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Bruin to Bruin: Leonard Kleinrock

Photo credit: Helen Quach

By Marty Johnson

April 10, 2024 9:18 p.m.

Leonard Kleinrock is considered one of the founding fathers of the internet, and he has served on the UCLA faculty for over 60 years. Podcasts contributor Marty Johnson sits down with Professor Kleinrock to discuss his life, career, and advice he has for UCLA students.

Marty Johnson: Hello, and welcome to Bruin Bruin, our new podcast series where we sit down with trailblazing members of the UCLA community. My name is Marty Johnson, and I’m a podcast contributor at the Daily Bruin. Today, we are very lucky. We’re here with distinguished computer scientist Professor Len Kleinrock, often credited as one of the founding fathers of the internet. His groundbreaking work in the 1960s laid the foundation for modern computer networking, and he has been a valued part of the UCLA faculty for over 60 years. Professor Kleinrock, welcome to the show, and thanks for joining us.

Leonard Kleinrock: Thank you, Marty. It’s a pleasure to be here.

MJ: So let’s get right into it. What first piqued your interest in science and engineering?

LK: It was a long time ago. I was reading a Superman comic. Having been based in New York, I did the things that kids do—sports, baseball, puzzles, gadgets, and comic books. And this is about when I was in first grade, I was reading a Superman comic. And in the centerfold of the Superman comic was a description of something called a crystal radio. And what fascinated me about that was, it would cost nothing. I could build it out of parts I could find around the house, and I get free music in my ears. So I figured, why not try? Well, one of the things you needed was an empty toilet paper roll, and I could find that, then I needed some wire, and I could find that in the streets. And then I needed a crystal. And they said, you can make that out of your father’s old razor blade, and a piece of pencil lead. And one other thing I needed was an earphone. And I didn’t have one. But I knew in the candy store down the street, there was a telephone booth. And in a telephone booth was a telephone with a handset. And I knew from experience, you could unscrew the earpiece, and it would drop out in your hand. So I stole the damn thing. The last piece I needed was something called a variable capacitor, whatever that was. And I know I couldn’t find that in the streets of Manhattan where I was living. So my mother took me on the subway down to Canal Street, where the surplus electronics stores were. And I walked up to the first proprietor, and I banged my fist on the table, and I said, “I need a variable capacitor.” And he said, “What size?” and it totally blew my cover. So I explained why I wanted it. He knew exactly what I needed. He sold it to my mother for a nickel, took it home, wired it up, and I could hear music. I could dial different stations. And this was magic. And I figured I would understand how this is going on, what’s going on. Yeah, wow. So I started monkeying around with broken-down radios, I would cannibalize them, started reading about it, went to the library, got some books, learned how to basically build radios. And I did that throughout my youth, and never became a ham radio operator. Because I couldn’t afford the rig. We were not at all wealthy; we weren’t quite poor. So by the time I got ready to go to high school, I was fortunate enough to be accepted to the Bronx High School of Science and Mathematics. It was the best high school around the world at the time. And I was basically headed toward a career in electrical engineering. So I took the radio courses there and all the science courses. And that’s what got me started toward science and engineering. It was that six-year-old crystal radio set.

MJ: Awesome. And at that point in your life, did you imagine your future as a researcher, or were you thinking more about getting into private industry?

LK: I had no thoughts about where this was going. I just liked the challenge, the puzzle, the building, making things work. And I wasn’t really committed to going into engineering. I liked to keep my options open. So I really didn’t decide to go into electrical engineering until I went into college. I enrolled as an electrical engineering student by then. But prior to that, I liked to keep the options open. Little did I know it was ordained. I was going to head to W.E. And that’s what I did.

MJ: Awesome. And you mentioned that you were born in New York. Can you tell me a bit about what that was like, growing up in the 1930s and 40s, in New York City, the Great Depression, pre-World War Two, must have been an amazing part of history.

LK: It was an amazing young man’s life. We were poor. I was born in Harlem, in the sense that my hospital was in Harlem. But we were living in a place called Washington Heights, up near the George Washington Bridge, on the wrong side of the tracks. And so there were gangs and hoodlums, and the streets were dangerous but fun. You’d go there and find anybody to play with, you know, stickball, punchball, ringolevio, kick the can, etc. So it was a very rich environment. But the thing I found most fascinating was the education. The elementary school that I went to was terrific. It had smart kids, kids from all over, and a lot of challenges. But it allowed me to have some kind of orderly structure, which I didn’t have in my home life. I was sort of a wild kid. My poor mother, they wouldn’t let her shop in certain stores because I would make things. They told her to take her business elsewhere. So I was pretty unruly. But when I got to elementary school, around the time I started doing the radio, the crystal radio, I realized this required structure, and there were rules, and there were consequences. So I pretty much straightened out. And I enjoyed elementary school a lot, had great classmates, good challenges, and I thrived there. Junior High School, again in New York City, was another story. That was Hell’s Kitchen. I mean, kids from all over the city came to these central junior high schools. And it was wild. But as I said, the streets were amazing. You could find anything you wanted to go out, just go out and play, you find things you need, you find it on the street, I used to fish for pennies, and nickels down the subway gratings with a long string, some gum, which people would drop down. It was exciting, challenging, and full of engagement. Never was never dull. I saw somebody commit suicide. I saw some kid get stomped to death. I mean, this is the environment of New York at the time. But as you say, I didn’t feel depressed because everybody was pretty poor. And then when World War Two broke out, you just swept up with enthusiasm and patriotism. I mean, there’s a lot of propaganda. And you know, the government was busy doing that. But I remember seeing P-38 fighter planes flying over the city. Proud to be in New York, it was, in my mind, the biggest city and the best city in the world. And couldn’t imagine being anywhere else.

MJ: Do you think modern-day New York has kind of lost some of that, you know, special ingredients that it has?

LK: Only slightly. It’s still a place full of vim and vigor, if you will. It’s a place where it’s a no-nonsense place. You know, there’s a lot of politeness around the country. People are very sweet to you and kind. In New York, you talk to somebody, and it’s just “Get out of here. What are you kidding me?” You know, it’s very straightforward. You don’t get away with things. And there’s a lot of bluffing as well. A lot of posturing. And you walk real fast around the streets in New York. It’s not lolling around. You just move, and it’s healthy. And playing softball and stickball was invigorating. I joined the swimming team in Bronx Science. And that was great. But the city still has that spirit, that enthusiasm. It’s a mixed city full of immigrants, everywhere as it was then. As you say, World War Two occurred. And we had people coming in from Europe, in my class, immigrant kids, and they did look weird. But they were striving. They were dressed funny. But you get used to it and you embrace them very quickly. So it was a really great melting pot. It wasn’t a protected environment at all. And it was real.

