Tamiko Thiel: part 1 - sculpting the electronic brain
In part one of an extended conversation, the pioneering media artist discusses designing the Connection Machine, working with Richard Feynman, and how her Japanese-American heritage shapes her revolutionary approach to making technology beautiful.
Today, the Spotlight shines On digital media artist Tamiko Thiel.
To mark our special milestone of 250 episodes, we are kicking off a two-part conversation with media artist Tamiko Thiel.
Tamiko has lived at the crossroads of art and technology for over 40 years. She designed the Connection Machine, the first commercial AI supercomputer, which now resides in New York's Museum of Modern Art. She has worked with everyone from Steven Spielberg to Richard Feynman and pioneered virtual reality art before most people had even heard of VR. Her Connection Machine even inspired Steve Jobs when he built his post-Apple computer, the NeXTcube.
In part one, Tamiko shares her journey from being a Stanford engineer to an acclaimed artist and how her Japanese-American roots shape her work, which explores identity, place, and space. Part two drops next week.
Dig Deeper
• Follow Tamiko Thiel on Bluesky, Instagram, and LinkedIn
• The Connection Machine
• Danny Hillis, Richard Feynman, Tamiko Thiel & Colleagues Design the Connection Machine
• The Female Supercomputer Designer Who Inspired Steve Jobs
• CM-1/CM-2 "Feynman" T-shirts
(This transcript has been lightly edited for clarity.)
Lawrence Peryer: Something I often tell people, or one of my self-concepts, is that I feel I grew up in the first generation of people that had computers in the home—very early personal computers in the early eighties. Music and technology were sort of my two best friends most of my adolescence. And it's been so fascinating to watch the dance they've done with each other over the years.
Tamiko Thiel: Yeah. Yeah.
Lawrence: And quite honestly, something I was going to get to, and maybe we could shelve for now and talk about later in the conversation, but also how the view of the potential of technology has changed. I would never say I identified as a techno-utopian, but I was certainly firmly in that late eighties, early nineties camp of techno-optimists.
Tamiko: Mm-hmm.
Lawrence: I'm dealing with a lot of disappointment right now. (laughter)
Tamiko: Yeah. Yeah. We're really getting the dystopian version, full force right now, especially as the ones with the power to decide whether it's utopia or dystopia seem to have gone full side to the dystopia, so yeah.
I didn't have a computer at home until very late because I always had a computer at my job, and so I had no need to buy my own until fairly late in the game. But I was a product design engineer, not a computer engineer or a computer scientist, but my first job was working as the product designer for the terminals for Hewlett Packard's computer journals division.
So, and then I went on with the Connection Machine to do the housing for the first AI supercomputer that was commercially available. So I certainly always saw myself as maybe not a techno-utopian, but a techno-optimist. With a full consciousness that no matter what you do, someone can figure out how to kill people with it.
Lawrence: Right, right. (laughter)
Tamiko: Unfortunately. I think that's a fairly true statement though, and just seeing how the ones who are doing negative things with the technology have won out, especially right now in the States. It's very distressing.
Lawrence: Yeah. One thing that gives me particular distress is that it's white men of my generation. It's impossible to ignore just that demographic. It's hard to be identified with that group. Yeah, yeah, yeah, yeah, yeah. Who wants to be in that club?
Tamiko: Yeah. No, I completely understand that. There are all sorts of clubs that, talking about the Second World War, it's like, I'm half German, half Japanese, right? The Axis powers. And so what do you want to identify with? I mean, I try and identify with the good that both of those cultures have produced and be aware of the evil that both of those cultures have produced and executed.
It was very interesting for quite a while when I first let people in my circle of friends in Boston know that I was going to move to Germany. (laughter) I got some really weird responses. This is 1984, and people were saying like, "Germany, but it's so dark there," compared to California. Yes, it doesn't get a lot of sun, but what do you mean it's dark there?
And then someone else just blurted out, "But Germans wear black leather and are sadomasochists," and it's like...
Lawrence: Some of them! (laughter)
Tamiko: I'm glad you—I'm glad you know them all so intimately. (laughter) I could ask you why you know them so intimately. But anyway, and then of course, like I get into sort of the punk Berlin crowd, and they're not all sadomasochists, but they were all wearing black leather. (laughter) So it's like, anyway.
Lawrence: Yeah.
Tamiko: Yeah. But I figured the only culture that's completely free of evil is one that's never had any power whatsoever over any human being. And as soon as you have power over some other human being, whether it's in your own group or outside of it, then there's bound to be people cropping up who like to misuse that power.
Lawrence: Yeah. Something that you just alluded to, which really strikes me as, I don't know necessarily a theme, but a very interesting strand throughout your life is this manifestation of, as an individual, the way you manifest the combination of art and engineering. Even in, if we want to have fun with stereotypes for a minute, Japanese and German. (laughter)
Tamiko: Oh yeah, I can go on about those stereotypes, man. Yeah, yeah. And stereotypes are often based on at least a kernel of true fact. (laughter) So I'm aware of all of those potential stereotypes and truths also. And it's a funky combination.
