoes
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of computers there, but I never made that connection. I didn't know that when my parents
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were paying for magazine subscriptions using punched cards, that there was something called
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a computer that was involved that read those cards and transferred the money between accounts.
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I was also not really interested in those things. It was only when I went to university
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to study math that I found out that they had a computer, and students were allowed to use
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And there were some – you're supposed to talk to that computer by programming it.
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What did that feel like, finding –
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Yeah, that was the only thing you could do with it. The computer wasn't really connected
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to the real world. The only thing you could do was sort of – you typed your program
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on a bunch of punched cards. You gave the punched cards to the operator, and an hour
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later the operator gave you back your printout. And so all you could do was write a program
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that did something very abstract. And I don't even remember what my first forays into programming
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were, but they were sort of doing simple math exercises and just to learn how a programming
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Did you sense, okay, first year of college, you see this computer, you're able to have
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a program and it generates some output. Did you start seeing the possibility of this,
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or was it a continuation of the tinkering with circuits? Did you start to imagine that
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one, the personal computer, but did you see it as something that is a tool, like a word
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processing tool, maybe for gaming or something? Or did you start to imagine that it could
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be going to the world of robotics, like the Frankenstein picture that you could create
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an artificial being? There's like another entity in front of you. You did not see the
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I don't think I really saw it that way. I was really more interested in the tinkering.
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It's maybe not a sort of a complete coincidence that I ended up sort of creating a programming
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language which is a tool for other programmers. I've always been very focused on the sort
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of activity of programming itself and not so much what happens with the program you
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I do remember, and I don't remember, maybe in my second or third year, probably my second
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actually, someone pointed out to me that there was this thing called Conway's Game of Life.
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You're probably familiar with it. I think –
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In the 70s, I think is when they came up with it.
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So there was a Scientific American column by someone who did a monthly column about
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mathematical diversions. I'm also blanking out on the guy's name. It was very famous
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at the time and I think up to the 90s or so. And one of his columns was about Conway's
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Game of Life and he had some illustrations and he wrote down all the rules and sort of
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there was the suggestion that this was philosophically interesting, that that was why Conway had
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called it that. And all I had was like the two pages photocopy of that article. I don't
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even remember where I got it. But it spoke to me and I remember implementing a version
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of that game for the batch computer we were using where I had a whole Pascal program that
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sort of read an initial situation from input and read some numbers that said do so many
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generations and print every so many generations and then out would come pages and pages of
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I remember much later I've done a similar thing using Python but that original version
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I wrote at the time I found interesting because I combined it with some trick I had learned
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during my electronics hobbyist times. I essentially first on paper I designed a simple circuit
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built out of logic gates that took nine bits of input which is sort of the cell and its
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neighbors and produced a new value for that cell and it's like a combination of a half
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adder and some other clipping. It's actually a full adder. And so I had worked that out
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and then I translated that into a series of Boolean operations on Pascal integers where
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you could use the integers as bitwise values. And so I could basically generate 60 bits
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of a generation in like eight instructions or so.
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So I was proud of that.
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It's funny that you mentioned, so for people who don't know Conway's Game of Life, it's
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a cellular automata where there's single compute units that kind of look at their neighbors
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and figure out what they look like in the next generation based on the state of their
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neighbors and this is deeply distributed system in concept at least. And then there's simple
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rules that all of them follow and somehow out of this simple rule when you step back
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and look at what occurs, it's beautiful. There's an emergent complexity. Even though the underlying
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rules are simple, there's an emergent complexity. Now the funny thing is you've implemented
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this and the thing you're commenting on is you're proud of a hack you did to make it
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run efficiently. When you're not commenting on, it's a beautiful implementation, you're
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not commenting on the fact that there's an emergent complexity that you've coded a simple
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program and when you step back and you print out the following generation after generation,
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that's stuff that you may have not predicted would happen is happening.
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And is that magic? I mean, that's the magic that all of us feel when we program. When
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you create a program and then you run it and whether it's Hello World or it shows something
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on screen, if there's a graphical component, are you seeing the magic in the mechanism
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I think I went back and forth. As a student, we had an incredibly small budget of computer
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time that we could use. It was actually measured. I once got in trouble with one of my professors
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because I had overspent the department's budget. It's a different story.
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I actually wanted the efficient implementation because I also wanted to explore what would
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happen with a larger number of generations and a larger size of the board. Once the implementation
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was flawless, I would feed it different patterns and then I think maybe there was a follow
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up article where there were patterns that were like gliders, patterns that repeated
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themselves after a number of generations but translated one or two positions to the right
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or up or something like that. I remember things like glider guns. Well, you can Google Conway's
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Game of Life. People still go aww and ooh over it.
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For a reason because it's not really well understood why. I mean, this is what Stephen
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Wolfram is obsessed about. We don't have the mathematical tools to describe the kind of
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complexity that emerges in these kinds of systems. The only way you can do is to run
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I'm not convinced that it's sort of a problem that lends itself to classic mathematical
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One theory of how you create an artificial intelligence or artificial being is you kind
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of have to, same with the Game of Life, you kind of have to create a universe and let
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it run. That creating it from scratch in a design way, coding up a Python program that
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creates a fully intelligent system may be quite challenging. You might need to create
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a universe just like the Game of Life.
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You might have to experiment with a lot of different universes before there is a set
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of rules that doesn't essentially always just end up repeating itself in a trivial
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Yeah, and Stephen Wolfram works with these simple rules, says that it's kind of surprising
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how quickly you find rules that create interesting things. You shouldn't be able to, but somehow
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you do. And so maybe our universe is laden with rules that will create interesting things
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that might not look like humans, but emergent phenomena that's interesting may not be as
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difficult to create as we think.