MJ: Were the type of kids you were hanging out with, like you, share your similar interests in science, or, you know, even hobbies? Or were they just very diverse and different?

LK: So the elementary school I went to had about six or seven classes in the same grade. And they say, the number one class were the smartest students all the way down to the kids who weren’t getting such great grades. I was typically in the one class and my colleagues were small kids who were engaged and not unruly and not you know, I always got a C or D in conduct. And in penmanship, by the way. And in history and geography, but in math and science, great. And so I was with a lot of kids with my interest in education. And the softball team I was a member of was called the Avengers. It was from all the classes and was a mixed group. And then we had some less academic kids, and somewhat rougher, but it was a very good experience. Also the one before I even got to elementary school I was living on on Amsterdam Avenue, which as I say, is the wrong side of Broadway. I’ve been to Washington Heights. If you’re on the east side of Broadway, that’s the bad side, the west side is good. I was on the east side. And I was one of two Jewish kids in the neighborhood, which was across the street from a Catholic, parochial school. And they didn’t like Jewish kids. And so I spent a lot of my time being chased fighting, and never joined the gang, the gang, the Jewish with a lot of other gangs around. And that basically, it colored some of my concern about being out on the streets alone. And so I couldn’t wait to become a teenager where that would be less prevalent. But to answer your question, it was a mix of kids, but mostly my time in school was with kids who were like myself interested in good education and doing the homework, etc.

MJ: Tell me a bit more about your family. Did you have any siblings? How were your parents, things like that?

LK: So both of my parents were immigrants. My father, they were both born in what is well, my mother was born in what is now Poland. My dad was born in Austria, then they were both born in Austria. My mother’s location is now Poland. My father’s location is now in Western Ukraine. And my mother came over here. My mother came over when she was almost five years old. It was a difficult journey. Her mother had come over here before, and left her with her siblings. And by the time she arrived, and she met her mother, she said, “You’re not my mother. That woman is,” and that was her older sister. But when she was young enough, she adapted very quickly. My father came over when he was 16. And he lived as an orphan basically, in World War One. When he was nine years old, his father came to him in 1914. And he said, “Son, they’ve taken me to the army.” I mean, obviously, he and he never did. And pretty soon he was living with his uncle. He was taken off to war. And the uncle arranged for a neighbor to take care of my father. Two months later, a neighbor started taking care of my father who knocked out one of the kids of that family, and they threw him out in the street. So he was literally a waif in World War One. What have been whatever army soldiers were in town that day. And with a bunch of other kids, so he had a rough time, you know, finding food, finding shelter. And in 1921, he came over. So what did he do? He started, he went to night school and worked as a grocer, a grocery clerk. And then he stopped night school. And he eventually was able to work with a partner at a small grocery store. So he was a grocer. Innenstadt I think was the one. So my father was a grocer. And he got his own store doing moderately well, but during the war, he did very well. The food stores were doing well during the war. And however, he got very ill, and just around 1945 He contracted a serious case of asthma. And he was unable to work for years after that. We’re about 12 minutes in, I guess you could say. So my father got very ill when he was 9045. He was 40 years old, and he couldn’t work. So he had to sell the store at a bargain price. And we were in bad straits at the time. I started working. All through high school, I was working three to four hours a day and all weekend as an usher in a movie theater. I am also going back a bit as a young man who went to Hebrew school. So it was four o’clock every day when I was in Hebrew school. And that limited the amount of external enjoyment I could have. And soon after that, I was busy working as an ASHA so I put all the money into the house. I kept none of it because I had a sister. She’s a year and a half, almost two years older than me. Two years and two months older than me. And she’s still alive. She and I never got very close. What are my earliest childhood memories is walking over to her with a hammer and hitting her in the head. And she’d still still point to the three stitches she got on a fire. That’s the period when it’s a really bad wild kid on structures I told you. So my parents are great. My biggest gift my mother gave me besides pushing for education, and love and warmth, where she let me do what I needed to do. She let me build things in a living room. Behind you know, building radios is a messy job, you got a soldering iron, you got an old chassis, dusty, dirty, and she let me store it all behind the sofa in the living room. She never bothered me about that. She let me build model airplanes. So she gave me the freedom to do what I wanted. My dad always pushed education very hard. And I’d come home with a 95. He asked me for the other five points. So it was a good lesson. Oh, I have been practicing violin for four years. And I can’t carry a tune. So you can imagine the way they suffered and my poor violin practice. But, you know, they gave me guidance and direction, and sent me to Hebrew school. made me work and basically gave me music lessons. And so early on, I joined the Boy Scouts. And the reason I joined the Boy Scouts is because I was raised as you said in New York City in New York City is a concrete jungle. There were almost no trees. And the thing I wanted to be a very young man was one of two characters, either Tarzan or an Indian. I mean, they lived life. Just imagine, right? Oh shoot a bow and arrow swinging the tree swim. So I wanted to get out in the outdoors. And the Boy Scouts offered me that opportunity. So once I joined, I could then go camping out in the Adirondacks. It was wonderful. I really enjoyed it. And I rose through Boy Scouts to become a patrol leader. And then what’s called a senior patrol leader while you’re in charge of all the patrols during the meetings. And the thing that gave me a real sense of leadership and responsibility. And I’ve always stood the ranks of you know the ranks in the boy scouts tenderfoot second class first class, then you become a star scout. Scout, you have to get five merit badges. And when I got to steal a scout my this sounded a little strange now. It’s okay, now one of the sides goes out. I think so. That’s all right. It doesn’t affect the recording. Okay. Yeah. Okay. So when I became a star Scout, my Scoutmaster said to me that you could become the first Eagle Scout in this troop. Now, to become an Eagle Scout was sort of way outside my grasp. I mean, I didn’t get 21 merit badges. And in those days, it was more difficult than it is today. One of the merit badges you had to get was something called Bird study. You had to identify no and see 40 different birds. Now, in my mind, there are only three birds in New York City. Sparrow, the pigeon and this eagle. I was dead wrong because Central Park had a wonderful mix of birds but So I went to scout camp, and I got 13 merit badges in two weeks, which is unheard of when I came home. My mother literally didn’t recognize me. What did I buy her? I was about as thin as a rail. But then I had to go back to get the boot study. And so the point is I achieved this eagle scout. And when I get to give new messages for young men and women, I’m going to use that as an example, where what you need to do is to be willing to reach beyond your grasp. Don’t make it easy for you to make something that’s going to challenge you. And if you succeed, you may fail. But if you succeed, you can recognize you can do that. And it gives you the courage, the inspiration, that confidence, you can repeat that. And that’s an important lesson for young people. I can’t emphasize this enough, but it was in the boy scouts. And through high school.

