episode 18 – The Robot Whisperer | Madeline Gannon

Resources and links

• Madeline Gannon’s webpage
• Cybernetic Serendipity – Exhibition 1968
• Autodesk Pier 9 Residency
• Manus – Art Work
• Quipt – Art Work
• The World Economic Forum – The Future of Jobs 2025

Credits:

Transcripts

[00:00:00] Nir Hindi: [00:00:00] madeline. Thanks again for joining us today on our podcast.

[00:00:04]Madeline Ganon: [00:00:04] Hey, it’s great to be here. Thank you for having me.

[00:00:08]Nir Hindi: [00:00:08] Maybe you can take one minute to kind of introduce yourself before we dive deep into all the exciting things you are doing.

[00:00:15] Madeline Ganon: [00:00:15] Yeah, that sounds great. I’m excited to talk with you today. My name is Madeline Gannon. I have a PhD in computational design from Carnegie Mellon university, where I explored better ways to communicate with machines so that that often met robots.

[00:00:30] And I think today we’re going to talk a lot about robots and what our future with them is, how we can live together more desirable ways and kind of how do we navigate this weird future that is coming at us at light speed to make sure it is inclusive and equitable to everyone.

[00:00:50] Nir Hindi: [00:00:50] Great. Madeline. I want to start and ask you your artistic material is technology and specifically robots.

[00:00:56] Now, before we get into what you’re doing with robotics, I want to ask you, how did you find yourself in the space of robots? Why robots?

[00:01:05] Madeline Ganon: [00:01:05] Well, yeah, I actually kind of fell backwards into it. So I really started in architecture, not software architecture, not hardware architecture, like building construction architecture.

[00:01:16] That’s my background. And an architect’s education is amazing. There’s no other discipline that gives you the tools and techniques to dream of something that doesn’t exist and convince people to make it real. Right? That’s all that architects do. And with that, you get a lot of skillsets in how you make, um, new worlds in computers.

[00:01:41] So, so 3d modeling, for example, um, at my university though, the last year that I was there. My university got a CNC router. Now this was in the model shop so when you build your models that, that get your ideas out of your head and into the world, a CNC router is a tool that you connect to computer and it carves away basically a 3d model that you have.

[00:02:04] So I had never really built anything that wasn’t out of paper and sticks prior to that. And this was the first time I could take all my. Digital creativity that I was learning inside the computer and get something out in the physical world almost instantaneously. And that was intoxicating. I felt empowered that my creativity wasn’t hampered by having to rely on someone else to make it.

[00:02:32] And so that sort of led me down this long path towards doing weird things with this machine, trying to get as much time as possible on it, using it to draw instead of car I’m using it to deform. Instead of, you know, basically what I did was found all the ways I could misuse the tool and I hit some limits there.

[00:02:53] And a lot of those limits were from the software, the stuff that talks to the machine to tell it what to do because I CNC router is usually made for like cabinet makers to carve, you know, ornate details out of wood doors and being them. Boom. And I was not, I was asking to do way weirder things and the software sort of prevented.

[00:03:17] It was, it was a hard roadblock for me to continue my explorations and that sort of convinced me to continue my education and learn how to program and how to talk to these machines. So I could create my own software that could do whatever weird and random and wonderful thing that I wanted that commercially available software wouldn’t abide by.

[00:03:39] Um, and so that led me, you know, I was doing my masters in architecture in Miami. And so I, I said goodbye to the beautiful weather and the beaches, and I moved to Pittsburgh to Carnegie Mellon university, where I got robots and programming instead. So it was an interesting trade-off between. Um, and they’re the, the program that I was in had this amazing fabrication facilities with these CNC routers, as well as laser cutters and 3d printers.

[00:04:09] You know, all these different tools that are basically all the same, they just. They manipulate material in different ways, but you talk to them the same way and one of the machines that they had there, they had gotten recently, no one really knew how to use it. It was just sort of sitting there kind of lonely.

[00:04:25] And that was an industrial robot arm. And in learning in my study as is learning how to program and communicate with these machines. The abstractions are kind of all the same. So if you can make something that talks to a 3D printer, that’s a three axis robot. A CNC router is a two and a half. Three again, like three motor robot or robotic arm just has six motors.

[00:04:50] So there’s a little bit more complexity, but it’s basically the same thing. You feed this machine geometry in just the right way and it can come to life. And so that’s sort of how I S I kind of wandered into robotics just by happenstance, because I was playing around with a machine in Miami, doing things I wasn’t supposed to do with it.