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But let me sort of ask, at that time, some of the world, at least in popular press, was
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kind of captivated, perhaps at least in America, by the idea of artificial intelligence, that
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these computers would be able to think pretty soon. And did that touch you at all? In science
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fiction or in reality in any way?
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I didn't really start reading science fiction until much, much later. I think as a teenager
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I read maybe one bundle of science fiction stories.
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Was it in the background somewhere, like in your thoughts?
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That sort of the using computers to build something intelligent always felt to me, because
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I felt I had so much understanding of what actually goes on inside a computer. I knew
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how many bits of memory it had and how difficult it was to program. And sort of, I didn't believe
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at all that you could just build something intelligent out of that, that would really
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sort of satisfy my definition of intelligence. I think the most influential thing that I
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read in my early twenties was Gödel Escherbach. That was about consciousness, and that was
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a big eye opener in some sense.
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In what sense? So, on your own brain, did you at the time or do you now see your own
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brain as a computer? Or is there a total separation of the way? So yeah, you're very pragmatically
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practically know the limits of memory, the limits of this sequential computing or weakly
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paralyzed computing, and you just know what we have now, and it's hard to see how it creates.
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But it's also easy to see, it was in the 40s, 50s, 60s, and now at least similarities between
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the brain and our computers.
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Oh yeah, I mean, I totally believe that brains are computers in some sense. I mean, the rules
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they use to play by are pretty different from the rules we can sort of implement in our
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current hardware, but I don't believe in, like, a separate thing that infuses us with
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intelligence or consciousness or any of that. There's no soul, I've been an atheist
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probably from when I was 10 years old, just by thinking a bit about math and the universe,
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and well, my parents were atheists. Now, I know that you could be an atheist and still
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believe that there is something sort of about intelligence or consciousness that cannot
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possibly emerge from a fixed set of rules. I am not in that camp. I totally see that,
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sort of, given how many millions of years evolution took its time, DNA is a particular
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machine that sort of encodes information and an unlimited amount of information in chemical
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form and has figured out a way to replicate itself.
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I thought that that was, maybe it's 300 million years ago, but I thought it was closer
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to half a billion years ago, that that's sort of originated and it hasn't really changed,
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that the sort of the structure of DNA hasn't changed ever since. That is like our binary
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code that we have in hardware. I mean...
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The basic programming language hasn't changed, but maybe the programming itself...
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Obviously, it did sort of, it happened to be a set of rules that was good enough to
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sort of develop endless variability and sort of the idea of self replicating molecules
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competing with each other for resources and one type eventually sort of always taking
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over. That happened before there were any fossils, so we don't know how that exactly
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happened, but I believe it's clear that that did happen.
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Can you comment on consciousness and how you see it? Because I think we'll talk about
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programming quite a bit. We'll talk about, you know, intelligence connecting to programming
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fundamentally, but consciousness is this whole other thing. Do you think about it often as
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a developer of a programming language and as a human?
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Those are pretty sort of separate topics. Sort of my line of work working with programming
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does not involve anything that goes in the direction of developing intelligence or consciousness,
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but sort of privately as an avid reader of popular science writing, I have some thoughts
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which is mostly that I don't actually believe that consciousness is an all or nothing thing.
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I have a feeling that, and I forget what I read that influenced this, but I feel that
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if you look at a cat or a dog or a mouse, they have some form of intelligence. If you
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look at a fish, it has some form of intelligence, and that evolution just took a long time,
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but I feel that the sort of evolution of more and more intelligence that led to sort of
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the human form of intelligence followed the evolution of the senses, especially the visual
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sense. I mean, there is an enormous amount of processing that's needed to interpret
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a scene, and humans are still better at that than computers are.
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And I have a feeling that there is a sort of, the reason that like mammals in particular
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developed the levels of consciousness that they have and that eventually sort of going
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from intelligence to self awareness and consciousness has to do with sort of being a robot that
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has very highly developed senses.
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Has a lot of rich sensory information coming in, so that's a really interesting thought
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that whatever that basic mechanism of DNA, whatever that basic building blocks of programming,
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if you just add more abilities, more high resolution sensors, more sensors, you just
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keep stacking those things on top that this basic programming in trying to survive develops
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very interesting things that start to us humans to appear like intelligence and consciousness.
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As far as robots go, I think that the self driving cars have that sort of the greatest
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opportunity of developing something like that, because when I drive myself, I don't just
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pay attention to the rules of the road.
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I also look around and I get clues from that, oh, this is a shopping district, oh, here's
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an old lady crossing the street, oh, here is someone carrying a pile of mail, there's
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a mailbox, I bet you they're going to cross the street to reach that mailbox.
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And I slow down, and I don't even think about that.
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And so, there is so much where you turn your observations into an understanding of what
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other consciousnesses are going to do, or what other systems in the world are going
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to be, oh, that tree is going to fall.
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I see sort of, I see much more of, I expect somehow that if anything is going to become
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unconscious, it's going to be the self driving car and not the network of a bazillion computers
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in a Google or Amazon data center that are all networked together to do whatever they
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So, in that sense, so you actually highlight, because that's what I work in Thomas Vehicles,
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you highlight the big gap between what we currently can't do and what we truly need
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to be able to do to solve the problem.
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Under that formulation, then consciousness and intelligence is something that basically
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a system should have in order to interact with us humans, as opposed to some kind of
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abstract notion of a consciousness.