MJ: So after high school, you went to New York City College and then eventually MIT, walk me through kind of the decision making behind going there and what ultimately led you to pursuing your PhD at MIT?

LK: That’s an excellent question, by the way. So I want to go to college, of course I was a senior in high school. And I voted away, couldn’t afford to go tuition etc. was out of the question. I was bringing money home for my parents to live on. But I voted away to every chamber commerce Chamber of Commerce in the United States asking what kinds of scholarships the average for your universities and colleges and I got a number back. Trouble is they could provide enough to cover travel, living expenses, and tuition. So I chose to do what was ordained anyway, to go to CCNY, City College of New York, which was an excellent school then still is. You know that CCNY has graduated more Nobel laureates than any other university in the country. And it’s still the case, and mostly from the time just before and while I was a student at any rate, so I’m set to go to CCNY enrolled as an electrical engineering student. But that summer, toward the end of that summer, my father took me to downtown New York to visit a cousin of his who had an electronics shop. It was an industrial electronics shop. He was building photoelectric devices, from scratch and selling them to places I wanted to count cereal boxes, and watch how high level the rocks work, etc. So it took me down there. And it was fascinating. These people were building electronics from scratch, designing them with real engineers. And my cousin offered me a job. And I said, Well, look, I’m set to go to college. But my father urged me to take the job. And so I did, and I went to night school. Like your father. Yeah, but he dropped out because the pressure was too hard. Now here I was. It was called Eve, it was called School of General Studies, even its action. But didn’t get a full degree at night, a full degree without ever attending a daytime school session, which is not possible almost anywhere else in the country right now. And that’s a shame. Because kids need to be able to be able to work and get a degree. So I started out in the evening session now. Ask yourself who goes to evening sessions for an electrical engineering degree? The answer is crazies, dropouts, very dedicated poor kids. And Gi is coming back from World War Two. Who it’s been who had matured and recognized how important education was. At work, I was with a bunch of engineers, many of them G eyes, who were brilliant, very talented. And I got a very interesting experience as a young man, what life was about, what direction to take, what lessons to take, and how to avoid some of the really difficult situations like the kids who are dropping out and just horsing around.

