The following is a conversation with Guido van Rossum, creator of Python, 1 of the most popular programming languages in the world, used in almost any application that involves computers, from web back-end development to psychology, neuroscience, computer vision, robotics, deep learning, natural language processing, and almost any subfield of AI.

This conversation is part of MIT course on Artificial General Intelligence and the Artificial Intelligence Podcast.

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And now, here's my conversation with Guido van Rossum.

You were born in the Netherlands in 1956.

Your parents and the world around you was deeply impacted by World War II, as was my family from the Soviet Union.

So with that context, What is your view of human nature?

Are some humans inherently good and some inherently evil or do we all have both good and evil within us?

I guess we all have good and evil potential in us and a lot of it depends on circumstances and context.

Out of that world, at least on the Soviet Union side and in Europe, out of suffering, out of challenge, out of that kind of set of traumatic events, often emerges beautiful art, music, literature.

In an interview I read or heard you said you enjoyed Dutch literature when you were a child.

Can you tell me about the books that had an influence on you in your childhood?

Well, as a teenager my favorite writer was, my favorite Dutch author was a guy named Willem Frederik Hermans, whose writing, certainly his early novels, were all about sort of ambiguous things that happened during World War II.

I think he was a young adult during that time and he wrote about it a lot, and very interesting, very good books, I thought, I think.

No, it was all fiction, but it was very much set in the ambiguous world of resistance against the Germans, where often you couldn't tell whether someone was truly in the resistance or really a spy for the Germans.

And some of the characters in his novels sort of cross that line and you never really find out what

And in his novels, there's always a good guy and a bad guy.

Is the nature of good and evil, is it clear there's a hero?

It's no, his heroes are often more, his main characters are often anti-heroes.

They're often, they fail at some level to accomplish their lofty goals.

And looking at the trajectory through the rest of your life, has literature, Dutch or English or translation had an impact outside the technical world that you existed in?

I don't think that it impacts me that much directly.

My work is highly technical and sort of the world of art and literature doesn't really directly have any bearing on it.

You don't think there's a creative element to the design?

You know, some would say art, design of a language is art.

I'm just saying that sort of I don't feel direct influences from more traditional art on my own creativity.

Right, of course, you don't feel doesn't mean it's not somehow deeply there in your subconscious.

Your hobbies were building electronic circuits, building mechanical models.

What, if you can just put yourself back in the mind of that young Guido 12 13 14 Was that grounded in a desire to create a system so to create something or was it more just tinkering?

Maybe towards the end of my high school period I felt confident enough that I designed my own circuits that were sort of interesting, somewhat.

But a lot of that time I literally just took a model kit and followed the instructions, putting the things together.

I mean, I think the first few years that I built electronics kits, I really did not have enough understanding of sort of electronics to really understand what I was doing.

I mean, I could debug it and I could sort of follow the instructions very carefully, which has always stayed with me, but I had a very naive model of like how a transistor works.

And I don't think that in those days I had any understanding of coils and capacitors, which actually sort of was a major problem when I started to build more complex digital circuits because I was unaware of the sort of the analog part of the how they actually work and I would have things that the scheme the schematic looked every everything looked fine and it didn't work.

And what I didn't realize was that there was some megahertz level oscillation that was throwing the circuit off because I had a sort of 2 wires were too close or the switches were were kind of poorly built.

But through that time I think it's really interesting and instructive to think about because echoes of it are in this time now.

So in the 1970s, the personal computer was being born.

So did you sense in tinkering with these circuits, did you sense the encroaching revolution in personal computing?

So if at that point we would sit you down and ask you to predict the 80s and the 90s, do you think you would be able to do so successfully to unroll the process that's happening?

I remember, I think in the summer after my senior year, or maybe it was the summer after my junior year.

Well, at some point, I think when I was 18, I went on a trip to the Math Olympiad in Eastern Europe.

And there was like, I was part of the Dutch team.