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Consciousness is something that you need to have to be able to empathize, to be able to
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fear, understand what the fear of death is, all these aspects that are important for interacting
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with pedestrians, you need to be able to do basic computation based on our human desires
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And if you sort of, yeah, if you look at the dog, the dog clearly knows, I mean, I'm
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not the dog owner, but I have friends who have dogs, the dogs clearly know what the
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humans around them are going to do, or at least they have a model of what those humans
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are going to do and they learn.
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Some dogs know when you're going out and they want to go out with you, they're sad when
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you leave them alone, they cry, they're afraid because they were mistreated when they were
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We don't assign sort of consciousness to dogs, or at least not all that much, but I also
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don't think they have none of that.
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So I think it's consciousness and intelligence are not all or nothing.
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The spectrum is really interesting.
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But in returning to programming languages and the way we think about building these
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kinds of things, about building intelligence, building consciousness, building artificial
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So I think one of the exciting ideas came in the 17th century and with Leibniz, Hobbes,
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Descartes, where there's this feeling that you can convert all thought, all reasoning,
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all the thing that we find very special in our brains, you can convert all of that into
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So you can formalize it, formal reasoning, and then once you formalize everything, all
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of knowledge, then you can just calculate and that's what we're doing with our brains
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is we're calculating.
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So there's this whole idea that this is possible, that this we can actually program.
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But they weren't aware of the concept of pattern matching in the sense that we are aware of
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They sort of thought they had discovered incredible bits of mathematics like Newton's calculus
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and their sort of idealism, their sort of extension of what they could do with logic
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and math sort of went along those lines and they thought there's like, yeah, logic.
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There's like a bunch of rules and a bunch of input.
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They didn't realize that how you recognize a face is not just a bunch of rules but is
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a shit ton of data plus a circuit that sort of interprets the visual clues and the context
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and everything else and somehow can massively parallel pattern match against stored rules.
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I mean, if I see you tomorrow here in front of the Dropbox office, I might recognize you.
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Even if I'm wearing a different shirt, yeah, but if I see you tomorrow in a coffee shop
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in Belmont, I might have no idea that it was you or on the beach or whatever.
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I make those kind of mistakes myself all the time.
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I see someone that I only know as like, oh, this person is a colleague of my wife's and
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then I see them at the movies and I didn't recognize them.
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But do you see those, you call it pattern matching, do you see that rules is unable
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Everything you see, all the pieces of information you look around this room, I'm wearing a black
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shirt, I have a certain height, I'm a human, all these, there's probably tens of thousands
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of facts you pick up moment by moment about this scene.
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You take them for granted and you aggregate them together to understand the scene.
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You don't think all of that could be encoded to where at the end of the day, you can just
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put it all on the table and calculate?
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I don't know what that means.
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I mean, yes, in the sense that there is no actual magic there, but there are enough layers
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of abstraction from the facts as they enter my eyes and my ears to the understanding of
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the scene that I don't think that AI has really covered enough of that distance.
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It's like if you take a human body and you realize it's built out of atoms, well, that
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is a uselessly reductionist view, right?
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The body is built out of organs, the organs are built out of cells, the cells are built
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out of proteins, the proteins are built out of amino acids, the amino acids are built
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out of atoms and then you get to quantum mechanics.
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So that's a very pragmatic view.
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I mean, obviously as an engineer, I agree with that kind of view, but you also have
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to consider the Sam Harris view of, well, intelligence is just information processing.
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Like you said, you take in sensory information, you do some stuff with it and you come up
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with actions that are intelligent.
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That makes it sound so easy.
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I don't know who Sam Harris is.
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Oh, well, it's a philosopher.
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So like this is how philosophers often think, right?
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And essentially that's what Descartes was, is wait a minute, if there is, like you said,
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no magic, so he basically says it doesn't appear like there's any magic, but we know
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so little about it that it might as well be magic.
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So just because we know that we're made of atoms, just because we know we're made
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of organs, the fact that we know very little how to get from the atoms to organs in a way
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that's recreatable means that you shouldn't get too excited just yet about the fact that
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you figured out that we're made of atoms.
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Right, and the same about taking facts as our sensory organs take them in and turning
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that into reasons and actions, that sort of, there are a lot of abstractions that we haven't
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quite figured out how to deal with those.
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I mean, sometimes, I don't know if I can go on a tangent or not, so if I take a simple
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program that parses, say I have a compiler that parses a program, in a sense the input
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routine of that compiler, of that parser, is a sensing organ, and it builds up a mighty
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complicated internal representation of the program it just saw, it doesn't just have
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a linear sequence of bytes representing the text of the program anymore, it has an abstract
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syntax tree, and I don't know how many of your viewers or listeners are familiar with
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compiler technology, but there's…
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Fewer and fewer these days, right?
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That's also true, probably.
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People want to take a shortcut, but there's sort of, this abstraction is a data structure
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that the compiler then uses to produce outputs that is relevant, like a translation of that
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program to machine code that can be executed by hardware, and then that data structure
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When a fish or a fly sees, sort of gets visual impulses, I'm sure it also builds up some
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data structure, and for the fly that may be very minimal, a fly may have only a few, I
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mean, in the case of a fly's brain, I could imagine that there are few enough layers of
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abstraction that it's not much more than when it's darker here than it is here, well
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it can sense motion, because a fly sort of responds when you move your arm towards it,
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so clearly its visual processing is intelligent, well, not intelligent, but it has an abstraction
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for motion, and we still have similar things in, but much more complicated in our brains,
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I mean, otherwise you couldn't drive a car if you couldn't, if you didn't have an
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incredibly good abstraction for motion.
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Yeah, in some sense, the same abstraction for motion is probably one of the primary
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sources of our, of information for us, we just know what to do, I think we know what
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to do with that, we've built up other abstractions on top.
