The future of networking technology

20:45Keith Winstein:Don't forget, at the end of this segment, I will have the future in a minute segment with Keith while I'll ask him some quick questions and he'll give us, to the best of his ability, some quick answers. Keith, I know you've done some really interesting thing on performance over networks. And when I say performance, I mean things like music. And during the pandemic, I tried to sing a song with somebody on Zoom. What a simple idea. It does not work or it did not work. And it seemed to be a network problem. So can you tell me, what have you done in this area? You know, a lot of the work that we do now is kind of, we've all become biologists.

21:25You know, I used to be a medical reporter. I was at the Wall Street Journal. And for three years, I wrote about science and medicine. And I read every issue of the New England Journal of Medicine. And I wrote about a lot of these medical studies. And I don't envy that world. It's really hard to run an experiment, especially a medical experiment. You have to collect the patients. And it takes years to get the effect size that you're expecting and everything. And at the end, you're using these extraordinarily sophisticated statistics to try and see, does Lipitor help or not help? And even those are the big studies.

21:59And somehow that, you know, the thing about computer science is that we are fueled by a motivation that comes from a confidence that the mystery is always solvable. You know, we're like Columbo. We're always going to find it. Because we have incredible tools in computer science on the problems that we choose to address. Because, you know, for example, in computer science, any mystery you have, we can inspect any part of a computational system without screwing it up. You know, this is not a privilege the biologists have. You can't dissect the frog and, like, keep the frog alive. And it's, you know, it's not a privilege the physicists have.

22:42You can't observe something, you know, and it's quantum mechanics. But it is a privilege we have because of something called Turing completeness. You know, you can always emulate this. This is a very deep result of Alan Turing, the founder of both computer science and arguably of AI, that you can always inspect the system without screwing it up. That gives incredible tools and then incredible confidence. And we can always rerun the system as many times as we want while investigating it. This is, again, not a privilege the astronomers have. You can't see an interesting supernova and say, oh, let's run it again, God.

23:15Keith Winstein:You don't get to reproduce it. So we have the most fun, I think, in this university, the computer scientists, because we have this incredible privilege of these tools on the problems that we address. And that gives incredible motivation. And that's, like, I think why most of us got into this. And you all, the statistics people, are like, we're getting this virus. where like suddenly we're having to become, you know, biologists and astronomers, where a lot of our work becomes more in essence, statistical and slow, where you do something for a long time. You know, I did this work with my students on video streaming, where, you know, this is like you're watching Netflix, and maybe it starts to rebuffer for a while.

23:55And, you know, can we make better algorithms for that? And, you know, so we have our own video streaming website here at Stanford, puffer.stanford.edu, where people watch television, and then we run various algorithms and, you know, but to do that kind of work, you have to run it for a year and collect a lot of data and then analyze it. And maybe it doesn't, and this is just not, it's not that fun. You know, it's not the playfulness and the interactivity and the confidence of being able to play with it and see the result that I think made me happy to be a computer scientist. And so, you know, we had done this work about sort of video and audio over the internet.

24:28And then during the pandemic, I got contacted by this, you know, connected with this colleague, Michael Rao, former guest on this podcast, who's a genius theater person. I mean, you. Yes. You know.

24:39Keith Winstein:Super fun to talk to. Yes. I mean, the humanities faculty at any academic institution have to, there's like a million people applying for one job. So the privilege of being here is like, you know, your colleagues are amazing. And this guy is incredible. And so, you know, he's like, look, I'm trying to teach theater during the pandemic to these students who are trying to do a play over Zoom. And it's like horrible, you know, like there's the delay. They can't hear each other very well. They can't do overlapping dialogue. They can't sing, you know, in unison. as I guess as you discovered, you know, and he says, well, I've seen you've had research on this.

25:07Can we use your research? And I had to explain, sort of embarrassing, that, you know, there's a thing we call research code, which is like code that is not really, it's only written so that you can write the paper. It's not like code that really even works per se, you know, or that anyone else would ever want to use. But, you know, we decided with my doctoral student, then doctoral student, Sajad Filotti, we decided to try and really do it with him and try and build like a bespoke system for actors and musicians to collaborate during the pandemic. So we taught this class in the fall of 2020 for undergrads and grad students about building new kinds of video conferencing systems.

25:46And then we actually did it. Michael and I, it was the main stage production in, I think, March of 2021. We had five actors, Stanford students, and then we have these three New York musicians who were very famous people. But, you know, during the pandemic, they weren't working. So it was an incredible privilege that they were like willing to work with this academic research group. So, you know, they did songs over our system and they, you know, it was a lot of fun to be back in this world where you're the mystery is inside a box and you know that you can solve it. And, you know, a lot of the problems with the Zoom and that kind of thing are not for any interesting academic reason.