Lawrence: Yeah. I'm thinking of the beauty in those attributes, just so you know, this is not, that was not a backhanded way to be critical. Before digging into a lot of your education and career, I wanted to talk a little bit about your early life. We don't have to spend a ton of time there, but I spent a lot of this weekend reading and listening to other interviews with you. There are some just fascinating anecdotes. I thought maybe I could dig into a little.
Tamiko: And you know some of my family history already from having interviewed my mother, Midori Kono Thiel, about her father Drew Ha Cornel.
Lawrence: That's right. That's right. And your family is so uniquely fascinating to me, in terms of just how much art is around your family, and it has been, it's really lovely. But something that struck me was the fact that your father, Philip, was an architect. I know just enough about architecture as an art to be dangerous. I'm not an aficionado or anything further than that. I know what I like aesthetically where to me, architecture lives again at that nexus point of art and science. Do you view your work as being at all parallel or in dialogue with him?
Tamiko: Definitely, it's even worse than you think. I mean, it's even better than you think, or worse than you... Anyway, so the reality is that Dad, Philip Thiel, started out as a naval architect, which means a shipbuilding engineer. He was doing hull design. I mean, he was in his twenties during World War II, and he was working, designing hulls for ships. So he didn't go to combat. He was on the engineering side.
And after the war and after his schooling as an engineer, he was teaching naval architecture. He came in 1950 to teach naval architecture at MIT. His office was right next to the office of György Kepes, who was not in the Bauhaus, but he was a good friend of Moholy-Nagy. Marcel Breuer, Walter Gropius, and Moholy-Nagy actually brought him from Europe to Chicago to help found what was called the New Bauhaus in Chicago, which really didn't seem to take off. It didn't last very long. The school was renamed very quickly.
And then by 1950, György Kepes was teaching the first art and technology courses at MIT. And as I said, Dad had his office next door to György Kepes's office and showed him some studies on the aesthetics of ship hull design that he had just been working on. And they not only became good friends, but Dad became one of Kepes's special students and graduated two years later with a special degree in architecture because Kepes was in the architecture department.
Also studied with Kevin Lynch, became a family friend. I also met, had dinner many times with both György Kepes and Kevin Lynch. Kepes went on to found the Center for Advanced Visual Studies in, I think it was 1968 or so at MIT and is mostly known for that, for starting the first department of art and technology in the US at MIT.
Dad, through his relationships with György and with Kevin Lynch, did his work in the perception of the built and urban environments from the perspective of someone moving through that environment. And that became really the subject of his entire life.
And his magnum opus was a book called People, Paths, and Purposes that was entirely talking about this, but bringing in all sorts of references to Japanese culture, to theater, to music, to pretty much all of the arts. He developed a notation in the way that Labanotation notates time and space, and the movement of dancers through time and space in the dance field. Dad developed a notation that he calls a Space Sequence Notation for the notation of the experience of walking through a building or an urban environment.
And it was exactly this theoretical background that I later then in the mid-nineties took as my theoretical background when I started creating virtual reality worlds, virtual worlds where the experience happens only if you personally instigate it with a joystick to move through those spaces and thereby encounter essentially a story which is built into the space itself.
So, and then you have the coincidence that about thirty years after Dad came to MIT as a teacher and left as a student, which he really delighted to point out, I came to MIT, it was 1981, so it was thirty-one years after Dad and came as an engineer. Halfway through my graduate work in mechanical engineering discovered what became the MIT Media Lab.
And that had evolved out of the departments that Kepes had started, that had then evolved from CAVS, had spun off into the Visual Language Workshop and the Architecture Machine Group and all of those laced with a lot of dropouts and frictions into the MIT Media Lab after I graduated.
So I took courses for literally half of my time as an MIT graduate student in mechanical engineering. I was actually moonlighting in the architecture department taking these classes that were all about computer graphics and using computers as tools to create virtual worlds or to create visual tools for creating virtual replicas as in the Aspen Project. That was one of the famous projects that came out of the Architecture Machine Group, et cetera, et cetera.
And that really is what resolved me to become a media artist. That this was really, after doing sort of the dance around going into product design, because Stanford Product Design was also in the seventies, one of the very few programs besides CAVS over at MIT that would allow you to combine engineering, art, and design.
And I didn't want to become an architect, 'cause Dad was an architect and Dad was sort of, he was a very good teacher, but one who basically he knew the right answer and if you thought that was wrong, then it showed that you were obviously stupid. (laughter) So it's like, ah, okay. I am not going to compete with Dad's architectural field in any way after trying out high energy physics and realizing that there are other people who are much better at it than I.
When I found the Stanford Product Design department, that was really the home for me as an undergraduate, being able to combine, again, engineering, art, and design.
Lawrence: What would that have meant? You were thinking your career path was?