[00:05:12] Nir Hindi: [00:05:12] Yeah, it’s kind of touristic that we’ll go back to. I often see it in among artists. So a question to our listeners when you already probably understood that Madeline doesn’t work with regular robots, no money. When I ask you robot, what do you think about often people will think about the Robocop style or this cutie small ones, but the orbits that Madeline is working with are the industrial, the huge one.

[00:05:38]we will add to our show notes, video, how she interacted with one of these huge industrial arms and Mylene. What I’m interested is that industrial robots are designed mainly for human labor, taking heavy stuff from one part to the other, and they are designed in a way to just execute specific task.

[00:06:01] Why change it?

[00:06:02] Madeline Ganon: [00:06:02] Well, I mean, that’s a good question. Right? And so industrial robots, they’re actually a really old technology within the context of robotics. So they’re kind of one of the first robots ever made and brought out of a lab and into a work environment. And it sort of came on to the factory line in the seventies.

[00:06:22] That’s like dinosaur compared to all the other robots that are coming to life now. And they’re really great. And they’re very great at, at automation. it’s a complicated topic. They kind of replace human labor, but they also do things that is dangerous for people or that people just can’t physically do.

[00:06:41] So these machines, what I love about them out of all the robots and I love lots of robots, but what I love most about industrial robots is that they have superhuman power. They’re super humans, you know, they’re Superman. And they can move at, you know, the one that I was working with it, it weighs one ton, move seven meters per second.

[00:07:05] It can hold 300 kilograms to a millimeter precision in perpetuity. You know, like these are the things that we describe our superheroes with. And so for me, if I could just take that thing that was designed to do short, repetitive tasks over and over again forever. And just open it up a little bit so that I could take some of its super powers.

[00:07:28] That’s really what I’m always going after. That’s really what I’m always chasing is how can I have the super powers of this machine and the way I see that is oftentimes it’s just a software, it’s an interface issue, right? If I could communicate with this machine a bit more intuitively, if it could anticipate what I’m doing and what I need now, all of a sudden we’re working or we’re collaborating where I’m kind of connected in a more natural way that I can take some of those superpowers for myself.

[00:07:59] Nir Hindi: [00:07:59] You talk about this sound so compelling. It’s like, you know, you think about the robot and you describe it in a, such a compelling, and I dunno, relationship  humanistic relationship in a way, which one of the things that also it’s interesting is that.

[00:08:14] You want to bring this machines from the factories into our live environment? Why, why, why do we need a robot that can hold 300 kilograms into the regular environment of humans?

[00:08:28] Madeline Ganon: [00:08:28] Well, I mean, there’s, there’s certain environments that like, you know, Maybe you don’t need a robot that picks up a car chassis.

[00:08:34] Even if somebody’s line, maybe you don’t need that in your kitchen. You know, so there’s some for that, but you know, that would be really, really, really wonderful to have on a construction site. Cause now you have this really adaptable machine that can be a forklift. It can be a cherry picker, a scissor lift.

[00:08:54] It can hold something instead of using expensive form work or a material intensive form work. It can just hold it forever while he knows that like you want to cast some concrete, you need to hold something in place. It can just hold it there. It’s not going to get tired. The flexibility and adaptability of this machine is why it’s been so helpful.

[00:09:13] In manufacturing, in automation. And if we could just have more intelligent software, give the robots a bit more contextual awareness of what’s going on. Now, all of a sudden it opens it up to a lot of more applications and a lot of more that the other aspect of this is that these robots are also kind of symbolic.

[00:09:36] For a lot of the newer machines that are coming out into the world. So if you think of, um, a self-driving car and you think of a robotic arm, they don’t look. Oh a lot alike, but in both scenarios you have something that moves very fast. It’s very heavy. It’s very dangerous, also very useful. And that doesn’t look like us and that doesn’t have a good way of communicating with us and that is impacting our lives and sort of joining us in a, in a public environment.

[00:10:05] And so the robotic arms are a more stable, older, more mature technology platform to begin to explore the fuzzy edges of our future with these machines as they kind of live among us.

[00:10:19] Nir Hindi: [00:10:19] You know, you’re talking and I’m getting excited and like, I have so many questions. Madeline, you walk the walk. No ?