26:22It's just kind of like they have a business and they're trying to be on millions of people's computers. And, you know, the Zoom guy, you know, he's a friend of our of us. I mean, I've never met him, but he's I think he's come to our networking class before I used to teach it. And, you know, he's been very candid. He's like, look, we just didn't prioritize kind of software quality. You know, you may remember like Zoom. They were so bad.

26:42Keith Winstein:Yeah, they had a moment. They had a moment and it was an unexpected moment. Remember when they screwed up so badly that Apple had to push an emergency update to macOS to delete Zoom from everyone's computer? Do you remember that? Yeah, this rings a bell, yes. There are a lot of sort of plumbing reasons why the delay in these systems is much, much larger than it needs to be. And to fix that, you really don't have to be a genius. You just kind of have to be a plumber and really get your hands dirty and find wherever the delays are coming from and squeeze that out. And so we did that in this StageCast system, and it was really nice.

27:15I mean, the musicians were telling us, you know, like, oh, my God, like, this is my craft is, you know, performing with people. And I haven't done it for, you know, by that point a year. And now I finally feel like I'm in this. I'm actually part of an ensemble. And the students, they asked us to turn on the system so they could have their party. You know, that was very rewarding. So that was a lot of fun to do. And I learned that we're not really teaching our students how to do this kind of engineering. You know, a lot of it is kind of like you write some code. maybe it's going to train some machine learning classifier and it runs for a while.

27:47And then eventually you look at it and then, I mean, I have this in my own work. You look at it and you sort of squint and like, well, can we say that this worked? And that I think is just less fun. And so I've been trying to...

28:00Keith Winstein:Before you go on, this is so interesting. I just want to ask a couple of things. So somebody might think, okay, if you wanted to have a live performance with musicians in New York, especially famous ones. It's a matter of getting a super duper fast, fat wire that connects. And it's very expensive, but you do it because like it's this unbelievable demonstration. But my understanding is you didn't get a super duper fat, dedicated wire. You were just using the same old internet that all of us use. And can you give us just a little bit more on like what was the magic idea that takes away what we refer to as latency, the delay from when I sing a C and when somebody in New York sings a G so that we can make part of a C chord.

28:44Yeah. So, you know, what you're talking about is the delay between when I sing something and you hear it and when you sing something and I hear it. And that is unrelated to the fatness of the wire. The fatness of the wire controls what we call throughput or data rate or what people sometimes call bandwidth. I mean, everyone calls it bandwidth. Anyway, throughput or data rate. So that's kind of like if I'm at home plate, you know, and I'm throwing something to you. You know, if I throw a bowling ball, that's going to, you know, that's a lot. And if I throw like a, you know, a baseball, yeah, you know, the bowling ball is like fatter, but, you know, they're probably going to get there at the same speed.

29:18Certainly if you like drop them, they're going to get there at the same speed. Right. So having a fatter pipe, more megabits per second does not change the delay. But the other thing you have to understand is that the network is not the problem here. everyone benefits when you blame the network if you are having a bad experience on youtube or zoom or whatever if you say oh man you know verizon is terrible or xfinity is terrible you have to understand everyone wants you to think that way xfinity would love for you to think that way if it means you're going to upgrade your xfinity if you blame them and zoom or chrome any of these companies would be very happy for you not to blame them but in practice it's not really Xfinity's fault.

30:01The delay is probably the same. You know, the delay is mostly for something like Xfinity, like a wired connection. And the delay is mostly just about the speed of light through the wires and that kind of thing. Okay. And so it doesn't, you know, and the speed of light through the wires, it's very fast, you know, like from New York to someone else in New York, you know, we're talking like, you know, it's like the same distance of if you and I were 15 feet apart in a room and just talking to each other, you know, that's the actual communications latency. But what you hear on Zoom is more like 10 times that.

30:33It's more like being like almost half of a football field away. And the reason for that is, I don't know what you want to say. It's bureaucracy.

30:43Keith Winstein:So did you cut through bureaucracy? I think there was elements, because I did read a little bit about it, a little bit of element of kind of predictiveness where you said, I know enough about music and performance that I can kind of guess what the next notes may be? Was there an element of that? That's a follow on. We didn't do that with the musicians. I mean, the truth is that if you look at the way a system like Chrome and Google Meet or Zoom work, there's a Zoom piece of software and it's getting packets in from over the network and they contain audio. And then it puts them into what we call a buffer because it doesn't want to run out of audio to play.

31:18If it starts playing the audio as soon as the packet arrives, then that audio is going to finish maybe before the next packet arrives. And that's going to sound like the robot voice. You've heard that on Zoom.