At night, I remember taking a calculus class on the first floor of a wonderful building called Shepard Hill City College where there was a beautiful campus. It’s Gothic style, it couldn’t be more beautiful. But there are basically no dormitories. It’s all a commuter school, except for the GI guys who had a dormitory when they came back and they loved it anyway, one night. In the summer I was taking a calculus class And the window was open because it was really hot. In the middle of the class, some gangs came by and they threw buckets of water into the class. And my calculus book, I have it here. If you open up to the white page, you’ll see it’s all wrinkled and curls on where the water came in. That’s the kind of environment I was in. But, you know, a lot of the kids were very dedicated, some more horsing around, as I say, and my faculty, the TPP, the faculty were teaching us, they two were working during the day as engineers, and came to teach us at night. They were theoretically strong. But they were practically experienced. They knew what this was about. And I remember very well, one day my professor came in. And he said, See, this is called a transistor. And he said, he basically just came up with germanium. And silicon Dramatis at times, says it is a better thermometer than it is an amplifier, because it’s very sensitive to heat. And it’ll change his characteristics according to the temperature. And here’s how to fix that. In today’s session, the professor would have said, See this transistor, he outperforms it without the experience, the practical side. So what I’m trying to paint you as a picture that my own growing up was built, both by practical hands-on applications, and the theoretical and straining books that I read. The teachers I had that mix of understanding why you’re doing what you’re doing, and the theory behind it as to why it’s behaving the way it is, is it a wonderful combination. And too often you have scientists who are good at one, but not the other. And that that combination is a real winning combination. And I like to phrase that as follows. engineers often will look at a device or a system and try to understand how it works. They’ll build it, they’ll design it, they’ll break it, they’ll repair it, they’ll bang it, they’ll experiment with it, you know, how does this thing work? Scientists say, why does it work that way? What is the physics and the mathematics behind the way it operates? The practical side theoretical side, but to have that combination is enormously powerful. And getting ahead of it, the professor who was on my PhD committee, a gentleman named Claude Shannon, who I hope some of the people listening to this podcast recognize, was the father of information theory, communication theory. He had that combination. He could take apart a differential gear with a Swiss army knife, and point to the most esoteric mathematics behind some of the things he was studying. So that combination is very important. At any rate, us. So I went to City College, it took me five and a half years, I went to three quarter time every summer, and I got the degree in five interviews. During the day, young men and women took four and a half years. So it was a really intense program. But when I study, I mean, I’m working all day, get to school in the evening, classes finish at 10: 30 or 11. And then I’d go to something called House plan, which substituted as a poor substitute what people call fraternities these days was a club and a brownstone down the street. And you go with a bunch of guys in your house around you. And then you have dances with the girls versions of these things of House plan. And I get on puppy, midnight, 1230. Wake up at seven. So when the hell do you study? And the answer is you do it on the subway down to work back to school and back home. And so I would take an eight and a half by 11 piece of paper, folded in half fold in half again to have eight sides in which I would divide all the important formulas and things I needed to know. And on the subway, I would study with this thing, right but three inches from my face, because he didn’t have any mobile when the subways were always standing. So those study habits worked at City College and I was first in my class day and evening I was president of my class did really well. And that story will come back to haunt us in just a minute. So as it came time to graduate, I decided yes, I did want to get a master’s degree, but only a master’s degree. And I was told one day that there’d be somebody coming from MIT to describe a scholarship program for a master’s degree at MIT. He was coming in at 4pm. So I took off early that day and made up for another day. And I came to listen to this guy. And he was from a place called MIT Lincoln Laboratory. That’s a research laboratory affiliated with MIT. They will often do this magnificent program, the staff associate program. They pay your tuition. They pay you as a research assistant. In the summers, you would work at Lincoln Laboratory as a full time employee, among some great researchers. And so it was enough to live on, not wealthy but strong enough. So he said, If you want to apply to this program, see the professor in the back of the room when I’m done with the lecture. I finished and went to the back of the room. And I said, I’d like an application. Guy, yes, my name, I told him. He said, I don’t recognize you. He’s a professor. So no, you wouldn’t go to night school, I go to evening session, he says, evening session, get the hell out here. Son of God, he wouldn’t give me an application. I still remember this guy’s name. And I won’t tell you on the radio, but I’ll tell you later, it suited him. At any rate, I voted away to Lincoln Lab and I got the application I got accepted. And I went off to MIT. Now, MIT is a frightening place. If you can picture, you know, this big dome, which is the icon. When you get there, and you look at that dome, it is awe inspiring, and frightening. Because it collects the world’s best students. And you know, your colleagues, your classmates are going to be really excellent, you better be good. And I was a research assistant, in a laboratory in the servo mechanisms laboratory. And my supervisor said, there’s a particular course you need to take. It’s called transitions in linear systems. I have the book behind me. It’s written by Murray Gardner and John Barnes. Murray Gardner was the fellow professor teaching there. Turns out John Barnes was a professor here at UCLA. And I was told, it would behoove you to do well in this course, because this course is what separates the men from the boys. Fine, started taking the course God was teaching. And the first midterm comes along, and I get a 5050. It just blew my mind. I mean, it was disgraceful. I mean, I went home saying you can get this. And so I realized that my study habits were not good enough. I couldn’t just have a piece of paper and just look at the notes and be done. So I, so this was a wake up call, a real wake up call. And you have two responses to a wake up call. Either you go sit in the corner and cry and get defeated. Or you take it as a challenge, you do something about it. And so I changed my study habits and started studying really hard. And I got an A in the course that’s lesson number two. A wake up call can be very useful, listen to it, and make a change if you need to. So I went through my master’s degree. And the program for Lincoln Lab was, you’d go to some semesters as a research assistant, the third semester as a full time student with no research assistant responsibilities getting paid. In the summer, as you work in Lincoln Lab in the fourth semester, and you had finished your thesis, you had to do a master’s thesis. By the end of the third semester, fourth semester, you’d have one or maybe two courses left, and you would commute from Lincoln Lab, which is 20 miles away and the shuttle. And I was programmed to do that. And in the summer, before that last semester, my supervisor of my master’s thesis was the head of the server, server mechanisms lab. came to me and said, Len, you want to go on for PhD. I said, I don’t want a PhD. I have a child coming this summer, scheduled for when I am going to be done working. Luckily, I’ve got a full time salary. In fact, I got married as an undergraduate in New York City College. I’m not suggesting anybody do that, by the way, it was too early. But I was married and we had a child plan. And sure enough, my son was born in August of 1950. I told Professor ranch’s the head of the server the next day and my supervisor said no, I don’t want to mess it up. PhD said you gotta get it, I really don’t want it. He said he gotta get it. So I acquiesced. But I said two conditions for myself. Condition number one is I wanted to have as my PhD supervisor, the best professor I knew at MIT. And that was the same claw challenge that I mentioned. And second, I don’t want to do a piddly little piece of work. If I’m going to do some research, I want to have some impact. I’m not going to spend four years just you know Doing something, because I had a great research position at Lincoln Lab ready to take on a wonderful private office doing research that could be better among some great scientists. So I decided to go ahead. So that summer I called Claude Shannon, and I said, I’d like to work for you. He said, come on out and see me in my home. So he invited me to his home, which is amazing, this giant of a man. And I went there, we had a very good discussion. And he agreed to have me work with him. But he wanted me to work on a chess playing program. And it was just beginning to develop a chess playing program. And I could play chess, but I’m not a great chess player. But he handed me this book by a guy named Fred Reinfeld, who was the author of many books on chess at the time. And this book was entitled 1000 and 1 billion chess sacrifices and moves on every page was a position, black and white, in the middle game, and it said, black as a billion sequence, go find it. White has a billion sequences, go find it. These were tough. And it was in the middle game. Shannon wants to operate in the middle game with strategies. So Shannon said, but in the back of the book of the answers, and I want you to look at that I want you to categorize for example, find out what is the most common move, first move of a Boolean sequence check. Exactly, yeah, or capture both. Because what limits what the enemy can do? And went on and on you exactly right. So we took those rules, and we put it into the bug, and we were writing, and it worked very well. And then I realized, this is not what I want to do for my PhD, I’m not good enough. So I started looking around and at MIT, and at Lincoln Lab, I was surrounded by computers. And in particular, there was a, we had one of the first transistors computers, it was called TX. Two. Earlier, there was a TX zero, which is now at MIT campus, and TX. Two were at MIT Lincoln. And the people who had built this machine wanted to be able to use both, but they were 20 miles away, and there was no way they could communicate. And I was surrounded by other computers as well. I said, Ah, computers are eventually gonna have to talk to each other. And there’s no network that will allow that to happen efficiently. So he was a new problem, which no one had been working on before. If I could solve it, we would have an impact. And I had an approach, I saw an approach to think about what kind of a network could support computer to computer communication. And so I started doing that. So that’s the end of the story of how I got CCNY and MIT.

MJ: So now this was, I think you’re about to explain it right around the time, you were inventing the underlying technology that would eventually make you one of the founders of the internet. So can you describe a little bit more about that process? What exactly was your contribution?