And there were other nerdy kids that sort of had different experiences and 1 of them told me about this amazing thing called a computer and I had never heard that word.

My own explorations in electronics were sort of about very simple digital circuits.

And I had sort of, I had the idea that I somewhat understood how a digital calculator worked.

And so there is maybe some echoes of computers there, but I didn't, I never made that connection.

I didn't know that when my parents were paying for magazine subscriptions using punched cards that there was something called a computer that was involved that read those cards and transferred the money between accounts.

I was also not really interested in those things.

It was only when I went to university to study math that I found out that they had a computer and students were allowed to use it.

And there was some, you're supposed to talk to that computer by programming it.

Yeah, that was the only thing you could do with it.

The computer wasn't really connected to the real world.

The only thing you could do was, you typed your program on a bunch of punched cards, you gave the punched cards to the operator, and an hour later the operator gave you back your printout.

And so all you could do was write a program that did something very abstract.

And I don't even remember what my first forays into programming were, but they were sort of doing simple math exercises and just to learn how a programming language worked.

Did you sense, okay, first year of college, you see this computer, you're able to have a program and it generates some output.

Did you start seeing the possibility of this or was it a continuation of the tinkering with circuits?

Did you start to imagine that 1, the personal computer, but did you see it as something that is a tool, like a word processing tool, maybe for gaming or something?

Or did you start to imagine that it could be, you know, going to the world of robotics?

Like you, you know, the Frankenstein picture that you could create an artificial being, there's like another entity in front of you.

I was really more interested in the tinkering.

It's maybe not a sort of a complete coincidence that I ended up sort of creating a programming language which is a tool for other programmers.

I've always been very focused on the sort of activity of programming itself and not so much what happens with the program you write.

I do remember, and I don't remember, maybe in my second or third year, probably my second actually, someone pointed out to me that there was this thing called Conway's Game of Life.

In the 70s, I think is when he came up with it.

So there was a Scientific American column by someone who did a monthly column about mathematical diversions.

It was very famous at the time, and I think up to the 90s or so.

And 1 of his columns was about Conway's game of life, and he had some illustrations, and he wrote down all the rules, and sort of there was the suggestion that this was philosophically interesting, that that was why Conway had called it that.

And all I had was like the 2 pages photocopy of that article.

But it spoke to me and I remember implementing a version of that game for the batch computer we were using where I had a whole Pascal program that sort of read an initial situation from input and read some numbers that that said, do so many generations and print every so many generations And then out would come pages and pages of, of sort of things.

And I remember much later I've done a similar thing using Python, but I'd sort of that original version I wrote at the time I found interesting because I combined it with some trick I had learned during my electronics hobbyist times.

I essentially first on paper I designed a simple circuit built out of logic gates that took 9 bits of input, which is the sort of the cell and its neighbors, and produced a new value for that cell.

And it's like a combination of a half adder and some other clipping.

And so I had worked that out, and then I translated that into a series of Boolean operations on Pascal integers where you could use the integers as bitwise values.

And so I could basically generate 60 bits of a generation in like 8 instructions or so.

It's funny that you mentioned, so for people who don't know, Conway's Game of Life is a, there's a cellular automata where there's single compute units that kind of look at their neighbors and figure out what they look like in the next generation based on the state of their neighbors and this is deeply distributed system in concept at least.

And then there's simple rules that all of them follow and somehow out of this simple rule when you step back and look at what occurs, it's beautiful, there's an emergent complexity, even though the underlying rules are simple, there's an emergent complexity.

Now the funny thing is you've implemented this and the thing you're commenting on is you're proud of a hack you did to make it run efficiently.

When you're not commenting on, what like this is a beautiful implementation.

You're not commenting on the fact that there's an emergent complexity, that you've coded a simple program, and when you step back and you print out the following generation after generation, that's stuff that you may have not predicted would happen is happening.

I mean, that's the magic that all of us feel when we program.