31:29Keith Winstein:Right. So they don't want that to happen. So they don't play the audio as soon as it arrives. They put it in a receiver side buffer that adds a lot of delay. And then when it gets out of that buffer, it goes into something called the rubber band buffer, the thing that adjusts the time. because if they have too much data in the buffer, they want to play it faster so that they can catch up. That's when you hear that. And we've all heard that too, yes. But that's a separate software component that they license from a different company, and so it needs its own buffer. Then from there, it goes into the operating system's play-out buffer in the sound device, the operating system.

32:03And then from there, it goes into the hardware device buffer. So you end up with everyone. It's different companies making every part of this, and they all add delay, and that's how you end up with 200 milliseconds. seconds. You know, that's like, it's like, you know, a significant fraction of a second. And so if you do it with a bunch of Stanford students and you just build it, you know, to do one thing and, you know, not, we're not trying to have it work on Mac and Windows and, you know, we're trying to do one thing. Right, right, right, right. Then you just have one buffer and every piece of software is on that one buffer.

32:34So you can get, you know, you can get literally quarter millisecond intrinsic latency if you just do it in a good engineering sense.

32:41Keith Winstein:Thank you. That really does answer my question. So you literally – and you said it before but I didn't know what you meant. You said we avoided all the middlemen. I think you said something like that. So you just built up a spoke piece of software that went to the lowest level of the network or some very low level of the network where you had control and you could make a lot of these buffers unnecessary. We had one trick which is maybe interesting which is that Zoom is trying to pick one tradeoff between delay and quality. So if you watch something on Netflix, the delay is huge. job. You know, they filmed that TV show six months ago or whatever, and it's spent a minute in your television before you're actually playing it.

33:17But the audio is perfect. And if you're on Zoom, you know, it's a much smaller delay. The audio is a little bit glitchy. And on a cell phone, you know, it's maybe even more glitchy. So there is a trade-off between how glitchy it's going to be and what the delay is going to be. And so we were able to set that trade-off differently in different situations without sending more packets. So the musicians, for example, are incredibly sensitive to delay. Like we would come on, I mean, these are professional musicians, but we would come on like, and we'd say, try out the new version of the software. It's going to be great.

33:46And they'd play for a little bit and they'd say, no, no, no, no, no. Go back to the git commit you had two weeks ago. It's like, how do you even remember? It was better then. So for them, we gave them the glitchiest audio, but it was absolutely real time. And then for the actors, we gave them, you know, less glitchy audio, but still good enough for them to say the overlapping dialogue. And then the audience, of course, got the perfect audio. And then, you know, in the middle, we had people that were adjusting the levels and the behind the scenes people, this kind of thing. So with the same stream of packets, we could pick different trade-offs between glitchiness and delay.

34:18And so that was the one academic trick.

34:20Keith Winstein:Thank you. That vignette and the idea that the three principals are having very different actual experiences, but all of them well matched to what they need to do their job of producing or listening. Very helpful. I want to make sure that I give you a chance to talk about this new class that you're teaching. Yes. Yeah. I mean, what I learned from this and then from some follow-on work is that, you know, we're not teaching our students this joyful part. The part that I think of as like so central to computer science is the playfulness of it. I mean, computer science is about reasoning about the consequences of procedural reasoning and computation.

34:55And the fact that you can design an automaton in your head and then see it play out at, you know, billions of times per second. I mean, that's fascinating to see so quickly the consequences of a thought. And I don't think we're teaching. I mean, you teach here. I think that's not the kind of playfulness that we are teaching. It's much more about like I'm going to train this thing and it's going to run for a while and I'm going to test it. You know, it's not so interactive. And so I would like to anyway, I'm with some, you know, a bunch of people. I'm starting a new, trying to start a new freshman introduction to computer science and electrical engineering that emphasizes the playfulness and the joy and the interactivity of computation.

35:34And so the idea of the class, it's a CSE class. The idea of the class is about real-time interaction with the real world. And everyone's going to get one of these like toddler xylophones. You've seen these things.

35:43Keith Winstein:I know it so well. Okay, you got kids? Yes. I have grandkids. I've had two or three generations, I've had three generations because I used one, my kids used one, my grandchildren used one. Well, no judgment. Maybe just you like, you know, it could be anyone. They're fun. So, you know, we're going to give everyone one of these xylophones and we're going to talk about, you know, what is sound? You know, it's a continuous pressure wave. It's a continuous function of time. And, you know, why is it these fundamental frequency of these notes? I mean, isn't it amazing that the ancient Greeks and the ancient Chinese came up with basically the same scale?

36:13How do these two ancient societies thousands of miles apart derive the same relationships? And then how would you reason about this information, this audio, in a computer? You might think that, well, it's a continuous wave. It has an infinite amount of information. There's a point at every time. It has a different amplitude, different air pressure. But it was discovered only 100 years ago. After relativity, after quantum mechanics, they discovered that, no, it's possible to take a finite number of samples per second and perfectly capture all the information in this continuous wave, that's pretty mind-blowing.