LK: Sure. So as I said, I had an approach to this. The reason computers couldn’t use networks that already existed, which was the biggest network at the time in the world, the telephone network, was the big honcho. But the telephone network had a way of sending information through its network, which was inadequate for computers. And that was the following. In those days, if I went to telephone you, there’d be a sequence of channels of links that would connect us. And you in our conversation, that whole sequence was dedicated to our conversation. And if I paused or took a cup of coffee, there would be silence. And those links will be wasted. But it turns out in speech, you are silent about 1/3 of the time. And that’s acceptable. It wasn’t too costly. But with data communications, it turns out, it’s very bursty, you send the burst of data and then you quiet for a long time. Turns out you are silent more than 99% of the time. And data communication links are expensive. So we couldn’t afford to dedicate a whole sequence of channels for a session where most of the time was idle. So I realized the thing we have to do is, is what’s called dynamic resource allocation. Which means if I want to send something, say I want to send a block of data, launch it into the network and goal on the first hop along that path. And once it goes at first rapid releases that channel, somebody else can use it and make the next hop. So it takes channels along the way only as it’s needed. Which means the resource we’re going to share with the channel and it’s dynamically allocated you only get to use it when you’re there and needed as opposed to if you’re not there. And the model for that is believing that is queueing theory. Think of a queue in a bakery store. And as a clerk serves the customers, that clerk is not going to ask you a customer to wait, while someone down the street is making their way to the bakery store, they’ll serve you next, they’ll serve whenever there’s work to be done in a dynamic fashion. So that idea of dynamic resource allocation was the key to designing a network which would allow the same thing to happen for data communications. Now, this idea was not a new idea. We already had at the time that the basically the flavor of the month in those days was time shared computers, and a time shared computer. Or before time sharing. Let me take you way back the first, the very first computers were big machines, and people would sign up to use them for hours at a time, I would sign up for a machine at Lincoln lived at the expo, for example, from midnight to 7am. And what was I do most of that time trying to write a program. And most of the time, the program wouldn’t work. And I scratched my what’s wrong, what’s going on here. And most of the time I was doing nothing was very efficient for me, but terribly inefficient for the computer. As the computers got bigger, they became more expensive. They couldn’t afford to let the machine be used so inefficiently. So they threw the user out of the computer room. And say, what you’re going to do is you’re going to take a deck of cards, one deck of cards, give it to an operator, and the operator will feed it into the machine. So they’d have a huge queue of jobs to be done. We’ll take two days to get the result come back. And typically would say, instead of a pile of output, you get some of the syntax error a job aborted. So days later, you try it again, this was very inefficient. So then they decided to use them back into the computer room and said, Look, you submit a job, we’ll run it. As soon as you’re done, somebody else can use the computer. So many people put in requests at the same time. And they served in some fashion, when somebody’s finished, the next guy grabs it. So they were using the computer in a dynamic shared way. You don’t keep it when you don’t need it. Same idea for network and I said, let’s put that into a network. And in those days it was called message switching. So you’re throwing a message goes hop, hop, hop to the network, grabbing and releasing the channel to the time. And the question is with those messages. When they bumped into a channel that was visited for McHugh See, I don’t understand queueing theory in the sand. How long would the queues get with the message to fall on the floor? And I was able to show if you designed it right. This is very efficient. The response time was small, the challenge would be used efficiently. And you could say exactly how much capacity each channel should have dependent upon the traffic matrix. So I modeled the system, I analyzed it, and then optimized it. And then I simulated because in my analysis, I had to make an assumption, an assumption which I knew was wrong. But I knew it didn’t impact the result. And I was able to simulate both with and without the assumption to show in fact, that the assumption was excellent and allowed the analysis to go through. So I put down this whole theory of the mathematical model and description of computer networks.

MJ: At that point, were you aware how significant your research would be?

LK: No, not at all. I knew I had to do a good job in modeling, analysis and optimization, because I was at MIT with professors that expected that and I knew I had to prove it. So at Lincoln Lab, I could run these long simulations to prove that it worked. And I had to solve other issues. So what I did some additional work in queueing theory on priority queuing theory as part of the research, because I realized the order in which the messages were served might affect the performance, long messages, short messages, and I created a model whereby you would take a long message and chop it up into little pieces and serve them one at a time. Well, that was really packetized in messages into smaller fixed length packets, and it was able to show that there was a great advantage to doing that. Short messages could get through the network quickly as opposed to long messages. What you don’t want in the network is for a small message to get behind the long message and be waiting while that long message is being transmitted. The short message can get in front of the big one and not bother the big one very much With device versus bed, so you had it made. So you could design a package decision. Anyway, I did all of that.

MJ: Awesome. And can you describe the process where we went from that research to where we are today, and how significant the internet is? Sure.

LK: Lincoln Lab wanted me to make my thesis into a book. And I did, and it came out in 1964. But I graduated, I finished my thesis on December 62. I got my degree in June of 63. And I immediately accepted a faculty position here at UCLA. And starting in July of 63. So there’s great research, and I wanted to see it implemented, but nobody cared. AT and T said, it wouldn’t work. And even if it did work we wanted and they wanted nothing to do with it. So there was resistance in industry. And what was I to do except continue to publish papers and develop PhD students to continue to study other aspects of networking. There was other research going on down the street here at RAND Corporation, Paul Baron was also looking at packet networks. He was more interested in architecture. I was interested in mathematical theory and performance. But he made the same point ATT said, we’re not interested in this. Happily, there was an event in 1957 that would set the stage for you for your question. In October 57, the Russians beat us into space. And they launched Sputnik, the first Earth orbiting satellite. And it caught the United States with our pants down. Then President Eisenhower said, this should never happen again. We have lost primacy in science, technology, engineering and math. So he created in the Department of Defense, something called the Advanced Research Projects Agency arpa. And its role was basically to lift the United States capability up in science and engineering and mathematics. So we funded research and education across the country, in high schools in universities and research labs, in industry research labs and research labs and universities, and began to fund research. In 1962, within ARPA, they had a special office devoted to supporting Computer Research. So they started supporting computers, researchers across the country. By the time 1966 came around, they had been funding great universities, MIT, Utah, UCLA, University of Illinois, Berkeley, and great Centers of Excellence had been created. And every time they went to a new researcher, say they will go to a great YouTube channel, say Marvin Minsky is an example Marvin Minsky is one of the founders of artificial intelligence. He got him off and said, Marvin, here’s a pile of money. Go do something great. failures, Okay, shoot for the moon. We know you’re great scientists. You’re going to have this money for a long time, go do it. And we’re not going to bother you. What would you do and just go for it? Every time they did that, by 1966, they went to a new researcher and said, here’s a pile of money. Go do some research. Okay. Buy me a computer and the opposite. Yeah, we’ll buy you a computer. But then that researcher would say look at MIT, they have great artificial intelligence. And University of Illinois, they have great high performance computing, University of Utah, great graphics. I knew the researcher I wanted in my lab. On the other hand, we can’t afford to give everybody everything. But if you knew the researcher was in the network, you could reach across the network, log on to the machine in Utah, and do the graphics there. So the idea of a network came into the mind of ARPA, suddenly, a well founded organization needed a network. And they were ready to do it. So he knew my dream was going to come true. You know, I had the technology, the research. So they started putting off and started putting together a group. And the man they put in charge of this network, which is going to be called the ARPANET, was a classmate of mine at MIT and officemate. In fact, he was also a staff associate at Lincoln Lab, a fella named Larry Roberts. They brought him in to lead the effort within arpa. And he brought me in early on to help them design and think about people but others as well to put together a plan. Eventually, my plan became a request for proposal sent out to industry to build what we then called a packet switch, and that contract was awarded in December 68, to a company called Bolt Beranek and Newman, a Cambridge Massachusetts research firm. And it was selected that UCLA would become the first node on that network. Because I had the mathematics, the understanding of the performance evaluation, and some of my students. So we were scheduled to get our first switch, first packet, which we call that a router these days. And the name of that machine was called an interface message processor, Imp and imp. And it was scheduled to come in on the Labor Day weekend of 1969, eight months after BBN got the contract. So BBN was furiously trying to put together the job, their job was to take a state of the art mini computer, change the hardware and software to implement the specification that we had sent out to make it into a packet switch. And sure enough, in eight months, they delivered that switch, it was running, it was on time, and it was on budget. You could never do that today. This is a new technology that uses new applications. And that machine is still here at UCLA, the first of those switches, wow.