Tamiko: Well, when I was at Stanford I thought I was going to be a product designer, where you can sit around thinking of cool solutions to problems. Then actually working at Hewlett Packard doing the packaging design for computer terminals in an incredibly supportive environment that really mentored me and supported me. And where I got to do much more in my early twenties than most people would be able to do.
I decided it was boring and I wasn't sure what I wanted. That was the problem. Yeah. I was working at a well-paid job in Silicon Valley. I had all sorts of really interesting friends who were working at Apple and at Xerox PARC. Xerox PARC is where the windows that we all use and the mice that we all use were invented.
It turns out that my best girlfriend in those days, later, she told me she was working on the very first Macintosh, but she couldn't tell me then, because it was a secret project.
The problem was that there was all of this stuff around me and the only thing I could think of doing with my life was either staying an engineer or becoming a manager of engineers. And I sat there, I was like, how old was I? I was like twenty-one or twenty-two or something like that, and said like, this can't be all there is to life. There's got to be more. But I have no clue what that more could be.
And so I decided to go to graduate school at MIT and radically change the place I was living. I had grown up on the West Coast. I was going to college on the San Francisco Bay Area at Stanford. So I moved to Boston. I started at MIT and it really did provide me with all of these other opportunities and ways of doing things.
And it's really funny because MIT actually has a very narrow focus. I mean, when friends of mine were starting the MIT Media Lab, I said, I want to become a media artist. Should I apply to do a PhD at the Media Lab? And I was literally told, if you want to do art, the Media Lab will not be the right place for you. We're going to be building tools, not art. And that's in general the MIT mentality.
So strangely enough, in this place that really does have kind of a tunnel vision, it was the place where I discovered, probably you have to say, I discovered some people who were teaching there in these parts of the architecture department that became the Media Lab who had much broader horizons, who really blew open my horizons and made me realize that what I was suited for and what I was interested in was where all this comes together, where the art and the design and the technology all come together.
Lawrence: Were you drawn specifically to human-machine interfacing or not necessarily?
Tamiko: Yeah, that was an interest while I was at Stanford Product Design. Also, just when I see a product for the first time, what does it say to me? If I need to use this, then how can I design a product so it's clear how it should be used so it's clear what it should mean, to me as a tool or to me as someone who it's supposed to help with the function.
It was very clear to me that, there are all these design books that have these sort of helpful rules of thumb and things like that. And one is that, okay, looking at the American population, here's the span for adults, so it's like the smallest and the tallest.
And I was in a design group at Hewlett Packard where like, I was definitely in the lowest fifth percentile in terms of size. And another one of the product designers was definitely in the ninety-fifth and upwards percentile in terms of height and size, and so we joked that we were the perfect team members because between the two of us, we could test it out and see how one product could be used by the whole extremes and everyone in between.
So that was very much a focus there. And then when I got to MIT, I was in the biomechanics lab. I just did a, as a master's, I did a very minor experiment with a device that my professor advisor had designed for his PhD thesis, which was the sonic navigational aid for the blind that sent out an ultrasonic pulse, got it back and translated it into an audible sonic environment that would tell the person, is there anything to my right?
I know that I can hear the wall to the left. I can hear little disturbances when I walk parallel to the walls, and I know those must be door jams. To the right, I'm not getting anything back. So it is probably open. But then every now and then I pass something that has kind of a soft, fuzzy thing that's maybe a tree.
And this is all sort of an audio version of the visual notation system that my father had been working on in his work.
And that's, it's purely coincidental in some way. If you believe in coincidence. Really also a reinforcement of my interest in, how do we perceive the environment? How does that perception of the environment act on our senses, on our emotions, on how we feel in that space? All of which feeds into work that I do on in virtual reality and augmented reality, dealing, creating, if you will, artificial or virtual spaces that, as artworks need to communicate that sort of feeling, emotions, sensory reactions to the user.
Lawrence: There are a few things that occur to me and one is, it's not clear to me how much our listeners will appreciate, and it's something I'm hoping we, you and I will be able to elaborate on for people just how long things like artificial intelligence and virtual reality, and to an extent AR have been with us and have been in the labs as well as with artists and with product designers. I'm sure just like you, I can remember in the eighties, artificial intelligence was five years away.
Tamiko: Right, right. Yeah.
Lawrence: General, a GI was five years away and that probably goes back to the fifties. It was five years away. Exactly. So I think we need to probably spend some time in a few different areas, but before I ask you, I know you've told the story elsewhere, but I'm going to ask you to tell the story of the Connection Machine for our listeners. Okay? Before I do that, how did the public unveiling of the Macintosh land for you, if at all? Like, were you as someone who was firmly in that world and thinking about design and aesthetics and interface and product, were you impressed? Was it a paradigm shift?
Tamiko: Oh yeah. It was. It was, because remember I had been in the Xerox PARC social crowd since at least '79. And then the Macintosh came out in '84. I was in the Xerox PARC social crowd because my boyfriend at the time was working there and so I visited him sometimes there after hours and saw the Windows system, saw the mouse, and I said okay, for like a designer or an, like me, I still thought of myself, I still was a designer at that point, rather than an artist.