[00:10:25] Madeline Ganon: [00:10:25] yeah. Yeah. I mean, I try to, I try.

[00:10:28] Nir Hindi: [00:10:28] No, I dunno, listeners, if you listen, there are some noises in the background it’s because Madeline now not only tell us to put robots in construction sites, she is actually building her new home to live with the robots. Yes. We’re

[00:10:45] Madeline Ganon: [00:10:45] having a conversation from a construction site at the moment.

[00:10:48] Yes. And, uh, yeah. So the story of how that came to be is, is did my PhD. I finished my PhD and, and a lot of the work that I had done had been, because when you, when you do academic research, it needs to fit within a certain confined has to check certain boxes as you do it, to get the degree. And then now that I’m done with that, I just sort of step back and say, wait a second.

[00:11:12] I can do anything. What do I want to do? What’s the next step? How do we take this to the next level? And for me, it wasn’t just, you know, inventing better ways to communicate with these machines. But I wanted to explore how to cohabitate with them. Like that’s the future that’s arriving the self-driving cars, the delivery robots, logistics, robots, the robots that we see in hospitals, the robots that we see, you know, cleaning floors, these machines are here.

[00:11:40] They’re actually here. In our lives. And a lot of them are, are not quite, you know, the future that we hoped for the future that we signed up for. And so what I decided to do is, is actually commit to that, commit to that idea of living in the future and beginning to work out what is the new normal going to be in 10 to 15 years with these machines?

[00:12:04] And you can’t do that when you go visit your robots. In an office, you know, from nine o’clock in the morning to five o’clock at night, you, you need to live among them. They need to live among you. And so that’s what I’ve committed to. And that’s what we’ve been working for the last year. And we’re, we’re close.

[00:12:21] We’re really, really close to being done with this project and beginning to move in with, uh, myself, my husband, our one-year-old daughter, and a whole menagerie of machines for her to grow up around,

[00:12:36]Nir Hindi: [00:12:36] You are saying things that kind of speak to my heart. Like one of the things that I’ve noticed, and I always work in the world of entrepreneurship and business.

[00:12:45] I always say that business, especially business in order to get better, they need to look to the past in a way and improve it. Yes. Artists always look to the future and try to create it. And I feel that in this space, there is a lot of room for collaboration and mutual learning. And the fact that you are saying, this is a future of 10, 15 years, but you’re already creating it today.

[00:13:10]  I always find it fascinating why artists actually doing it, why they take it upon themselves to create this potential futures that often we discuss, but artist live.

[00:13:23] Madeline Ganon: [00:13:23] Yeah. I think we have a lot of permission from society to be weird. To be abnormal to really push out the limits. Right. So I think that that’s part of it.

[00:13:33] I think, um, also artists are, especially when you work in technology and you’re, you’re trying to push at the edge of the future of that technology. They’re competing against corporations that have R & D departments of 30 40 50 people working on some of these things. And so to be competitive in that space, you have to go further out.

[00:13:58] You have to go in and sort of wander and scout terrains that aren’t immediately. Applicable or relevant to corporations that maybe are looking at a 3-5 timescale, right? You have to go further out 10 to 15 years. And if you have a good nose, they can kind of, sort of like smell and tell the direction of where things are going.

[00:14:22] If you keep your eyes open along, along the way then all of a sudden you find yourself in really relevant terrain in, in that timescale. So is everyone going to be living with next year, like robot arms on their desk next to them?

[00:14:37]Nir Hindi: [00:14:37] you cannot see it. Maybe I will post the picture after Madeline just showing us now the environment she built and there’s already a robotic arm over there with  her new 3D printer.

[00:14:46] Madeline Ganon: [00:14:46] Right. So maybe, you know, that’s not everyone’s reality in 10 to 15 years, but like you can begin to abstract this to very, very normal things. Like for example, standing desks, standing desks are very dumb robots that people have in their everyday lives. Now, when that standing desk can talk to your window blinds can talk to the doors or the shades, or, you know, all those things become connected and more integral into a.

[00:15:15] On an articulated environment. Now, all of a sudden you’re getting towards that more robotic future that is maybe 10 to 15 years out.

[00:15:24] Nir Hindi: [00:15:24] I want to ask you a question. Now, a few weeks ago, I spoke with Jim McKelvey who is a well-known entrepreneur, but he’s also a glass artist and we discussed one characteristic that he thinks that only entrepreneurs and artists have in common it’s audacity.