MJ: Did you ever consider using your research for more entrepreneurial ideas or a business as opposed to, you know, research?

LK: It was not early in my mind. But in 1975 while I started teaching, the performance evaluation, the tools, the queueing theory, and in 1975 published a book on queueing theory. The theory and 76 are published in a book as applications of queueing theory, namely all about networking. So my wife and I decided, look, we have to get this word out to the industry. You know, nobody knows about the technology. So we decided that I would do a three day seminar across the country, explaining the theory, the performance evaluation, and the application implementation. And so we formed a company called Technology Transfer Institute. And I did this across the country. It was successful. I decided to have others of my peers who were excellent in their field give three day seminars on other scientific engineering fields like timesharing, like graphics, communication theory, computer performance, evaluation, etc. And so I formed this company, and that company still exists today. I sold it in 2012. But it grew and grew. We’re running hundreds seminars, but never never did. I leave my position here at UCLA. I let others run it. That’s my desire. My goal in life was to be a professor, a teacher, doing research and teaching young men and women and graduate students how to do research. But I did then in 19, before the Technology Transfer Institute, in October 68, I formed a company called link a big corporation with two other colleagues and other colleagues here at UCLA. One of them was Andy Andrew flutterby. Another was a professor from MIT called Irwin Jacobs. And we formed a liquid cooperation to do consulting on communication theory and networking. In the spring of 1969, my home by the way, was the first office. My garage was the first classified facility. We had a safe there. Then we moved westward. Again, I would spend some time there. Toward the end of the beginning of the summer of 1969, I was getting ready to make UCLA the first note of the ARPANET. So I told Irwin, Andy, I’m not going to be able to work this summer. They said Fine, come back in the form I did. Meanwhile, they decided to move the company down to La Jolla, California near San Diego. They quit their positions on faculty, so I decided not to go. I want to remain a faculty member. And that company eventually got sold to a company called Macomb. Owen and Andy took the proceeds and I got some of the proceeds. Well, they took the profits and they formed a company that you know, a company called Qualcomm. Wow, major company. So that was Lincoln. That was the beginning of that endeavor.

MJ: That’s amazing. so what do you think is the next evolution of the Internet? Like there’s all these things people are talking about AI blockchain technology? What’s next? What’s the next big thing?

LK: So that’s a really hard question to answer. Because you haven’t raised the other half of that. And that’s the dark side of the internet. When you mentioned AI, you have put it in. But the internet had 25 years to be curated by engineers and scientists from 1969 to about 1994. We created new applications, new technology, running experiments and scientific experiments. And with the goal of making this a valuable, miraculous tool. In the early 90s, the internet took a bad turn, because suddenly, it reached out to the consumer world. It was easy to use, there was a good graphical interface called the World Wide Web, there was a high speed backbone backbone. There were industrial companies putting forth capabilities. And these companies realize this internet is a money making machine, we can reach consumers and sell thanks to them. So a lot of the focus of development shifted to how we can attract customers and sell them things instead of doing great miraculous scientific engineering. And one of the things that led to that was the first spam message, the first broad base spam message where it reached everybody was on April 12 1994, two lawyers sent out a spam email, I can show you a copy of it, I have it by the way. And it basically pointed out to the recipients of this email. There’s a green card lottery taking place now. It’s going to expire in six months, come to us by our services, lawyers, and we’ll help you get into the lottery. These guys were advertising on our engineering network not allowed. So we sent an email back and said, You can’t do that to stop Shame on you, how dare you, we send so much email back to them. We took down their server. So it was an unintended consequence of the first spam email, we created the first denial of service attack. But the cat was out of the bag now. And so it took a left turn, and started moving into action, which it hasn’t recovered from since. And, in fact, one of the great powers of the internet is that anybody from any location with a computer, and an Internet access, can reach out to millions of people instantly, at almost no cost anonymously. Well, that’s the great power of the internet. It’s also a great enabler of the dark side. And both have risen. Okay. And we see some very terrible things happening out there. So do I think we’ll cover? I hope so. And I believe so. But I’m not convinced that we will. The dark side is very dangerous. Fake news is an example of what’s going on reaching out to constituencies firing up people’s anger and bad behavior, fraud, on and on. And now, as you pointed out, with AI coming in AI will have profound influence on the internet. It’s going to continue whether or not we reach sentience, sentience, I don’t know, become smarter than us, I don’t know. But it will have an impact. It will guide a lot of what’s going on the internet. And the question is, will it be controllable in the sense that we prevent it from basically enhancing fake news, lies, hallucinations, etc. And yet, it’s enormously powerful. It can do things that we can’t do as humans, like pattern recognition, it’s so good at it. But the thing that I fear, and I’ve always had this concern is the following. Any well designed, optimized system is dangerous. And let me give you an example. Consider a ham radio versus FM radio. Am radio is always lousy. And the further you go from the base station, the lousy route gets. And you know, it’s getting lousy, because you can hear it’s getting poor. FM is terrific. It’s perfect. And as you go out, it stays perfect until you get to the edge of its limits. And then it collapses suddenly, well designed systems are meant to perform well in the domain for which they were designed. And beyond that, no guarantees. Now, if you don’t know how these systems behave with artificial intelligence as a neural network, and if you don’t know what the boundaries are, where they will work well and where they will collapse, you are in dangerous territory. I mean, what if we gave an artificially intelligent system, the job of running the US economy and one day decides to ruin the economy or tries beyond capability and collapses. If we don’t know what the boundaries are, it’s dangerous. And I’m going to give you an example from the past. The first check a plane program was written for an IBM 701, computer by a guy named Samuels. And it was learned by rote, and he could play with it. And one day he was playing with it. And he made a mistake. And he accidentally changed the algebraic sign of the goal function from plus to minus, the machine was now programmed to lose. And he started playing with, he didn’t know we’d done that, and he couldn’t tell who was trying to lose. Because to lose good, you have to capture control of the board, make the big sacrifice and boom. Now does the national economy go that way, suppose there’s a mistake or limit? Scary. So if you don’t understand how these things work, you’re playing a dangerous game. And that’s my concern about these wonderfully effective neural network artificial intelligences. Now we’re trying to make them explainable. So we understand what’s going on. But it is an issue. So what is the future of the Internet? The world is becoming and will become a pervasive, pervasive global nervous system. Everywhere you go, the internet will be there, and it will be invisible. Happily, you won’t see it, just like electricity is invisible. It disappeared into the infrastructure. But he’s got a wonderfully simple interface, it’s two holes in the wall, you plug in, you get electricity, there’s no password, there’s no tiny keyboard, there’s no application drains or whatever. That’s not the case with the Internet. Today, it’s far too complex to get access. Even though they are cell phones, these smartphones are really smart. They’re still complicated little babies, I don’t want it to read, I want to be able to talk to the internet, as I’m talking to you, with my voice, with my gestures, with my haptics and expressions. And that will happen because of embedded technology that we’re producing these days. embedded technology and, and software agents out there to do our bidding. But it’s going to be a fight between that view and the view of systems that run amok, as in some of the potential artificial intelligence systems, but it will be invisible, and it’ll be everywhere. And your privacy is gone. If you’re going to get there. You gave your privacy up, when your parents put their address in a telephone booth. And when you start carrying on a cell phone, we know where you are, and what you’re saying.