For a designer like me, this would be the most incredible tool possible, but it was only on these Altos that were in Xerox PARC. And my boyfriend at the time said, "We have Windows and mice and you can't have them." And I was, decades later when I found out that there were various other people during that time who came in after hours and were given access to these things and worked with them. I was so furious with him. Wow. And we had separated a long time ago when I went to MIT, but just the idea that, okay, we're going to keep this technology to ourselves was really infuriating to me.
Lawrence: And a remnant of the first generation of computer scientists, right? That whole high priest model of only certain people could feed the cards and read the cards. Yeah, yeah, yeah.
Tamiko: And I was at one of the last things I remember at Xerox PARC was when they had this huge party on the rooftop terrace to announce the, now I'm going to blank on the name, whether it was the Xerox Star, I can't remember the name of the product, but it was their attempt to bring out a product, which PARC was not good at at all, that would allow other normal people to buy and use Windows and mice and things like that. And it failed miserably because it was so expensive.
And so when the Macintosh came out in '84, it actually didn't have separate windows, but it did have a bitmap display, which was also before that like just at Xerox PARC. So the bitmap display, the mouse, and being able to basically, all of the sorts of programs that I had been able to use because I had been working at computer companies that had minicomputers or mainframes that provided access to these tools. And now all of it in some small box. I can't remember what it cost the first one, but it was a revolution.
And my friend Joanna Hoffman, who worked on that first Macintosh, visited me while I was still a student at MIT. So remember I graduated in '83, so this was probably like 1982, and she said, "Don't tell anyone, but we are bringing out this computer. It's a standalone computer and it's only this big and it'll have floppy disk storage and it'll use the mouse and it'll have a bitmap display." And I'm going like, oh my God. Wow. Finally, finally, someone's actually going to bring it out and then a couple of years later, boom, the Macintosh and I'm going like, oh my God. That's what she was working on this whole time.
So yeah, it was a revolution and it, it's funny, a revolution in a number of strange ways that I haven't really seen research on, but there's this statistic I've heard several times that female participation in computer science departments was increasing until the mid-eighties, and then it started decreasing again.
And I've read some speculation which would make sense perhaps that it was actually something like the advent of the Macintosh, which made it possible to do a lot of things using computer technology, whether it was editing or whether it was creating images where you were using the computer to do things, but you didn't have to learn to program in order to do them.
It's really quite possible that in some funny ways, the Macintosh was the beginning of the demise of women's participation in computer science departments. Because they were actually not interested in developing new technology, they wanted to be able to do things with technology and tools like the Macintosh enabled them to do those things using computer technology without having to build the technology themselves.
Lawrence: That sounds right. That sounds right.
Tamiko: And that's frankly also what ended up happening in a different way with me when I decided that I wanted to start creating media art. I've developed hardware and software.
Lawrence: Mm-hmm.
Tamiko: And it takes a long time. And so, so I frankly, as an artist, if I need to develop hardware and software, I'll do it. But if I can find a way to use existing hardware and software tools to create artworks, then I prefer to put my time into the creation of the artwork rather than into the creation of the tool. So perhaps that's exactly what happened with me, that around in the mid-eighties, all over for different reasons. Then I stopped going into engineering and started creating art with technical tools.
Lawrence: Yeah, that's actually, that's, that is a very fascinating insight and reflection on that evolution. So with that said, do you mind relating the tale of the Connection Machine?
Tamiko: So, right. Not at all. So when I was at MIT as a grad student, actually it was people at Xerox PARC who were working in artificial intelligence who said, "Oh, you're going to MIT, you have to meet these friends of mine, Marvin Minsky and his PhD student, Danny Hillis." And so I basically went to MIT in 1981 as a mechanical engineering student, but with social introductions to a number of people in the MIT AI Lab.
Danny immediately became a friend and a bunch of other people in the AI Lab became friends, and they had much more interesting parties than in the mechanical engineering department. I actually didn't have any friends in the mechanical engineering department. They were all in the AI Lab or in the architecture department. So that was really my social environment in the two years that I was at MIT.
And like I said, my discovery of this Visual Language Workshop and the Architecture Machine Group that later merged to become the Media Lab was what decided me that, when I finish up this degree, I actually want to then go, make a right-angle turn and probably go to art school and somehow become an artist, a media artist.
So I graduated, there was a ceremony, and then I think really three days after—two or three days after—Danny called up and said, "Can we meet? I want to tell you about this company I'm starting." And I knew he'd been working on this crazy concept. The Connection Machine using Marvin Minsky's sort of society of mind ideas, that intelligence probably doesn't arise from having really good processors because here we've got eighty billion really stupid processors, and somehow out of these eighty billion stupid processors, human intelligence arises.