When you create a program and then you run it, whether it's Hello World or it shows something on screen, if there's a graphical component, are you seeing the magic and the mechanism of creating that?

As a student, we had an incredibly small budget of computer time that we could use, it was actually measured, I once got in trouble with 1 of my professors because I had overspent the department's budget.

I actually wanted the efficient implementation because I also wanted to explore what would happen with a larger number of generations and a larger size of the board.

Once the implementation was flawless, I would feed it different patterns and then I think maybe there was a follow-up article where there were patterns that were like gliders, patterns that repeated themselves after a number of generations, but, translated 1 or 2 positions to the right or up or something like that.

And there were, I remember things like glider guns.

Well, you can Google Conway's Game of Life.

For a reason, because it's not really well understood why.

I mean, this is what Stephen Wolfram is obsessed about.

He's just, we don't have the mathematical tools to describe the kind of complexity that emerges in these kinds of systems.

And the only way you can do it is to run it.

I'm not convinced that it's sort of a problem that lends itself to classic mathematical analysis.

And so 1 theory of how you create an artificial intelligence or an artificial being is you kind of have to, same with the game of life, you kind of have to create a universe and let it run.

That creating it from scratch in a design way, coding up a Python program that creates a full intelligence system may be quite challenging.

You might need to create a universe, just like the game of life.

Well you might have to experiment with a lot of different universes before there is a set of rules that doesn't essentially always just end up repeating itself in a trivial way.

Yeah, and Steve Wolfram, Stephen Wolfram works with these simple rules, says that it's kind of surprising how quickly you find rules that create interesting things.

You shouldn't be able to, but somehow you do.

And so maybe our universe is laden with rules that will create interesting things that might not look like humans, but the emergent phenomena that's interesting may not be as difficult to create as we think.

But let me sort of ask, at that time, some of the world, at least in popular press, was kind of captivated, perhaps at least in America, by the idea of artificial intelligence.

That these computers would be able to think pretty soon.

I didn't really start reading science fiction until much, much later.

I think as a teenager I read maybe 1 bundle of science fiction stories.

build something intelligent always felt to me because I felt I had so much understanding of what actually goes on inside a computer.

I knew how many bits of memory it had and how difficult it was to program and sort of, I didn't believe at all that you could just build something intelligent out of that, that would really sort of satisfy my definition of intelligence.

I think the most influential thing that I read in my early 20s was Gödel, Escher, Bach.

That was about consciousness and that was a big eye-opener in some sense.

So, yeah, on your own brain, did you at the time or do you now see your own brain as a computer?

Or is there a total separation of the way?

So yeah, you're very pragmatically, practically know the limits of memory, the limits of this sequential computing or weekly paralyzed computing.

And you just know what we have now and it's hard to see how it creates.

But it's also easy to see it was in the 40s, 50s, 60s and now at least similarities between the brain and our computers.

Oh yeah, I mean I totally believe that brains are computers in some sense.

I mean, the rules they use to play by are pretty different from the rules we can sort of implement in our current hardware.

But I don't believe in like a separate thing that infuses us with intelligence or consciousness or any of that.

I've been an atheist probably from when I was 10 years old, just by thinking a bit about math and the universe.

Now I know that you could be an atheist and still believe that there is something sort of about intelligence or consciousness that cannot possibly emerge from a fixed set of rules, I am not in that camp.

I totally see that, sort of, given how many millions of years evolution took its time.

DNA is a particular machine that sort of encodes information and an unlimited amount of information in chemical form and has figured out a way to replicate itself.

I thought that that was, maybe it's 300 million years ago, but I thought it was closer to half a billion years ago that that sort of originated and it hasn't really changed, that the sort of the structure of DNA hasn't changed ever since.

That is like our binary code that we have in hardware.

The basic programming language hasn't changed, but maybe the programming itself.

It happened to be a set of rules that was good enough to sort of develop endless variability and sort of the idea of self-replicating molecules competing with each other for resources and 1 type eventually sort of always taking over.