MJ: Yeah, that actually goes into my next question. Some people may claim that the invention of the Internet has had negative impacts, like you mentioned, lack of privacy, or just screen addiction, things like that. What would you say to those people?

LK: I would say first of all, accept the fact your privacy is gone. And you’ve contributed to it. Use a credit card, we know what you paid for what you bought, when you were there. Same with a cell phone, you put your address in a telephone directory, the only privacy you can get is to go to the edge of the ocean here in Santa Monica, strip, dive in, and hope there’s no sonar down there, but there probably will be. So it’s pretty much gone, that there were limits to abuse of privacy that we can try to control. And in that regard. You know, what do we do with all this negative side of the internet? Well, there are various constituencies, activists here that need to engage. First of all, there’s the IT manufacturers, there’s the Googles, there’s the Amazons, there’s Microsoft, they’re selling you products. There’s the government. Should the government control No, the government should provide an arena where the stakeholders are a forum where the stakeholders can interact. There’s scientists who should try to find solutions to some of these problems, or we’re constantly trying to, there’s all kinds of homomorphic encryption, which hopefully can protect data, etc. slow, too slow to be deployed. But there’s one other so I mentioned four, three groups so far. There’s the manufacturers, the industry, there’s the government. There’s the scientists. The other group, are the users, the user population, and we the EU are far too silent. Only recently have we been allowed to say something about? Do you accept the cookies we’re putting on there, and most often you accept them? Or that you’ll be the 20 or 30 Page legal document which you won’t read. We are too quiet, we have to express our concerns. And we have to be able to express what we’re willing to accept. I mean, how would you express what privacy you want? It’s a little complicated, because you don’t know all the ways they can get it, it should be easy to describe what’s going on. Instead of a 20 page legal document, there are graphical ways where you can describe how much you will let somebody reach into your contact database, track your behavior on the web, look at your email, etc. And you can do it graphically, the graphic ways to do that, you should have a policy, I’m willing to accept this. And when you look at a website and say, Well, this is what I’m going to do. And if it doesn’t match, maybe you should negotiate. And if you can’t agree, you leave. Well, that’s not yet here. But the user population has to complain and be willing to walk away when it doesn’t match what they want to see. So that’s yet to be done. But my big argument here is that the user population is not vocal enough. And they have to engage and express through whatever means they can, their dissatisfaction or satisfaction with what they’re seeing.

MJ: So at this point, I want to switch gears and talk about your involvement at UCLA. So you’ve been a member of faculty for over 60 years, why have you stayed so long?

LK: Because I love it. Because I can’t think of a better profession. I can tell you all the things that’s wonderful about letting me do that. First of all, you don’t have a boss. You decide what classes you want to teach, by and large. You decide what research you want to do. You get to travel. The best minds in the world are at universities, and they come and visit you, you can go and visit them. It’s prestigious, the salary is fairly good. You’re doing good. You’re working with young people, which keeps you young. You’re challenged all the time. But you have to like teaching. And that’s not always a prerequisite for people joining the faculty. If you don’t like teaching, it’s a nightmare. And you see the result of some of that with some of the faculty who just don’t like teaching.

MJ: Why UCLA though? I mean, I’m sure you could, you know, teach at MIT or any of these other prestigious universities, why UCLA?

LK: So a few reasons. First of all, I did not want to become a faculty member. When I got my PhD. I was ready to take this great research position. Lincoln Lab had this wonderful position waiting for me. They, by the way, sponsored my PhD as well. And I wanted to it’s great research place. But they said, Look, we know you feel you’d like to work for us. But you probably feel an obligation. We don’t want you to have any sense of that. We want you to look out into industry, look out in the world, see what’s available. So I went and looked, I looked at industry, I got a wonderful job offer Bell Labs is often a great position. I came to the west coast to look at some places, including the aerospace industry. But I was not interested in teaching. Although I had done a little teaching as a graduate student, which I liked. For some reason, UCLA thought I was looking for a faculty position. So they invited me out to interview. So I did. And son of a gun, they made me an offer. Now this offer was way out here on the West Coast guys, remember, this is 1962 63. This was the Wild West. And my whole family was back on the East Coast. And the job they were offering me was paying half the salary I was going to get as a researcher doing something I really didn’t know much about. I’d done a little bit of teaching. But it looked interesting. So I went to the folks at LinkedIn lab, and I said, Look, I really want to work here. But I’ve got this offer from UCLA. And it’s got these features which are interesting. And they made a wonderful response. I said, Listen, try it. If you don’t like it, come back to Lincoln Lab. What a generous offer. Well, I tried to, I guess I liked it. But I gotta tell you, it’s the most wonderful position you can imagine. You decide your own rules. And if you like doing research and teaching, there’s no better job. Yeah, and by the way, UCLA was then and still is the most prestigious university. When I first came here, the only the Department of Engineering had no individual departments was one department of engineering. The whole school is one department. And it was run by the namesake of this building Luellen belta and 9068 and 69. We converted the departments. But my colleagues here are wonderful, and why did he never take a position elsewhere? Well, Oh, my children were born here. I got a divorce. And they were living with their mother. And I have visitation rights. And I never wanted to take six months or a year away while they were growing up. So in fact, I never took a sabbatical. But it was their personal reasons as well as professional reasons why.

MJ: So over the 60 years, UCLA’s acceptance rate has gone, you know, lower and lower, and become more selective. I’m wondering if you’ve noticed a change in the quality of your students? Do you feel like you’re any smarter or more capable than when you first started teaching now?