36:49That's called the Nyquist-Tartley theorem, I think. And so when you have that information in a computer, I want the students to write programs very live, very interactively, that understand the sound and manipulate it. So can you write a program that understands, and these are for freshmen, these are people with no background, can you write a program that understands what note of the xylophone did you just hit in real time? And can we come up with a code that maps kind of the letters of the alphabet to pairs of xylophone notes, you know, A, B, C, et cetera? Can I give you a sentence like, you know, the sky is blue outside and you play it and then your phone or your computer in real time prints out the sky is blue outside in real time, not sort of run it for a day and check and that kind of thing.

37:29You know, this idea that human language can be expressed in bits and talked about, you know, that was quite controversial. You know, Claude Shannon, who's the founder of information theory and hung out with all these Turing and those kinds of people. I don't know about Turing, but those people, you know, he wrote this famous paper in the 40s about information theory. And one of his chapters was about, you know, human language and the information content, the perplexity of human language. And when the famous Soviet mathematician Kolmogorov read that paper, he didn't get that chapter because it was censored by the Soviet translation.

38:03You know, the Russian translators believe that the idea that, you know, that even the human language is quantifiable or that you can talk about the information content of human language quantitatively. That was thought to be contrary to Marxist doctrine. So these are controversial topics, the idea that you can have computation about language and about thought. And so I would love to have this much more playful introduction, joyful introduction to computer science and electrical engineering through this sort of real-time interaction with the real world. And that came from this collaboration with Michael Rao that we did five years ago at this point at the theater.

38:34Keith Winstein:It's a fantastic way for us to end with this hopeful note, no pun intended, that this is the way we're going to introduce the next generation of computer science to their craft. And it's real time. It's playful. And it may be not what people are expecting at this time in the future of computer science. So it's great to hear. Before we end, I'm wondering if we can do the future in a minute segment where I ask you a few rapid fire questions and you give me as as is possible a short, sweet answer. I'll do my best. Here we go. What is one thing that gives you the most hope about the future? I mean, I think many of our students really do have an optimism about their ability to make a positive difference.

39:19And many of our students are just incredibly impressive in both their ability to get things done, but also the dreams that they have and the hope that they have about the future. And I think that's very fueling.

39:31Keith Winstein:What's one thing you want people to walk away from this episode remembering? I mean, I think that truth matters and that the computer scientists are trying at least to find a way to capture that. Aside from money, what is the one thing you need to succeed in your research? Oh, I mean, fantastic, you know, doctoral students. If all goes well, what does the future look like? You know, I mean, I think the things that I prize and I think things that are a core to computer science is this idea of independence of thought. So, you know, the idea that a college student in Finland can make the operating system that turns out to, you know, take over the world and a guy in Switzerland can make the thing that, you know, we all communicate over the World Wide Web and, you know, the two bike mechanics in Ohio can make the airplane.

40:12this independence of thought and distribution of where innovation comes from. I mean, most innovate, I know this podcast is just Stanford people, but most innovation, if you look at it, does not come from Stanford and MIT and Berkeley, right? Most of it comes from nobodies. Most of the most significant innovations in the world come from not where it was supposed to come from. And for that to remain possible, there needs to be this distribution of people near the frontiers of innovation, the bike mechanics or the research programmers, you know, all over the place so that some people can take the step, you know, and it's never who you think it's going to be to innovate.

40:46Keith Winstein:And finally, if you were starting over again and you needed to get your certification or your degree in a different discipline, what would it be? I always wanted to be one of those people that was fluent in Latin. Very, you know, if you read like the secret history, I was very jealous of that world. Thanks to Keith Winstein. That was the future of network systems. Thank you for listening to the future of everything. Don't forget, We have a huge catalog of back episodes and you can listen to the future of just about anything. Also, please rate and review the podcast. Your ratings and reviews, we read them, we respond to them, and they help us grow the community.

41:20Keith Winstein:So please do it. If we deserve a five, give it to us. Otherwise, give us whatever we deserve. Thanks very much. You can follow me on many social media apps such as LinkedIn, Threads, Blue Sky and Mastodon, where I'm at Russ B. Altman or at R.B. Altman. You can also follow the Stanford School of Engineering at Stanford School of Engineering or at Stanford ENG.

41:48Keith Winstein:If you'd like to ask a question about this episode or a previous episode, please email us a written question or a voice memo question. We might feature it in a future episode. You can send it to thefutureofeverything at stanford.edu. All one word, thefutureofeverything. No spaces, no underscores, no dashes. Thefutureofeverything at stanford.edu. Thanks again for tuning in. We hope you're enjoying the podcast.