That happened before there were any fossils.

So we don't know how that exactly happened, but I believe it's clear that that did happen.

Can you comment on consciousness and how you see it?

Because I think we'll talk about programming quite a bit, we'll talk about intelligence connecting to programming fundamentally, but consciousness is this whole other thing.

Do you think about it often as a developer of a programming language and as a human?

Those are pretty sort of separate topics.

My line of work, working with programming, does not involve anything that goes in the direction of developing intelligence or consciousness.

But sort of privately, as an avid reader of popular science writing, I have some thoughts which is mostly that I don't actually believe that consciousness is an all or nothing thing.

I have a feeling that, and I forget what I read that influenced this, but I feel that if you look at a cat or a dog or a mouse, they have some form of intelligence.

If you look at a fish, it has some form of intelligence.

And that evolution just took a long time, but I feel that the evolution of more and more intelligence that led to the human form of intelligence followed the evolution of the senses, especially the visual sense.

I mean, there is an enormous amount of processing that's needed to interpret a scene, and humans are still better at that than computers are.

And I have a feeling that there is a sort of the reason that mammals in particular developed the levels of consciousness that they have, and then eventually going from intelligence to self-awareness and consciousness, has to do with sort of being a robot that has very highly developed senses.

Has a lot of rich sensory information coming in.

So, that's a really interesting thought, that whatever that basic mechanism of DNA, whatever that basic building blocks of programming, is if you just add more abilities, more high resolution sensors, more sensors, You just keep stacking those things on top that this basic programming in trying to survive develops very interesting things that start to us humans to appear like intelligence and consciousness.

Yeah, so as far as robots go, I think that the self-driving cars have the greatest opportunity of developing something like that, because when I drive myself, I don't just pay attention to the rules of the road.

I also look around and I get clues from that.

Oh here's an old lady crossing the street.

Oh, here is someone carrying a pile of mail.

I bet you they're going to cross the street to reach that mailbox.

And so there is so much where you turn your observations into an understanding of what other consciousnesses are going to do or what other systems in the world are going to be.

Of I expect somehow that If anything is going to become conscious, it's going to be the self-driving car and not the network of a bazillion computers in a Google or Amazon data center that are all networked together to do whatever they do.

In that sense, you actually highlight, that's where I work in autonomous vehicles, you highlight the big gap between what we currently can't do and what we truly need to be able to do to solve the problem.

Under that formulation then consciousness and intelligence is something that basically a system should have in order to interact with us humans as opposed to some kind of abstract notion of consciousness.

Consciousness is something that you need to have to be able to empathize, to be able to fear, understand what the fear of death is, all these aspects that are important for interacting with pedestrians need to be able to do basic computation based on are human desires and and thought

if you sort of yet if you if you look at the dog the dog clearly knows me now another dog owner my buddy I have friends who have dogs The dogs clearly know what the humans around them are going to do, or at least they have a model of what those humans are going to do, and they learn.

Some dogs know when you're going out, and they want to go out with you, they're sad when you leave them alone, they cry, they're afraid because they were mistreated when they were younger.

We don't assign sort of consciousness to dogs or at least not all that much.

But I also don't think they have none of that.

So I think it's Consciousness and intelligence are not all or nothing.

But in returning to programming languages and the way we think about building these kinds of things, about building intelligence, building consciousness, building artificial beings.

So I think 1 of the exciting ideas came in the 17th century, and with Leibniz, Hobbes, Descartes, where there's this feeling that you can convert all thought, all reasoning, the thing that we find very special in our brains, you can convert all of that into logic.

And then once you formalize everything, all of knowledge, then you can just calculate.

And that's what we're doing with our brains is we're calculating.

So there's this whole idea that this is possible.

they weren't aware of the concept of pattern matching in the sense that we are aware of it now.

They sort of thought you, they had discovered incredible bits of mathematics like Newton's calculus.

And their sort of idealism, their sort of extension of what they could do with logic and math sort of went along those lines.