LK: Yes, but I’m gonna give you an answer, you don’t expect? I don’t find them as good. Not at the PhD level. And there’s a number of reasons for that, I think. One of the mics, I can blame on the funding agencies. What I described to you earlier is the way up funded research. They would come to a faculty member and say, look, here’s a pile of money, it’s yours, go do what you want. What does that faculty member do? He doesn’t need the money, he’s getting the salary from the university, he goes to his graduate school says, look, here’s a problem, go work on it, go figure it out yourself, shoot for the moon, I’m not going to bother you, I want help, I’ll help you. So it was a wonderfully rich, engaging environment where great research was done. But then the funding agencies slowly changed. And pretty soon they couldn’t give a contract, unless there was a military application, which was devastating for university. And most universities wouldn’t accept it. And they said, at the same time, research labs began to disappear, Bell Labs disappeared. The IBM Watson disappeared, basically. So where did those researchers go, they took faculty positions. So the more faculty chasing less money from the funding agencies. And the problems that we’re working on got smaller, and smaller, and shorter and shorter. And so what happened is the faculty had, in their mind, had no choice but to do their research that way, smaller problems, shorter term, less money. And they will fund their students and teach them that same approach. Now those PhD students, they are the faculty of the next generation. So in some sense, the shoot for the moon, the grand challenges, were no longer the soup, the euro. Interesting, and, and it affected the way the researchers, the students thought about problems. And I’ve seen that slowly. It’s not universally true. But I’ve seen a tendency where it used to be when I gave a student a problem to work on, make a model of this, evaluate it, and tell me what you find. And they don’t understand what they have done. They showed the results. They talked about the implications, how it could be extended, why it was behaving that way, slowly began to see students come back and say, Look, I’ve simulated the model. And here’s the way it performs. And I say, Well, look at that performance curve looks like it’s got a straight line here. What’s the meaning of the slope in terms of the underlying model? Or what if I doubled the number of users what would it be? The answer would be Oh, out simulated again. Big mistake, they had no understanding why it was behaving the way it was. They missed that other half of what I talked about, the how and the why. And one of the reasons that happened is not only the funding, but it’s something called computers. I feel computers are the worst enemy of critical thinking, right? People relegate knowledge to the web, they don’t have it up in their head. And if you don’t have things in your head, you can dream about it. You can’t take a shower and think about it or drive a car and puzzle over it. And something sure if I want to look up what the Assyrians did in 1000 BC. I didn’t know that but I can look it up. Okay. But if I want to remember Maxwell’s equations, or Archimedes’ principle, or some physics, it’s got to be in my head so I can use it and understand how these things relate. So I can generate new stuff. So the computers are there. They’re wonderful devices, but they vertically inhibit a certain level of critical thinking,especially now with ChatGPT and Bard and all these tools. It’s just students are becoming over reliant on them almost exactly. And they can do great things, but they miss the ability to do a certain amount of creativity. And, for example, as a professor, I’ve always given closed book exams. And the students have been waiting. What if I, what do you have a five part problem? And I can’t get Part Eight, because I forgot the magic formula? My answer was, don’t worry, you can buy it during the exam, I sell parts of the exam and you lose those points. So it gets the fear out of it. But I want them to have it in their head. So they can, so can muddle around there, and you know, things will happen. I’ve seen it happen over and over again. And I don’t see that much of it these days. By the way, the students are very good at regurgitating, you know, if you give them a homework problem, they’ll do it. You ask them to study something else, though, they’ll know that stuff. But then it’ll disappear when they go away. Interesting.

MJ: Do you enjoy teaching or researching more?

LK: Both they don’t, I don’t separate them. My teaching is a kind of research and my research is a kind of teaching. For example, when I when I get on a blackboard, I love a blackboard, I use it anymore. I love Blackboard. I’ll be up there developing some some theorem. But my mind is in the mind of the student. And I’ll say to myself, Now, wait a minute, I don’t understand what I just said. Neither today. So I’ll go back and explain it another way, well, carefully, you need to be able to do that if you’re going to be effective an effective teacher, but I don’t separate the two, the best way to learn is to teach. And that also, look, some of my homework problems or exam problems have become research papers, you take a simple version of something, so I can extend that. And it becomes some new knowledge. So I don’t separate them. But the wellspring of my life is teaching. And watching young men and women get the AHA, the gleam in their eye, the understanding. And you know, when you’re working with a PhD student on a new problem, you prefer that they come up with a problem, where even if you do in those early months, you know, they’ll pedal along, the progress won’t be linear. It’ll be nothing. And maybe you’ll give the middle ideal go slip and fall down again. And then one day, it starts to take off. And that’s when I as a supervisor, know that they’ve become a researcher. And they have to understand it’s highly nonlinear, don’t get discouraged along the way. You know, we as faculty do a great disservice to our students, and teachers in general do because we give students 4000 years of accumulated knowledge for free and easy. Here’s the Mona Lisa. Here’s a great piece of literature. Here’s Maxwell’s equations here. Have it. Here’s Archimedes’ principle, whatever his theorem is little’s theorem. So they believe that it’s easy. They don’t realize because we don’t teach them that every one of those people, when they hit the frontier, they hit a dead end and have to work really hard to break through. Once they break through, here’s the result. Oh, that’s nice. But they have to realize, when they get there, and they find a Tod, they’ll get discouraged unless they realize, so we’re the great scientists. And when you break through, you’ll know. So it’s a disservice that we handed out so easily without telling them. It was a lot of issues, a lot of difficulty. For those great scientists who made breakthroughs, we tend not to do it because we want to present them with the material. And you have to explain to the researchers, students what it’s like. That’s why it’s highly nonlinear.

MJ: If you had, if you had the opportunity to give your biggest piece of advice to you know, every single UCLA student, focusing more on just life advice, how you should live your life as opposed to academics and career, what would that be?

LK: Trust in yourself. Find ways to prove to yourself that you can achieve. The eagle scout was my example. By the way, Don’t get discouraged if you fail. It’s a way to change what you’re doing so you improve and most of all, never, ever. Take a job that you don’t enjoy. They will never pay you enough. I mean, after all, it’s your life. You know, the salary is not the issue. You have enough to live on. But don’t cry prostitute yourself for, you know, use the word financial gains. Do something you enjoy, because as Confucius said, if you take a job you enjoy, you’ll never work a day in your life. And that’s so beautiful. It captures it so well.

MJ: Thank you so much for joining us Professor Kleinrock. It was an honor to get to interview you. And thank you again.

LK: My pleasure, buddy. Nice speaking with you.

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Marty Johnson
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