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We build much more complicated data structures based on that, and we build more persistent
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data structures, sort of after some processing, some information sort of gets stored in our
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memory pretty much permanently, and is available on recall, I mean, there are some things that
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you sort of, you're conscious that you're remembering it, like, you give me your phone
link |
number, I, well, at my age I have to write it down, but I could imagine, I could remember
link |
those seven numbers, or ten digits, and reproduce them in a while, if I sort of repeat them
link |
to myself a few times, so that's a fairly conscious form of memorization.
link |
On the other hand, how do I recognize your face, I have no idea.
link |
My brain has a whole bunch of specialized hardware that knows how to recognize faces,
link |
I don't know how much of that is sort of coded in our DNA, and how much of that is
link |
trained over and over between the ages of zero and three, but somehow our brains know
link |
how to do lots of things like that, that are useful in our interactions with other humans,
link |
without really being conscious of how it's done anymore.
link |
Right, so our actual day to day lives, we're operating at the very highest level of abstraction,
link |
we're just not even conscious of all the little details underlying it.
link |
There's compilers on top of, it's like turtles on top of turtles, or turtles all the way
link |
down, there's compilers all the way down, but that's essentially, you say that there's
link |
no magic, that's what I, what I was trying to get at, I think, is with Descartes started
link |
this whole train of saying that there's no magic, I mean, there's all this beforehand.
link |
Well didn't Descartes also have the notion though that the soul and the body were fundamentally
link |
Separate, yeah, I think he had to write in God in there for political reasons, so I don't
link |
know actually, I'm not a historian, but there's notions in there that all of reasoning, all
link |
of human thought can be formalized.
link |
I think that continued in the 20th century with Russell and with Gadot's incompleteness
link |
theorem, this debate of what are the limits of the things that could be formalized, that's
link |
where the Turing machine came along, and this exciting idea, I mean, underlying a lot of
link |
computing that you can do quite a lot with a computer.
link |
You can encode a lot of the stuff we're talking about in terms of recognizing faces and so
link |
on, theoretically, in an algorithm that can then run on a computer.
link |
And in that context, I'd like to ask programming in a philosophical way, what does it mean
link |
to program a computer?
link |
So you said you write a Python program or compiled a C++ program that compiles to some
link |
byte code, it's forming layers, you're programming a layer of abstraction that's higher, how
link |
do you see programming in that context?
link |
Can it keep getting higher and higher levels of abstraction?
link |
I think at some point the higher levels of abstraction will not be called programming
link |
and they will not resemble what we call programming at the moment.
link |
There will not be source code, I mean, there will still be source code sort of at a lower
link |
level of the machine, just like there are still molecules and electrons and sort of
link |
proteins in our brains, but, and so there's still programming and system administration
link |
and who knows what, to keep the machine running, but what the machine does is a different level
link |
of abstraction in a sense, and as far as I understand the way that for the last decade
link |
or more people have made progress with things like facial recognition or the self driving
link |
cars is all by endless, endless amounts of training data where at least as a lay person,
link |
and I feel myself totally as a lay person in that field, it looks like the researchers
link |
who publish the results don't necessarily know exactly how their algorithms work, and
link |
I often get upset when I sort of read a sort of a fluff piece about Facebook in the newspaper
link |
or social networks and they say, well, algorithms, and that's like a totally different interpretation
link |
of the word algorithm, because for me, the way I was trained or what I learned when I
link |
was eight or ten years old, an algorithm is a set of rules that you completely understand
link |
that can be mathematically analyzed and you can prove things.
link |
You can like prove that Aristotelian sieve produces all prime numbers and only prime
link |
So I don't know if you know who Andrej Karpathy is, I'm afraid not.
link |
So he's a head of AI at Tesla now, but he was at Stanford before and he has this cheeky
link |
way of calling this concept software 2.0.
link |
So let me disentangle that for a second.
link |
So kind of what you're referring to is the traditional, the algorithm, the concept of
link |
an algorithm, something that's there, it's clear, you can read it, you understand it,
link |
you can prove it's functioning as kind of software 1.0.
link |
And what software 2.0 is, is exactly what you described, which is you have neural networks,
link |
which is a type of machine learning that you feed a bunch of data and that neural network
link |
learns to do a function.
link |
All you specify is the inputs and the outputs you want and you can't look inside.
link |
You can't analyze it.
link |
All you can do is train this function to map the inputs to the outputs by giving a lot
link |
And that's as programming becomes getting a lot of data.
link |
That's what programming is.
link |
Well, that would be programming 2.0.
link |
To programming 2.0.
link |
I wouldn't call that programming.
link |
It's just a different activity.
link |
Just like building organs out of cells is not called chemistry.
link |
Well, so let's just step back and think sort of more generally, of course.
link |
But you know, it's like as a parent teaching your kids, things can be called programming.
link |
In that same sense, that's how programming is being used.
link |
You're providing them data, examples, use cases.
link |
So imagine writing a function not by, not with for loops and clearly readable text,
link |
but more saying, well, here's a lot of examples of what this function should take.
link |
And here's a lot of examples of when it takes those functions, it should do this.
link |
And then figure out the rest.
link |
So that's the 2.0 concept.
link |
And so the question I have for you is like, it's a very fuzzy way.
link |
This is the reality of a lot of these pattern recognition systems and so on.
link |
It's a fuzzy way of quote unquote programming.
link |
What do you think about this kind of world?
link |
Should it be called something totally different than programming?
link |
If you're a software engineer, does that mean you're designing systems that are very, can
link |
be systematically tested, evaluated, they have a very specific specification and then this
link |
other fuzzy software 2.0 world, machine learning world, that's something else totally?