That was the spark that set Danny in motion to say, okay, I don't think we're going to solve this problem of artificial intelligence, all of the multitudinous problems of artificial intelligence by creating very, very powerful processors. I think it's something about the connections, and that's why his concept was called the Connection Machine.
And he said, "We've got funding to start a company, but we don't even know if it's physically possible to build this machine. You've worked in packaging design for computers. Can you join us and answer that question and then if it is possible, actually design the packaging for the Connection Machine?"
Then he said in the next sentence, with a twinkle in his eye, "And if you do come, you get to work with Richard Feynman," because he knew I had started out as a high-energy physics student at Stanford that, we all like revered Feynman. And indeed, when he said that, it's like my eyes just opened wide and I said, "Where do I sign? Where do I sign?"
So that, that's a true story. That's really what convinced me even before I went out and visited the company. It's like, of course I'm going to work at your company if I can work with Richard Feynman.
Lawrence: Yeah, why not? (laughter)
Tamiko: Well, there's actually, I can send you a link to a really funny story that Danny tells. Danny is a very good storyteller and I picked up a lot of tips from listening to his stories. Richard's son, Carl, was studying AI along with Danny and Marvin, and was one of the first, was one of the people who helped start Thinking Machines and apparently when, at some point Danny was like hanging out with Carl and his family.
And told Richard, who was a professor at Caltech in high-energy physics, and Richard said, "Oh, that sounds like a really crazy idea. Can I come out and play?" And so Richard literally came out and spent his summer vacations hanging out at Thinking Machines.
And Danny's story is when he first showed up. Richard said, "Richard Feynman reporting for duty, what should I do?" And they were in the middle of setting up and they said, "Well, we actually don't have anything for you to do. Can you like, go to the stationery store and buy a bunch of paper and other office supplies?" And Richard said, "Yes, sir." And Richard Feynman went off to buy office supplies.
At some point, they figured out, okay, one of the big problems we have is we want to start out with 64K processors. That's actually 65,536 processors. They're going to be really simple, one-bit processors, and we're going to connect them in a grid pattern with wires. But that means that when you have 65,000-plus processors, it's really hard to communicate between them. And we think it's important that these communications go quickly.
So why don't you figure out some way to connect them in a much faster way than just talking to your nearest neighbors. And Richard came back and said, "Why don't you connect them in a twelve-dimensional Boolean hypercube?" (laughter) And everyone's going like, "Yeah, why not? Yeah."
And Richard also said, "And I've been solving all these partial differential equations and I figured out how we can route the messages between all the processors." And it's like no computer scientist had ever used partial differential equations to solve a computer architecture problem. But Richard was a physicist and that was one of the tools he used.
So Richard literally designed the router that was doing the message passing between these 65,000-plus processors. And part of my job, of figuring out whether it was possible to build this machine, was understanding how everything fit together. Because I had to do all of the drawings that would explain to the fabricators what to do.
Lawrence: Did you have to build the board?
Tamiko: Not me personally, but there were electrical engineers who were doing the like, okay, this is how we connect all the chips to each other and stuff like that. But my job was to tell them how to connect all those processor chips in a twelve-dimensional Boolean hypercube. (laughter)
So I'm going like, "Danny, what is this?" And he says, "Oh, it was Richard Feynman's idea. Go ask Richard." I go to Richard and Richard, if you've ever read any of Richard Feynman's books, you'll recognize this immediately. So I said, "Richard, what's a twelve-dimensional Boolean hypercube?" And he says, "Oh, that's easy." And he grabs a piece of paper and a pencil, and he starts drawing diagrams.
And he's famous for these Feynman diagrams, which are very simple drawings, which express complicated mathematical concepts in quantum chromodynamics in a very simple way. And so that's how he worked, that's how he thought. And that's part of his Nobel Prize.
So he's drawing there and he says, "Okay, so here we have a chip. Each chip has sixteen processors on it. So there are only 4,096 chips, even if there are 65,536 processors. Okay? So you have this chip and you connect one chip to another, and that's a one-dimensional Boolean hypercube. Each chip is connected to one other chip, and at the most, from one to the furthest away chip, there's only one step. Okay?
"You take that and you duplicate it, and you connect the symmetrical corners. So the one-dimensional chip looked like a line with the end points for chips, and now I've duplicated it, connected the corners. Now I've got a square where all the corners are chips. That's a two-dimensional Boolean hypercube. Each chip connected to two others, and the furthest path is only two steps away.
"Well, you duplicate that and connect like corners. Now I've got a cube where each corner of the cube is a chip. Each one connected to three others, and the furthest step is three. Okay?" And then he drew another cube around that cube, connected the corners and said, "That's the fourth-dimensional one. You've got the inner 3D chip cube and you've got the outer 3D cube and they're connected together. Each chip connected to four others and the furthest step is four."
And then he said, "And after that it's too complicated to draw." (laughter)
Kind of like, thanks, thanks. We're at four, I need to get to twelve. How am I going to do this? So you can keep on putting, like, obviously you just, you can double that cube within a cube and connect all the like corners.