[00:15:38] And you already started to speak about it, that going into this 10, 15 years a future. And when , we spoke in the past, you said “my goal is to do something nobody did”. And I’m asking why or where, where does it come from this desire or. Aren’t you scared to go to places that nobody has been before?

[00:16:01] Madeline Ganon: [00:16:01] I mean, I guess maybe I just have the characteristics of an Explorer for me.

[00:16:05] It’s like, why would you do something if someone else can do it? That’s for me is the hard stop is like, there’s a lot of folks that are doing really, really beautiful, interesting work. Highly technical work doing like, um, filmmaking with high-speed robotics. And I’m so enamored with it. And like, I have all the tools to do it and to do it kind of in an interesting way.

[00:16:26] But I feel like for example, there are people doing that and so, okay. That terrain is been scouted and it’s been mapped out and there’s a paved road for people to go there for me. I want to take the machete and cert. Cutting through the jungle to see where the new worlds are too, that may or may not even be interesting if you’re an entrepreneur.

[00:16:46] If you’re a researcher, if you’re an artist, what you really are is an Explorer. And when you find new land, Oftentimes, you don’t want to now create a town you want to, okay. You want to pass it, pass it off to someone else and go find another new place. You know, it’s just this constant curiosity, at least for me is, is what drives me to go further out,

[00:17:09] Nir Hindi: [00:17:09] by the way, we didn’t talk about it, Madeline, but that’s exactly also what Jim McKelvey said. He says artists and entrepreneurs, are explorers and the rest are tourists. They have a map and you know, they just follow the map. artists and entrepreneurs go exactly. As you described it. Very interesting. And you haven’t talked yet, so I want to kind of ask you another question about one of your work, but before that, let’s take a short break.

[00:17:34] Hey, thanks for coming back. We are speaking with Madeline about industrial robotics and the future call living together. Madeline, one of your works it’s called Manus. It’s a group of robots, maybe. I don’t know, in the video I so 15 or 20 standing a kind of a row long row. And they interact with human. Now this robots, a group of a one arm robot with kind of an eye that looked at us.

[00:18:02] And like other works you are doing, there is an element of randomness in a way I can imagine myself entering, looking at all those 20 one-eye robots arms looking at me and knowing the doubt random, which means they don’t do what I tell them kind of can reinforce the fear of human of robots because you add this randomness to robots to do what they want.

[00:18:29] First of all, why you add this randomness to this work with robots?

[00:18:35] Madeline Ganon: [00:18:35] Well, I wouldn’t necessarily call it randomness. I would call it autonomy for us is perceived like random, but they have their own agenda. They’re programmed to kind of do what they want, respond to their environment, but really with this idea of autonomy and that project in particular was an invitation from the world economic forum to help the visitors for their, the annual meeting beacon to think about what our future art with these machines could be for the fourth industrial revolution. So as an artist, I saw it as an amazing opportunity to put something in front of policy makers, you know, the people who are actually going to impact how this technology enters into the society across the world and get them to think about.

[00:19:23] Ways that this technology could be rather than continuing on the path that we have now. So the idea of autonomy is really what we’re working towards, both inside and outside of industrial manufacturing. These machines are getting smarter, they’re getting more aware of their environment and as a consequence, they’re able to make decisions without us explicitly telling them to do something.

[00:19:49] And that can be a great thing. It can also be a scary thing. The idea is to highlight both with a lot of the work that I do with these machines. I try to tell people and show people that they’re not, they’re not pieces of manufacturing equipment. They’re actually creatures. When something happens, autonomy, it behaves without us telling it to do something, just like any other animal or person that we interact with on a daily basis.

[00:20:18] And you and I there’s social norms. There’s cues that we have that let us co-habitate and interact in a pleasant way, in a productive way and what I’ve been working towards is trying to find those same cues and show that we can transcribe those same cues onto these machines that look nothing like us.

[00:20:43] And we can still respond to them in that same way that you and I, even through a video call, you know, our body languages is still resonating with one another.

[00:20:53] Nir Hindi: [00:20:53] Do you think we should be afraid from robots?

[00:20:56] Madeline Ganon: [00:20:56] Uh, I don’t think that that matters. I don’t think my opinion on that matters whether we should be afraid or, or a few of us. I mean, I’m in a privileged position to be working in this field,

[00:21:07] Nir Hindi: [00:21:07] speak about the robots like their kids, you know, it’s like, they’re sweet, like autonomy. They have their own autonomy. And when I see you, this video that you have that you did at Autodesk this with this huge arm is like, we are so small compared to this.