link |
Or is there some intermixing that's possible?
link |
Well the question is probably only being asked because we don't quite know what that software
link |
And I think there is a truism that every task that AI has tackled in the past, at some point
link |
we realized how it was done and then it was no longer considered part of artificial intelligence
link |
because it was no longer necessary to use that term.
link |
It was just, oh now we know how to do this.
link |
And a new field of science or engineering has been developed and I don't know if sort
link |
of every form of learning or sort of controlling computer systems should always be called programming.
link |
So I don't know, maybe I'm focused too much on the terminology.
link |
But I expect that there just will be different concepts where people with sort of different
link |
education and a different model of what they're trying to do will develop those concepts.
link |
I guess if you could comment on another way to put this concept is, I think the kind of
link |
functions that neural networks provide is things as opposed to being able to upfront
link |
prove that this should work for all cases you throw at it.
link |
All you're able, it's the worst case analysis versus average case analysis.
link |
All you're able to say is it seems on everything we've tested to work 99.9% of the time, but
link |
we can't guarantee it and it fails in unexpected ways.
link |
We can't even give you examples of how it fails in unexpected ways, but it's like really
link |
good most of the time.
link |
Is there no room for that in current ways we think about programming?
link |
programming 1.0 is actually sort of getting to that point too, where the sort of the ideal
link |
of a bug free program has been abandoned long ago by most software developers.
link |
We only care about bugs that manifest themselves often enough to be annoying.
link |
And we're willing to take the occasional crash or outage or incorrect result for granted
link |
because we can't possibly, we don't have enough programmers to make all the code bug free
link |
and it would be an incredibly tedious business.
link |
And if you try to throw formal methods at it, it becomes even more tedious.
link |
So every once in a while the user clicks on a link and somehow they get an error and the
link |
average user doesn't panic.
link |
They just click again and see if it works better the second time, which often magically
link |
it does, or they go up and they try some other way of performing their tasks.
link |
So that's sort of an end to end recovery mechanism and inside systems there is all
link |
sorts of retries and timeouts and fallbacks and I imagine that that sort of biological
link |
systems are even more full of that because otherwise they wouldn't survive.
link |
Do you think programming should be taught and thought of as exactly what you just said?
link |
I come from this kind of, you're always denying that fact always.
link |
In sort of basic programming education, the sort of the programs you're having students
link |
write are so small and simple that if there is a bug you can always find it and fix it.
link |
Because the sort of programming as it's being taught in some, even elementary, middle schools,
link |
in high school, introduction to programming classes in college typically, it's programming
link |
Very few classes sort of actually teach software engineering, building large systems.
link |
Every summer here at Dropbox we have a large number of interns.
link |
Every tech company on the West Coast has the same thing.
link |
These interns are always amazed because this is the first time in their life that they
link |
see what goes on in a really large software development environment.
link |
Everything they've learned in college was almost always about a much smaller scale and
link |
somehow that difference in scale makes a qualitative difference in how you do things and how you
link |
If you then take a few steps back into decades, 70s and 80s, when you were first thinking
link |
about Python or just that world of programming languages, did you ever think that there would
link |
be systems as large as underlying Google, Facebook, and Dropbox?
link |
Did you, when you were thinking about Python?
link |
I was actually always caught by surprise by sort of this, yeah, pretty much every stage
link |
So maybe just because you've spoken in other interviews, but I think the evolution of programming
link |
languages are fascinating and it's especially because it leads from my perspective towards
link |
greater and greater degrees of intelligence.
link |
I learned the first programming language I played with in Russia was with the Turtle
link |
And if you look, I just have a list of programming languages, all of which I've now played with
link |
I mean, they're all beautiful in different ways from Fortran, Cobalt, Lisp, Algol 60,
link |
Basic, Logo again, C, as a few, the object oriented came along in the 60s, Simula, Pascal,
link |
All of that leads.
link |
They're all the classics.
link |
The classic hits, right?
link |
Steam, that's built on top of Lisp.
link |
On the database side, SQL, C++, and all of that leads up to Python, Pascal too, and that's
link |
before Python, MATLAB, these kind of different communities, different languages.
link |
So can you talk about that world?
link |
I know that sort of Python came out of ABC, which I actually never knew that language.
link |
I just, having researched this conversation, went back to ABC and it looks remarkably,
link |
it has a lot of annoying qualities, but underneath those, like all caps and so on, but underneath
link |
that, there's elements of Python that are quite, they're already there.
link |
That's where I got all the good stuff.
link |
All the good stuff.
link |
So, but in that world, you're swimming these programming languages, were you focused on
link |
just the good stuff in your specific circle, or did you have a sense of what is everyone
link |
You said that every programming language is built to scratch an itch.
link |
Were you aware of all the itches in the community?
link |
And if not, or if yes, I mean, what itch were you trying to scratch with Python?
link |
Well, I'm glad I wasn't aware of all the itches because I would probably not have been able
link |
I mean, if you're trying to solve every problem at once, you'll solve nothing.
link |
Well, yeah, it's too overwhelming.
link |
And so I had a very, very focused problem.
link |
I wanted a programming language that sat somewhere in between shell scripting and C. And now,
link |
arguably, there is like, one is higher level, one is lower level.
link |
And Python is sort of a language of an intermediate level, although it's still pretty much at
link |
the high level end.
link |
I was thinking about much more about, I want a tool that I can use to be more productive
link |
as a programmer in a very specific environment.
link |
And I also had given myself a time budget for the development of the tool.
link |
And that was sort of about three months for both the design, like thinking through what
link |
are all the features of the language syntactically and semantically, and how do I implement the
link |
whole pipeline from parsing the source code to executing it.