Lawrence: So they're like nested cubes. Is that the way a dummy like me should understand it?
Tamiko: Well, they were hypernested cubes because if you think about it, okay, here's a chip that has four connections to the inner cube, but then you have to duplicate that structure and connect all those corners. So you've got an incredible, yeah. Yes. They're all nested cubes, but it gets very complicated to keep those things separate and, as Richard said, it's just too complicated to be able to follow all those connections.
So I'm playing around with paper and pencil and I have to say, this is 1983, we're designing the world's first commercial artificial intelligence supercomputer on paper and pencil. Not completely. They were also using symbolic Lisp machines. But all of the work on the packaging design was done on paper and pencil, literally.
So I'm playing around on paper and pencil and looking at the topology and trying to think, well, how can I simplify this? And I realize then finally, if I take the inner cube, think of all the connections between the third-dimensional cube and the fourth-dimensional cube as being sort of rubber bands. Then they stay in place. But I can move things around a lot, so I take the inner cube and put it next to the outer cube, and then I've got all these fourth-dimensional connections, which are really hard to keep track of.
So I just drew a thick line and said, okay, that's my metaconnection. So I have two 3D cubes connected together by my metaconnection, which, if you really want, I can draw it out very easily. It's also on my website. By God, it looks like a 1D cube. It looks like a line, but now the line is a metaline connecting two three-dimensional Boolean hypercubes.
I duplicate that and I get a square. I duplicate that. I get a 3D cube and that 3D cube, I—that's a—I'm sorry, that I duplicate the 4D cube to make what looks like a square, but it's a five-dimensional Boolean hypercube. I duplicate the five-dimensional, connect it, and I've got the 6D Boolean hypercube where each corner is now a 3D cube, with chips in the corner.
Well, I realize all of these structures repeat every third dimension. So the twelve-dimensional Boolean hypercube looks just like the 3D hypercube, except the corners are 9D hypercubes, and the corners of the 9D hypercubes are 6D hypercubes, et cetera, et cetera, et cetera, on down.
So then, then it was easy to communicate by this symbolic diagram that no longer showed each individual one. With my metadimensions, then you knew, okay, what that means going down is this one is connected to all of these, et cetera. It became very easy to keep track of it.
Lawrence: Simply put, what was the machine meant to do?
Tamiko: The machine was meant to duplicate human intelligence. There are a lot of different components to artificial intelligence, but Danny's intuition was the first thing we need is massive parallelism, because that's what we've got in our brains. We don't know why, but somehow out of those connections that change, when you practice something, whether it's a new language or whether it's a new physical skill or learning to ride a surfboard for the first time, all of your neurons are rewriting their connections and that's what we call learning.
And so of course there were neural nets already at that time, and there was a theory that neural nets might be the secret behind this, but we didn't have the hardware to implement them. And even with a Connection Machine, they could only do neural nets with a couple of layers. And it wasn't until 2012 or so that we started having the computing power to really have really deep levels of neural nets.
And that's what allowed all of a sudden artificial intelligence to start working in the way it is now. The computing power catching up to the ideas that were already there on neural networks and how somehow the connections between neural neurons and being able to change the relative weights between these nodes somehow was going to be storing memory or storing some sort of ability to move or to distinguish something to recognize. And we still don't know exactly how it works. And that's what's spooky about neural networks.
Lawrence: Incredible, isn't it? That we don't, so we have this construct that Feynman described to you that you were able to finally grok and articulate and design around, right? That's the insides, right. How did you come to your thinking about how to visualize computation? That's the art in this product. Right? That's why it's sitting in MoMA. Right? Like what, how did you get there?
Tamiko: Through the T-shirt logo. This is the only supercomputer designed after a T-shirt logo. In the beginning of any good startup company, at some point you need a T-shirt that sort of symbolizes your...
Lawrence: The swag is important. (laughter)
Tamiko: The swag is really important. It really is what fuses people together and also gives you something to present to the outside world. Right. It's corporate identity, if you will.
We had been, I had been talking about this cube of cubes and here we can visualize it in this simplified way that however, explains all of that structure. And so Danny came to me and said, "We need a T-shirt logo." And he said the way that he had been visualizing the machine to himself at this point was this cube of cubes, but within the cubes, within this hardware rigid, unchanging structure of the twelve-dimensional hypercube, the software could make connections that didn't have to pay attention.
They didn't have to know this processor was connected to that. Obviously it was going through all of these hardware connections, but the processor didn't have to know about it. The processor, thanks to Richard's routing system, would just say, "I want to send a message to that processor way over there." And those connections would conceptually be independent, abstractly, be independent of the hardware structure.
So that's the logo that I came up with. This geometric sort of Cartesian cube of cubes, but inside these pom-pom balls whose connections were independent of that rigid hardware structure. So we made the T-shirts and everyone was wearing these T-shirts and Richard really liked the T-shirt. He wore it for a lot of his, for his lectures. So you'll see him wearing the T-shirt in a lot of videos where he's explaining his various cool ideas.