[00:21:23] Madeline Ganon: [00:21:23] Yeah. Yeah. That’s also why I like working with industrial robots because they’re these massive beasts of machines that, you know, it’s very evocative to be. And if you feel like a lion Tamer, so does everyone need to be a lion Tamer? No, but it’s kind of fun to do it. What I’m interested in is not, should we, or shouldn’t we be afraid of these machines, but it’s really.

[00:21:51]take this technology that is kind of found in industry it’s found in academia, but it’s not really found in culture. We sort of made up our minds. As a society that we don’t want these machines to be our overlords. We don’t want them to be our slaves. We don’t want to be their slaves either.

[00:22:11] You know, that there’s consensus across humanity for that. But what we have decided is how do we want these machines to make our lives better, to augment and expand and enhance our daily experience of life. So that’s why I like to work, take, you know, work with policymakers to work in cultural institutions, sort of take these ideas out from a handful of people who know how to use this technology and bring it to wider audiences so they can start to build an awareness of what this technology can and can’t do, but also begin to grapple and chew through and, and make up their own opinions about what does could be or what they might like about it or what they’re very distrustful of. I think that that’s really the most important thing?

[00:23:00] Nir Hindi: [00:23:00] Yeah. Asking questions and not just accepting as the reality as is one of the things that I’m positive listeners can hear in your voice is that you are speaking about in a very positive and optimistic way. And I have a very good friend that always says that we always tend to show the negative aspect of technology instead of speaking about the positive influence of technology and why you feel compelled to look at that and to make us maybe look at the whole boats in a more positive or optimistic ways? Because just last month, the world economic forum published the future of jobs, 2025. And in it, they say that I remember now the number 50%, 60% will be replaced by robots. So a lot of people, it’s also kind of a concern for their livelihood, but still you maintain this optimistic and positive. What will you tell them?

[00:23:58] Madeline Ganon: [00:23:58] I think their concerns are valid. I think their concerns are, are just as well. I think not only with robots, but also software, right? Automation that’s happening in software. The reason why I have optimism is because I focus on the future. That’s the way that my brain is wired. Um, focusing on the task, focusing on the present, they are the fuel, at least for me, that helps me burn the light that looks towards the future. And. For everyday people, automation, robotic automation is having an immense impact on their daily life, in the present, especially in Asia and in China, China has, uh, adopted robotic automation, a higher rate than the entire globe put together.

[00:24:43] Right. So they’re going to begin to feel that in their labor market as well. Um, would I, so there are folks that are working on. Equitable policies for integrating automation into the workforce and different type of economic structures and social structures and safety nets to help ease the transition towards your value in society, not being directly linked to the time and labor that you put in during the week.

[00:25:13] What I’m trying to do is chart out new paths, forwards new metaphors, new frameworks for using this amazing technology. So we didn’t have to, automation was not an inevitability with this technology in the sixties. Uh, when these machines were just coming online in general motors, in other manufacturing contexts, at the same time, there were artists and computer scientists building these machines that actually had personalities and that responded and reacted to people that had curiosity that had creativity in mind.

[00:25:47] And what happened was that the economics of automation won out over the economics of companionship and curiosity and creativity for these machines. So I feel like for me, the gauntlet that I try to bring towards the future is sort of picking up what was left off in the sixties and sort of exploring if now’s the time and that we can actually revisit those ideas and make them a reality.

[00:26:16] Nir Hindi: [00:26:16] Do you have some recommendations for what, which artists we should check from the sixties?

[00:26:20] Madeline Ganon: [00:26:20] So there’s this amazing, uh, exhibition that happened in England called  cybernetic serendipity. And there’s a treasure trove of amazing work there that really got to the heart of just crazy people exploring what this new technology could do and what it can mean to us.

[00:26:39] A lot of it goes towards representation. So people drawing or painting, carving with machines. Um, but a lot of it also was, was like actually trying to make mechanical life. I like, that was amazing. And they did it like they didn’t have computers really then like the computer was such an odd concept. It was like with like, Hydraulic pumps.