And they thought, yeah, logic, there's a bunch of rules and a bunch of input.

They didn't realize that how you recognize a face is not just a bunch of rules, but is a shit ton of data.

Plus a circuit that sort of interprets the visual clues and the context and everything else, and somehow can massively parallel pattern match against stored rules.

I mean, if I see you tomorrow here in front of the Dropbox office, I might recognize you.

Yeah, but if I see you tomorrow in a coffee shop in Belmont, I might have no idea that it was you or on the beach or whatever.

I make those kind of mistakes myself all the time.

I see someone that I only know as like, oh, this person is a colleague of my wife's.

And then I see them at the movies and I don't recognize them.

But do you see those, you call it pattern matching, do you see that rules is unable to encode that?

Everything you see, all the pieces of information, you look around this room, I'm wearing a black shirt, I have a certain height, I'm a human, all these, there's probably tens of thousands of facts you pick up moment by moment about this scene, You take them for granted and you accumulate, aggregate them together to understand the scene.

You don't think all of that could be encoded to where at the end of the day you can just put it all on the table and calculate?

I mean, yes in the sense that there is no actual magic there, but there are enough layers of abstraction from the facts as they enter my eyes and my ears to the understanding of the scene.

I don't think that AI has really covered enough of that distance.

It's like if you take a human body and you realize it's built out of atoms, well, that is a uselessly reductionist view, right?

The body is built out of organs, the organs are built out of cells, the cells are built out of proteins, the proteins are built out of amino acids, the amino acids are built out of atoms and then you get to quantum mechanics.

So that's a very pragmatic view, I mean obviously as an engineer I agree with that kind of view, but you also have to consider the, with the Sam Harris view of, well, intelligence is just information processing.

You just, like you said, you take in sensory information, you do some stuff with it, and you come up with actions that are intelligent.

So like this is how philosophers often think, right?

And essentially that's what Descartes was, is wait a minute, if there is, like you said, no magic, so he basically says it doesn't appear like there's any magic, but we know so little about it that it might as well be magic.

So just because we know that we're made of atoms, just because we know we're made of organs, the fact that we know very little how to get from the atoms to organs in a way that's recreatable means that you shouldn't get too excited just yet about the fact that you figured out that we're made of atoms.

Right, and the same about taking facts as our sensory organs take them in, and turning that into reasons and actions.

That sort of, There are a lot of abstractions that we haven't quite figured out how to deal with those.

Sometimes I don't know if I can go on a tangent or not.

So, if I take a simple program that parses, say I have a compiler, it parses a program.

In a sense, the input routine of that compiler, of that parser, is a sensing organ.

And it builds up a mighty complicated internal representation of the program it just saw.

It doesn't just have a linear sequence of bytes representing the text of the program anymore.

And I don't know how many of your viewers or listeners are familiar with compiler technology, but there's- Fewer and fewer these days, right?

People want to take a shortcut, but there is sort of...

This abstraction is a data structure that the compiler then uses to produce outputs that is relevant, like a translation of that program to machine code that can be executed by hardware.

And then that data structure gets thrown away.

When a fish or a fly sees, sort of gets visual impulses, I'm sure it also builds up some data structure and for the fly that may be very minimal a fly may may have only a few I mean in the case of a fly's brain I could imagine that there are few enough layers of abstraction that it's not much more than when it's darker here than it is here.

Well, it can sense motion because a fly sort of responds when you move your arm towards it.

So clearly, it's visual processing is intelligent.

Well, not intelligent, but it has an abstraction for motion.

And we still have similar things in, but much more complicated in our brains.

I mean, otherwise you couldn't drive a car if you didn't have an incredibly good abstraction for motion.

Yeah, in some sense the same abstraction for motion is probably 1 of the primary sources of our, of information for us.

We just know what to do, I think we know what to do with that.

We've built up other abstractions on top.

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Guido van Rossum: Python | Lex Fridman Podcast #6