When it became time to actually start building the machine, I had taken all the input from the electrical engineers and drew up images of, okay, if these are the components you want and these are the connections you have. Then in a real physical structure, we've got a board that's two foot by two foot, that's only one board. And there's a whole lot of these and if you put them together and leave room for cooling and for the cabling, you've got something that's ten feet tall and about five feet by five feet.
And everyone said, "Oh my God, that's way too big." And so all the electrical engineers went back to their drawing boards and said, "Okay, well we can throw out all these connections and reduce these and double up these." And so we finally got the boards down to their current size, which was still kind of large.
But at some point I said, "Okay, we can actually put this in a standard nineteen-inch rack, which is, if you go out and buy a generic rack to put electrical components on, nineteen inch is really a standard rack size." So I said, "Guess what? After you guys did all that reduction work, we could actually make this look like any other computer that's out there or the refrigerator you've got in your kitchen or any other sort of rectangular box that's about the size of a person."
The problem was we were all, like Danny and I were like twenty-five. A lot of people like Brewster Kahle, who's better known today as the founder of the Internet Archive was, was he twenty? I think he had just graduated. So it's like he and Carl Feynman, they're all twenty, twenty-one or something like that.
And we're going up against the big boys, the older men, they were probably like in their forties and fifties or something, who were used to getting all of these million-dollar contracts from DARPA, from the Defense Advanced Research Projects Agency.
And we were going to, we, we had a couple of older people like in their forties or something who were the managers. But we were going to bring in these people, and say for only three to five million dollars this machine can be yours. It's got an architecture unlike anything you've ever seen before. It will do things unlike any computer you've ever seen before.
And we knew that if we brought in that guy with his checkbook—it was all guys then, doing the procurement at the time. And if he saw it and he said, "Oh, that looks exactly like the refrigerator that I just bought for my wife. I just put it into the kitchen." We had lost, we would have no credibility.
So for me, with this background that I talked about, Dad imbibing the ethos of the Bauhaus and he actually did work for Walter Gropius and for Marcel Breuer as a twenty-year-old recent graduate with his special degree. So I was brought up in this sort of Bauhaus aesthetic combined with a Japanese aesthetic from my mother's side.
Lawrence: That's incredible.
Tamiko: I felt like we need to have a form that's distinctive, that looks like no machine has ever looked like before, no computer has ever looked like before. But if that form could also communicate to the person the moment they see it, how the machine works, how it's so different, how it's so revolutionary, then that guy's going to say, "Here's the check. You've got it."
So there you see also my product design background, human factors background, how does the appearance of this object that we've built affect the person who sees it? Do they understand how to use it? Does it communicate, and this is marketing, right? Does it communicate to them that with this object, they will be able to do something they cannot do with any other object out there?
That's, you can say it's pure marketing, but it's also, that's how you form an emotional relationship between an object, the human who uses it or buys it or somehow has to deal with it or wants to deal with it. So that's really a very large part of a product designer's job. Also of an industrial designer's job, is to create this emotional bond between you and some built object.
I had two years' experience working at Hewlett Packard in product design and I didn't have the huge depth of experience and understanding of what all the manufacturing processes that were out there and the materials and things like that. And I was kind of a clumsy drawer.
So at some point it became clear we needed some real experienced industrial designers.
And that's when they engaged two designers from what was then the Eliot Noyes Company. Al Hawthorne and Gordon Bruce were the principals, after Eliot Noyes himself had died. And so they came in as the industrial designers.
And so I presented this whole speech about how the machine is connected together and how the machine functions and what it's about. And they said from the beginning, "Oh yeah, I think we should do something with this cube of cubes idea."
And I went, "Yeah, probably. But I've been living and breathing it for the last year and a half. Let me go off, you go off and make cube of cubes drawings. I'm going to go off and run through different alternatives that have nothing to do with that, just to make sure we're not blinding ourselves, that we're checking out all the alternatives."
So I hired a friend of mine, Tom Piotrowski. We went off and Gordon and Al went off and we all did a lot of drawings and at some point I said like, "Okay, let's just get this over with. I'm going to draw a cube of cubes also." And I drew it and Tom and I looked at it and said, "Well, that's it, isn't it?"
It was just, as soon as it was there on paper, like, okay, that's what it's going to be. Gordon and Al had also tried some different forms and stackings and stuff, but no, basically all of us said, "Okay, it's the cube of cubes."
And then the question was, okay, that's the hardware. That's the rigid hardware structure. The T-shirt logo was really the best expression of the full functionality of the machine. So how do you express that T-shirt in real life? (laughter)
And Carl Feynman had also grown up in this AI community. I've read science fiction like everyone else and dreamt of AI like everyone else, or had been doing it for the last several years. And Carl Feynman said, "When I imagine the Connection Machine, I imagine this cloud of lights and they're all like blinking as they send their messages to each other."