[00:27:01] And it was just like, I have no idea how they did what they did because you know, like I could recreate it now with all the tools that I have, the amount of, of innovation and ingenuity that went into bring these creatures to life. I was really, really spectacular. Uh, one of, one of my favorite artists is a guy named a Dutch guy named Edward Ihnatowicz.

[00:27:25] And he had this sound activated mobili, Sam, that was this creature that would listen for you and reorient. It’s like really ornate vertebrae spine and its face to look at you as you are around it. And you know, if you look at that work and you look at my work, there’s like a direct line between just kind of interaction and engagement, and that to me is, is really what a lot of what I explore in my work is that, you know, what the robot is doing is it’s giving you its attention. And that is, especially in this day and age, uh, giving someone your attention is such an act of generosity. And even when a machine gives it to us, we sort of feel a connection to it because of that generous act.

[00:28:11] And so that’s, that’s, you know, that’s a single dimension. Of exploration that week that I’ve been digging into with our relationship to these machines are there’s so many more dimensions that, that people that come from different backgrounds, different value sets, different worldviews, different disciplines could begin to layer and explore into our future with these machines.

[00:28:35] If the technology were more open and accessible and relatable to those people,

[00:28:41]Nir Hindi: [00:28:41] if I may add to your last comment. I think if people will be open-minded to these technologies and not scared from them, I think we can have much more collaborative opportunities as, as you just speak about it, because listening to you is it raises a lot of kind of questions.

[00:29:01] Why we perceive the Robotics world as we perceive?

[00:29:04] Madeline Ganon: [00:29:04] Yeah. I want to reiterate that those fears are valid. When you’re working manufacturing and the plant starts to integrate robots, it’s a scary feeling and it happens right.

[00:29:16] But there’s a shift now that needs to accelerate towards those rather than, and Tesla kind of admitted to this with their factory as well, that working with robots plus people. Was more effective, more powerful than just doing robotics or just doing people. So to find those points of engagement, where robots plus people can be greater than the sum of their parts, I think is, is really wonderful.

[00:29:42] Right? You use the robot with the robots. Good for you. Use the person for what the person’s good for and you build the interface, the software that connects them into this more integral system.

[00:29:54] Nir Hindi: [00:29:54] Great. So that’s led me to my next question, because you spoke about innovation. You spoke about creativity and you spoke about creating this software and you actually created one.

[00:30:03] And in your work, there is a kind of potential for innovation that I see. Your robots respond directly to human action instead of the type a commands most all about relay or so instead of pre-program command, that probably are very good for more secure or more repetitive work environment. In yours it’s very difficult to kind of pre-program because the orbit itself needs to thrive in a dynamic environment. Something happened,   they respond. So you develop the Quipt, a control software for robots that act as an interpreter, translating human motions into instructions for the robot. Tell us about this Quipt.

[00:30:45] Madeline Ganon: [00:30:45] It basically helps a robot understand our body language and it responds with its own body language. And what’s really wonderful about that. We have verbal communication. We have written communication, but nonverbal cues, nonverbal communication is something that is broadcast at such a primal low level of frequency across people across species.

[00:31:09] That it’s something that we can’t turn off. And so it doesn’t have high fidelity. I can’t do body language and communicate the same way that if I were to just tell you a sentence, right. But at a low level for low-level States of mind, it’s an amazing trip for that information. Just as an example, like if you have any pets, you know, if you have a dog or if you have a cat, you know, you know that if it’s ears are back.

[00:31:36] Kind of feels threatened if its tails between his leg, it feels threatened. If it’s tails wagging you’re as happy, right? These kinds of non-verbal cues that it knows that, you know, when it, when you sort of make a certain face and sort of tower over it, that it’s done something wrong and you probably shouldn’t have eaten the garbage out of the, like, there are certain things that I just know when we co-exist with different species that makes it a really enjoyable and meaningful relationship across these two things.

[00:32:03] So with robots and that’s a lot of what I’ve been working towards is building this kind of repertoire of body language and ways of, of having it be in a flow, just like we have with other living things. So for Quip to particular is really like, I was really fortunate to be in an artist residency at the software company, Autodesk, they had this amazing facility called pier nine.

[00:32:30] That was just chock-full of CNC machines and robots. And like, it was like being in a candy store for me. It was amazing. And so they had this. Big a one ton robot, ADB IRB, 6,700. But again was, they just got, it was just sitting there. They didn’t really know what to do with it. And they also had this motion capture system, which there are cameras that can sense three-dimensional space.