link |
So I think both with the timeline and the goals, it seems like productivity was at the
link |
core of it as a goal.
link |
So like, for me in the 90s, and the first decade of the 21st century, I was always doing
link |
machine learning, AI programming for my research was always in C++.
link |
And then the other people who are a little more mechanical engineering, electrical engineering,
link |
They're a little bit more MATLAB focused.
link |
Those are the world, and maybe a little bit Java too.
link |
But people who are more interested in emphasizing the object oriented nature of things.
link |
So within the last 10 years or so, especially with the oncoming of neural networks and these
link |
packages that are built on Python to interface with neural networks, I switched to Python
link |
and it's just, I've noticed a significant boost that I can't exactly, because I don't
link |
think about it, but I can't exactly put into words why I'm just much, much more productive.
link |
Just being able to get the job done much, much faster.
link |
So how do you think, whatever that qualitative difference is, I don't know if it's quantitative,
link |
it could be just a feeling, I don't know if I'm actually more productive, but how
link |
do you think about...
link |
Well, that's right.
link |
I think there's elements, let me just speak to one aspect that I think that was affecting
link |
my productivity is C++ was, I really enjoyed creating performant code and creating a beautiful
link |
structure where everything that, you know, this kind of going into this, especially with
link |
the newer and newer standards of templated programming of just really creating this beautiful
link |
formal structure that I found myself spending most of my time doing that as opposed to getting
link |
it, parsing a file and extracting a few keywords or whatever the task was trying to do.
link |
So what is it about Python?
link |
How do you think of productivity in general as you were designing it now, sort of through
link |
the decades, last three decades, what do you think it means to be a productive programmer?
link |
And how did you try to design it into the language?
link |
There are different tasks and as a programmer, it's useful to have different tools available
link |
that sort of are suitable for different tasks.
link |
So I still write C code, I still write shell code, but I write most of my things in Python.
link |
Why do I still use those other languages, because sometimes the task just demands it.
link |
And well, I would say most of the time the task actually demands a certain language because
link |
the task is not write a program that solves problem X from scratch, but it's more like
link |
fix a bug in existing program X or add a small feature to an existing large program.
link |
But even if you're not constrained in your choice of language by context like that, there
link |
is still the fact that if you write it in a certain language, then you have this balance
link |
between how long does it take you to write the code and how long does the code run?
link |
And when you're in the phase of exploring solutions, you often spend much more time
link |
writing the code than running it because every time you've run it, you see that the output
link |
is not quite what you wanted and you spend some more time coding.
link |
And a language like Python just makes that iteration much faster because there are fewer
link |
details that you have to get right before your program compiles and runs.
link |
There are libraries that do all sorts of stuff for you, so you can sort of very quickly take
link |
a bunch of existing components, put them together, and get your prototype application running.
link |
Just like when I was building electronics, I was using a breadboard most of the time,
link |
so I had this sprawl out circuit that if you shook it, it would stop working because it
link |
was not put together very well, but it functioned and all I wanted was to see that it worked
link |
and then move on to the next schematic or design or add something to it.
link |
Once you've sort of figured out, oh, this is the perfect design for my radio or light
link |
sensor or whatever, then you can say, okay, how do we design a PCB for this?
link |
How do we solder the components in a small space?
link |
How do we make it so that it is robust against, say, voltage fluctuations or mechanical disruption?
link |
I know nothing about that when it comes to designing electronics, but I know a lot about
link |
that when it comes to writing code.
link |
So the initial steps are efficient, fast, and there's not much stuff that gets in the
link |
way, but you're kind of describing, like Darwin described the evolution of species, right?
link |
You're observing of what is true about Python.
link |
Now if you take a step back, if the act of creating languages is art and you had three
link |
months to do it, initial steps, so you just specified a bunch of goals, sort of things
link |
that you observe about Python, perhaps you had those goals, but how do you create the
link |
rules, the syntactic structure, the features that result in those?
link |
So I have in the beginning and I have follow up questions about through the evolution of
link |
Python too, but in the very beginning when you were sitting there creating the lexical
link |
analyzer or whatever.
link |
Python was still a big part of it because I sort of, I said to myself, I don't want
link |
to have to design everything from scratch, I'm going to borrow features from other languages
link |
So you basically, exactly, you first observe what you like.
link |
Yeah, and so that's why if you're 17 years old and you want to sort of create a programming
link |
language, you're not going to be very successful at it because you have no experience with
link |
other languages, whereas I was in my, let's say mid 30s, I had written parsers before,
link |
so I had worked on the implementation of ABC, I had spent years debating the design of ABC
link |
with its authors, with its designers, I had nothing to do with the design, it was designed
link |
fully as it ended up being implemented when I joined the team.
link |
But so you borrow ideas and concepts and very concrete sort of local rules from different
link |
languages like the indentation and certain other syntactic features from ABC, but I chose
link |
to borrow string literals and how numbers work from C and various other things.
link |
So in then, if you take that further, so yet you've had this funny sounding, but I think
link |
surprisingly accurate and at least practical title of benevolent dictator for life for
link |
quite, you know, for the last three decades or whatever, or no, not the actual title,
link |
but functionally speaking.
link |
So you had to make decisions, design decisions.
link |
Can you maybe, let's take Python 2, so releasing Python 3 as an example.
link |
It's not backward compatible to Python 2 in ways that a lot of people know.
link |
So what was that deliberation, discussion, decision like?
link |
What was the psychology of that experience?
link |
Do you regret any aspects of how that experience undergone that?
link |
Well, yeah, so it was a group process really.