And so we said, "Okay, well let's, we want to make the internal workings of the machine visible to the outside world, but if we just make the skins transparent," I mean, we considered that. "What if we just make the outer plastic skins transparent?" Well, what do you see? You see boards and you see lots of cables, and you see chips. But that doesn't tell you anything about how the machine actually functions.
So this idea of form follows the function of the machine. That works fine if you're dealing with a mechanical function, but if you're dealing with a function that's inherently invisible like electronics, then it doesn't tell you anything because it just, it could be any board, it could be any chip, it could be any cable. That's not unique.
So then, with these ideas of these sort of processors, sort of glowing and sending off their light messages. And then I said, "Okay, let's make, let's make the status lights," that every single chip had a status light connected to it. So you can tell whether is it getting electricity, is it working, is it malfunctioning? And usually they're right next to each chip.
So we just moved those lights from being next to each chip to being on the edge of the board that was on the outside, made the doors translucent, not transparent because if it's transparent then you see, you're just going like, okay, there's a lot of boards in there. If it's translucent, then they're glowing mysteriously through this door.
Lawrence: Such drama. (laughter)
Tamiko: It increases the drama. And you're seeing all, you're not saying, "Oh yeah, there are boards and cables." You're saying there's some sort of mysterious lights that are blinking and glittering in there. It's thinking. It's thinking.
And with this cube of cubes structure, it was kind of a metaphorical electronic brain, when you think of the brain with its convoluted structure. So really, people told me they would sneak into the computer room after hours and the Connection Machine would just be sitting there, blinking mysteriously like an electronic brain.
And it became a cult object with that very small crowd of people who were really into supercomputers. It was a very small crowd back in the mid-eighties when it came out.
Lawrence: That's beautiful. I love that.
Tamiko: But it picked up on a lot of images that we all had floating around in our heads from science fiction movies and from a shared culture of techno-optimism, of thinking, yes, we can build a machine that somehow improves things and extends the range of what we can do as human beings. Let's hope that it doesn't take a wrong turn.
But Danny was also thinking about that, and he said, "Okay, let's make it not any taller than you," and I'm five foot three, so he literally said, "Make it as tall or smaller than you, because then for your generic white male, which is the main customer base we have to aim at here, it'll be smaller than them. It'll be beneath their eye level, and it'll feel like a member of the family rather than an overlord."
So we were also very conscious of this: will AI kill us? Because even in 1984, '85, the HAL computer of 2001: A Space Odyssey from the film that came out in 1968 was still the most dominant image of an AI. And of course it was an AI that went wrong and killed the humans because it perceived the humans as endangering the mission. And that's still the fear that we carry with us now. We tend to know that it's the humans who create the AI to harm humans.
Lawrence: To react that way.
Tamiko: Right. And, but that's what we're seeing happen right now. Of course. Yeah, so the follow-on just to sort of wrap that story up, the follow-on machine, the CM-5, I was not involved in the design of that machine. And it ended up being tall, taller than the human. I'm not sure how tall, at least seven feet, maybe more. It really did dwarf humans.
It had then these strips of LED grids that were added on, but they were not functional. They were decorative, which my Bauhaus background would've never allowed me to do. I mean, I would've done something like make the sides of the machine translucent so you could see, I mean, again, they had status lights on those boards. So there were all sorts of lights happening that we could have shown through.
But I was off in Germany being an art student and I had no email over there and no contact. So I was not involved in that, in the CM-5 design at all.
Tamiko Thiel
Media Artist
Tamiko Thiel grew up in the University District in Seattle from 1962 - 1974, when she graduated from Roosevelt High School. Her father Philip Thiel was a professor at the University of Washington in Architecture and Urban Planning, and her mother Midori Kono Thiel is a Japanese arts expert, a major Japanese performing arts organizer and a prize-winning Japanese calligrapher. Tamiko received a B.S. in Product Design/General Engineering from Stanford in 1979, an M.S. in Mechanical Engineering from MIT in 1983, and a Diploma in Applied Graphics from the Academy of Fine Arts in Munich, Germany. Her first appearance as an artist was at age 5, when the Seattle Times published a photo of her painting a Turkey in Mrs. Roberts' kindergarten class at University Heights Elementary School.
Tamiko has been creating politically and socially critical media artworks for over 40 years that explore place, space, the body and cultural identity. In 2018 she was awarded the iX Visionary Pioneer Award by SAT Montreal in 2018 for her life's work. In 2024 she was an inaugural inductee into AWE’s XR Hall of Fame, and received the 2024 ACM SIGGRAPH Distinguished Artist Lifetime Achievement Award in Digital Arts.
Tamiko was lead product designer on Danny Hillis’ Connection Machines CM-1/CM-2 (1986/1987) at the MIT AI Lab startup Thinking Machines Corporation. These were the first commercial artificial intelligence supercomputers and in 1989 won the Gordon Bell Prize as the fastest supercomputer in the world. These machines influenced Google’s AI technology, inspired S… Read More