[00:32:53] And so if you’ve ever seen, like on a film set where they make actors wear these suits with little dots on them, it’s the same technology. And so for me, I saw like, Oh, here I have a robot that can move in the world, but can’t see. And here I have cameras that can see, but not move well. I just built some software to connect the two.

[00:33:11] And by making that, and by having that kind of continuous fluid feedback interaction between how I was moving and the robot responded, it sort of became apparent, you know, as much as I was impacting the robot, how it moved and how it was moving was also impacting me. I wasn’t expecting to feel a connection or to feel an emotional response to how the robot was moving.

[00:33:37] But lo and behold, as soon as you make something, move in an adamant way, um, that response is attentive to you that we as humans sort of project our own emotion onto it, and we can’t help it. It’s kind of like hardwired into our, our primal monkey brains.

[00:33:54] Nir Hindi: [00:33:54] What did you feel the moment you saw this connection?

[00:34:01] Madeline Ganon: [00:34:01] A little puppy in the lab that was just really happy to see me. Um, you know, as I was programming it, you know, like sometimes it would be very, very jittery and move around and that kind of seemed like it was excited. It also made the motors of certain motors move, which have a higher pitch sound or a lower pitch sound.

[00:34:17] So it’s not, it’s like a multi-sensory experience where it’s not just kind of the spatial. Interaction that you have, but you can also hear the sound and you know, you’re not supposed to touch them, but also it was a little bit of tactile interaction too.

[00:34:31] Nir Hindi: [00:34:31] I wouldn’t call it the puppy. Move in elephant height or giraffe height.

[00:34:37] The toe total is this. Yeah. Um, You mentioned that this artist in residence, and I wonder you worked with few companies, how has this experience working with companies? Why should he, you want to work with them? Why they want to work with you?

[00:34:57] Madeline Ganon: [00:34:57] What I get out of it. A lot of what I get out of it is, is access to expensive equipment or space.

[00:35:03] And what they get out of it are a prototype of their future users, at least in the case of Autodesk, right? So they are for their artists and residents. They brought in a group of people who are doing really advanced things, but oftentimes don’t even use their software because their software caters to the masses.

[00:35:21] It has to. You know, economically it has to cater to what most people want. And so here are these fringe people doing fringe, weird things that get them sort of, kind of like just plants, a little flags to see, like, is this actually an interesting direction to go to? What sort of innovations are you have?

[00:35:39] What are the limits of our tools? What are what’s the low hanging fruit to sort of build as features and what is like, would need a total overhaul for it. So I think at the end of the day, I hope that it’s, you know, A win, win, win situation, where I get something out of it, they get something out of it and us together get something that we couldn’t get apart.

[00:35:58] It’s not purely transactional, but I, I think that at least in the case with Autodesk, that, that they got the better deal. I got some access to equipment, but the several years of cohorts that they’ve done, they’ve been able to actually hire a lot of these interesting people as well. Um, so that’s like great for talent acquisition.

[00:36:17] They’ve been able to have basically affordable consulting on and feedback from advanced users for what their soft credit software can and can’t do. And they’ve been able to get a sneak peek of what’s coming in the future.

[00:36:32] Nir Hindi: [00:36:32] One of the things you mentioned when I asked you about that this resident is that you want to move the needle, how the technology of those companies actually can be more human.

[00:36:40] How are you feel you want to do it then? How did they respond to this desire of yours to make technology more human?

[00:36:48] Madeline Ganon: [00:36:48] Well, a lot of the, kind of like a lot of principles of human centered design is it’s still very, that’s still sort of like design thinking is something that has. Sort of tra traversed from design school, into the design discipline over into industry and human centered design is not quite there yet.

[00:37:10] Right? So, so if you have a project manager developing software, perhaps they’ve done some design thinking training on it, but, but human centered design is something that’s still is. Hasn’t sort of. Risen to popular enough frame of thought to sort of carry over into these new disciplines. And I just find it very, very powerful, um, way of thinking about these things that is basically like for a lot of things, it’s like, don’t make software that needs a tutorial, right.

[00:37:40] If it’s not intuitive enough for people to just play with and pickup, then you’re doing it wrong. Yeah.

[00:37:45] Nir Hindi: [00:37:45] Beautiful, great, great advice

[00:37:47] Madeline Ganon: [00:37:47] Yeah, exactly. Yeah. Um, so, so that’s, that’s kind of a one aspect of it. And I think at the end of the day, the goal is not to make technology more human. The goal is to make technology more relatable, more relevant and to, and more empowering at the end of the day.