link |
At that point, even though I was BDFL in name and certainly everybody sort of respected
link |
my position as the creator and the current sort of owner of the language design, I was
link |
looking at everyone else for feedback.
link |
Sort of Python 3.0 in some sense was sparked by other people in the community pointing
link |
out, oh, well, there are a few issues that sort of bite users over and over.
link |
Can we do something about that?
link |
And for Python 3, we took a number of those Python words as they were called at the time
link |
and we said, can we try to sort of make small changes to the language that address those
link |
And we had sort of in the past, we had always taken backwards compatibility very seriously.
link |
And so many Python words in earlier versions had already been resolved because they could
link |
be resolved while maintaining backwards compatibility or sort of using a very gradual path of evolution
link |
of the language in a certain area.
link |
And so we were stuck with a number of words that were widely recognized as problems, not
link |
like roadblocks, but nevertheless sort of things that some people trip over and you know that
link |
that's always the same thing that people trip over when they trip.
link |
And we could not think of a backwards compatible way of resolving those issues.
link |
But it's still an option to not resolve the issues, right?
link |
And so yes, for a long time, we had sort of resigned ourselves to, well, okay, the language
link |
is not going to be perfect in this way and that way and that way.
link |
And we sort of, certain of these, I mean, there are still plenty of things where you
link |
can say, well, that particular detail is better in Java or in R or in Visual Basic or whatever.
link |
And we're okay with that because, well, we can't easily change it.
link |
We can do a little bit with user education or we can have a static analyzer or warnings
link |
in the parse or something.
link |
But there were things where we thought, well, these are really problems that are not going
link |
They are getting worse in the future.
link |
We should do something about that.
link |
But ultimately there is a decision to be made, right?
link |
So was that the toughest decision in the history of Python you had to make as the benevolent
link |
dictator for life?
link |
Or if not, what are there, maybe even on the smaller scale, what was the decision where
link |
you were really torn up about?
link |
Well, the toughest decision was probably to resign.
link |
All right, let's go there.
link |
Hold on a second then.
link |
Let me just, because in the interest of time too, because I have a few cool questions for
link |
you and let's touch a really important one because it was quite dramatic and beautiful
link |
in certain kinds of ways.
link |
In July this year, three months ago, you wrote, now that PEP 572 is done, I don't ever want
link |
to have to fight so hard for a PEP and find that so many people despise my decisions.
link |
I would like to remove myself entirely from the decision process.
link |
I'll still be there for a while as an ordinary core developer and I'll still be available
link |
to mentor people, possibly more available.
link |
But I'm basically giving myself a permanent vacation from being BDFL, benevolent dictator
link |
And you all will be on your own.
link |
First of all, it's almost Shakespearean.
link |
I'm not going to appoint a successor.
link |
So what are you all going to do?
link |
Create a democracy, anarchy, a dictatorship, a federation?
link |
So that was a very dramatic and beautiful set of statements.
link |
It's almost, it's open ended nature called the community to create a future for Python.
link |
It's just kind of a beautiful aspect to it.
link |
So what, and dramatic, you know, what was making that decision like?
link |
What was on your heart, on your mind, stepping back now a few months later?
link |
I'm glad you liked the writing because it was actually written pretty quickly.
link |
It was literally something like after months and months of going around in circles, I had
link |
finally approved PEP572, which I had a big hand in its design, although I didn't initiate
link |
I sort of gave it a bunch of nudges in a direction that would be better for the language.
link |
So sorry, just to ask, is async IO, that's the one or no?
link |
PEP572 was actually a small feature, which is assignment expressions.
link |
That had been, there was just a lot of debate where a lot of people claimed that they knew
link |
what was Pythonic and what was not Pythonic, and they knew that this was going to destroy
link |
This was like a violation of Python's most fundamental design philosophy, and I thought
link |
that was all bullshit because I was in favor of it, and I would think I know something
link |
about Python's design philosophy.
link |
So I was really tired and also stressed of that thing, and literally after sort of announcing
link |
I was going to accept it, a certain Wednesday evening I had finally sent the email, it's
link |
I can just go implement it.
link |
So I went to bed feeling really relieved, that's behind me.
link |
And I wake up Thursday morning, 7 a.m., and I think, well, that was the last one that's
link |
going to be such a terrible debate, and that's the last time that I let myself be so stressed
link |
out about a pep decision.
link |
I should just resign.
link |
I've been sort of thinking about retirement for half a decade, I've been joking and sort
link |
of mentioning retirement, sort of telling the community at some point in the future
link |
I'm going to retire, don't take that FL part of my title too literally.
link |
And I thought, okay, this is it.
link |
I'm done, I had the day off, I wanted to have a good time with my wife, we were going to
link |
a little beach town nearby, and in I think maybe 15, 20 minutes I wrote that thing that
link |
you just called Shakespearean.
link |
The funny thing is I didn't even realize what a monumental decision it was, because
link |
five minutes later I read that link to my message back on Twitter, where people were
link |
already discussing on Twitter, Guido resigned as the BDFL.
link |
And I had posted it on an internal forum that I thought was only read by core developers,
link |
so I thought I would at least have one day before the news would sort of get out.
link |
The on your own aspects had also an element of quite, it was quite a powerful element
link |
of the uncertainty that lies ahead, but can you also just briefly talk about, for example
link |
I play guitar as a hobby for fun, and whenever I play people are super positive, super friendly,
link |
they're like, this is awesome, this is great.
link |
But sometimes I enter as an outside observer, I enter the programming community and there
link |
seems to sometimes be camps on whatever the topic, and the two camps, the two or plus
link |
camps, are often pretty harsh at criticizing the opposing camps.