[00:38:07] Right. So it’s not, it’s not like, um, especially in, in robotics, I think. It’s sort of the opposite. You don’t wanna make the robots more human. You don’t want to make the robots look like us. What you want to do is make them more relatable, more legible that people intuitively understand what they’re doing without looking at a screen without reading a manual.

[00:38:31] Well,

[00:38:31] Nir Hindi: [00:38:31] I always say that art is made by human. For human. So art by nature is human-centric. And you just said it. I think you nailed it when you say it hasn’t become yet a way of thought or way of thinking. And that’s what I feel. I feel that, you know, design thinking and lean startup and maybe agile development, those are great methods, but it’s not yet the mindset that you would like to see because everyone has access everyone has access to those tools, but still you don’t see a lot of innovation or a lot of human centric design results in that sense. So it’s very interesting, we’re getting into the end of the podcast and I definitely can continue this podcast for another two hours.

[00:39:17] I don’t know. You probably have your own day, but I want to kind of ask you maybe one or two final questions. What is the most exciting advancement you see today in robotics?

[00:39:30] Madeline Ganon: [00:39:30] I mean, hands down, it is the, the amazing developments that are happening in machine learning and artificial intelligence, and basically what has been pretty reliable and pretty useful. So, so let me, let me step back for a second and say like artificial intelligence is also this really scary term for a lot of people. And a lot of it is hype. A lot of it is I think, a bit overblown, but what machine learning and artificial intelligence can do really, really well is look at a lot of data.

[00:40:04] And when you see something new, it can build a bridge from what you have seen to what you. What you’re seeing right now. And what that means for robotics is that you don’t need to program every possible instance and scenario for that robot to do something, which now if something new happens in front of a robot and it doesn’t know what to do, it crashes.

[00:40:25] Great. So there’s no possible way that if these robots are going to be truly autonomous, that I can enumerate all the possible scenarios that could possibly have into this robot across its life for, for it to, uh, successfully exist. And so machine learning is sort of bridging that gap between old knowledge and new knowledge for, for these machines.

[00:40:48] What it also does is it makes Working with cheaper sensors, cheaper equipment, a lot better. So something that we like you would need like a $10,000 sensor for a robot to be able to do a task accurately. Now, all of a sudden you can do it with a webcam or you can do your phone because machine learning is there to sort of fill in the blank spots of that data set.

[00:41:13] So that that to me is, is really, really exciting. Um, because of what it means is that this technology is no longer limited to the people who can afford, you know, million dollar labs. It’s really coming down to, if you’re a kid in high school and doing a science fair project that you live in, you have an opportunity to be really innovative.

[00:41:35] You have an opportunity to make a discovery that makes impact. That, that to me is really, really exciting.

[00:41:40] Nir Hindi: [00:41:40] One last question you said. In past interview “They, the robots connects with us in a meaningful way that is the future, I want to live in” describe me this future 15 years from now, how it will look?

[00:41:53] Madeline Ganon: [00:41:53] Oh, that’s a good question. I mean, I, to be honest, I don’t really know. Right. So part of being an Explorer is not quite knowing where you’re, you sort of have a heading, but you don’t have a finish line. Right. So part of what I’m setting off to do is, is, um, find out what that 10, 15 years looks like and, and report back to the rest of the world.

[00:42:15] What that is

[00:42:16] Nir Hindi: [00:42:16] great. I love it. I don’t know about you. Probably the listeners does know that already. I enjoyed it. I hope you enjoyed as well.

[00:42:26] Madeline Ganon: [00:42:26] Very much.

[00:42:27] Nir Hindi: [00:42:27] Yeah, very kind. And I envied the orbits that they spent so much time with you.

[00:42:32] Madeline Ganon: [00:42:32] So

[00:42:34] Nir Hindi: [00:42:34] thank you very, very much for taking the time and sharing all your great work.

[00:42:38] I would highly recommend you guys, the listeners check Madeline’s work. We will have on our show notes, all the links for things she mentioned. Madeline. Thanks again.

[00:42:49] Madeline Ganon: [00:42:49] Thank you.

[00:42:50] Nir Hindi: [00:42:50] Have a great day back in Pennsylvania.

[00:42:54]