link |
As an onlooker, I may be totally wrong on this, but what do you think of this?
link |
Yeah, holy wars are sort of a favorite activity in the programming community.
link |
And what is the psychology behind that?
link |
Is that okay for a healthy community to have?
link |
Is that a productive force ultimately for the evolution of a language?
link |
Well, if everybody is patting each other on the back and never telling the truth, it would
link |
not be a good thing.
link |
I think there is a middle ground where sort of being nasty to each other is not okay,
link |
but there is a middle ground where there is healthy ongoing criticism and feedback that
link |
is very productive.
link |
And you mean at every level you see that.
link |
I mean, someone proposes to fix a very small issue in a code base, chances are that some
link |
reviewer will sort of respond by saying, well, actually, you can do it better the other way.
link |
When it comes to deciding on the future of the Python core developer community, we now
link |
have, I think, five or six competing proposals for a constitution.
link |
So that future, do you have a fear of that future, do you have a hope for that future?
link |
I'm very confident about that future.
link |
By and large, I think that the debate has been very healthy and productive.
link |
And I actually, when I wrote that resignation email, I knew that Python was in a very good
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spot and that the Python core developer community, the group of 50 or 100 people who sort of
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write or review most of the code that goes into Python, those people get along very well
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A large number of different areas of expertise are represented, different levels of experience
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in the Python core dev community, different levels of experience completely outside it
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in software development in general, large systems, small systems, embedded systems.
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So I felt okay resigning because I knew that the community can really take care of itself.
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And out of a grab bag of future feature developments, let me ask if you can comment, maybe on all
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very quickly, concurrent programming, parallel computing, async IO.
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These are things that people have expressed hope, complained about, whatever, have discussed
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Async IO, so the parallelization in general, packaging, I was totally clueless on this.
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I just used pip to install stuff, but apparently there's pipenv, poetry, there's these dependency
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packaging systems that manage dependencies and so on.
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They're emerging and there's a lot of confusion about what's the right thing to use.
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Then also functional programming, are we going to get more functional programming or not,
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this kind of idea.
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And of course the GIL connected to the parallelization, I suppose, the global interpreter lock problem.
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Can you just comment on whichever you want to comment on?
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Well, let's take the GIL and parallelization and async IO as one topic.
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I'm not that hopeful that Python will develop into a sort of high concurrency, high parallelism
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That's sort of the way the language is designed, the way most users use the language, the way
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the language is implemented, all make that a pretty unlikely future.
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So you think it might not even need to, really the way people use it, it might not be something
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that should be of great concern.
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I think async IO is a special case because it sort of allows overlapping IO and only
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IO and that is a sort of best practice of supporting very high throughput IO, many connections
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I'm not worried about that.
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I think async IO will evolve.
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There are a couple of competing packages.
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We have some very smart people who are sort of pushing us to make async IO better.
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Parallel computing, I think that Python is not the language for that.
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There are ways to work around it, but you can't expect to write an algorithm in Python
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and have a compiler automatically parallelize that.
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What you can do is use a package like NumPy and there are a bunch of other very powerful
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packages that sort of use all the CPUs available because you tell the package, here's the data,
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here's the abstract operation to apply over it, go at it, and then we're back in the C++
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Those packages are themselves implemented usually in C++.
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That's where TensorFlow and all these packages come in, where they parallelize across GPUs,
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for example, they take care of that for you.
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In terms of packaging, can you comment on the future of packaging in Python?
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Packaging has always been my least favorite topic.
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It's a really tough problem because the OS and the platform want to own packaging, but
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their packaging solution is not specific to a language.
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If you take Linux, there are two competing packaging solutions for Linux or for Unix
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in general, but they all work across all languages.
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Several languages like Node, JavaScript, Ruby, and Python all have their own packaging solutions
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that only work within the ecosystem of that language.
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What should you use?
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That is a tough problem.
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My own approach is I use the system packaging system to install Python, and I use the Python
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packaging system then to install third party Python packages.
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That's what most people do.
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Ten years ago, Python packaging was really a terrible situation.
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Nowadays, pip is the future, there is a separate ecosystem for numerical and scientific Python
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based on Anaconda.
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Those two can live together.
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I don't think there is a need for more than that.
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Well, at least for me, that's where I've been extremely happy.
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I didn't even know this was an issue until it was brought up.
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In the interest of time, let me sort of skip through a million other questions I have.
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So I watched the five and a half hour oral history that you've done with the Computer
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History Museum, and the nice thing about it, it gave this, because of the linear progression
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of the interview, it gave this feeling of a life, you know, a life well lived with interesting
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things in it, sort of a pretty, I would say a good spend of this little existence we have
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So, outside of your family, looking back, what about this journey are you really proud
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Are there moments that stand out, accomplishments, ideas?
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Is it the creation of Python itself that stands out as a thing that you look back and say,
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damn, I did pretty good there?
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Well, I would say that Python is definitely the best thing I've ever done, and I wouldn't
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sort of say just the creation of Python, but the way I sort of raised Python, like a baby.
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I didn't just conceive a child, but I raised a child, and now I'm setting the child free
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in the world, and I've set up the child to sort of be able to take care of himself, and
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I'm very proud of that.
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And as the announcer of Monty Python's Flying Circus used to say, and now for something
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completely different, do you have a favorite Monty Python moment, or a moment in Hitchhiker's
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Guide, or any other literature show or movie that cracks you up when you think about it?
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You can always play me the dead parrot sketch.
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Oh, that's brilliant.
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That's my favorite as well.
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It's pushing up the daisies.
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Okay, Greta, thank you so much for talking with me today.
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Lex, this has been a great conversation.