Transcription
Uh, now Rafi, before we get into it, uh, I remember hearing from you that when you were eight, you watched a film. Tell us about this film that really shaped you.
Yes. So I was super excited to watch my first science fiction movie. Yeah. As a child, while looking for the beauty of life and positivity of life, Blade Runner, it was a fascinating experience. Uh, I didn't know English, my my cousin translated. I hope he did a good job. And it was a beautiful dialogue about, I remember two androids sharing their worlds. And I asked like, what are they saying? And he said, he says, it's not your memory, it's someone else's memories. And that, as a child, the feeling of like, how two androids or humanoids in conversation, through the lens of a child's mind, of a positivity, seeing the downtown Los Angeles, flying cars, like, like the mediocre of the future, I just can't forget that feeling.
You were thinking a lot deeper than I think most 8-year-olds that I know would think about. Was that always you as a child?
I mean, it, it was this um, the similar time. I was also very lucky to have the first computer, Commodore 64.
Oh, wow.
It was a coincidence. My mom brought home this for like, a birthday gift. And I, I, I just can't forget the feeling of programming games, to be able to like, look at the, the door, the floor, the ceiling. Like, everything was in the games were changeable and editable. And I was coming back to the room and looking how boring the physical world and why like imagination doesn't apply to the physical world. Um, so I think they all meet at the same kind of a year.
So you always wanted to escape to the metaverse where you could just manipulate anything.
As much as. You eventually actually ended up in Los Angeles, but a slightly less dystopian Los Angeles, the Los Angeles of today. What brought you here?
So thanks to my partner Essun, also. I was, we were like together at the undergrad years at Istanbul, studied visual communication design and photography and video. 2008, I coined the term data painting. The idea of like, seeing information, not just a number, but a form of memory. The idea of like, what happens if the information of life, I mean, it can be heartbeats, brain signals, and Wi-Fi, Bluetooth, anything and everything we can quantify through sensors and machines. Could they be like, a form of like pigmentation? And it was an undergrad last year epiphany. And then I was super inspired by the media architecture. The idea of adding media into architecture, going beyond glass, steel and concrete. And and and that was the year I felt that UCLA Design Media Arts department, where I am teaching last 10 years.
Okay.
Fascinating place for that.
So, I mean, did you view computers, data, digital displays as a medium from the very beginning, or was it something that you developed along the way as you discovered what it meant to be an artist?
I think the, the idea of mind's eye as a computational practice. So I, I don't know really how to draw very well. I'll be super honest. And uh, and I, I have kind of a form of like disability when it comes to like mind's eye to the paper. But I found myself pretty much excited about the idea of computation, like finding geometry, colors, moods, and forms and shapes through algorithms, uh, or 3D, you know, design techniques, computational design, and eventually now AI algorithms. There was a happy place for the mind. And I felt that, um, that was a first learning this mind's eye meets the digital algorithms and find a connection. I mean, it's now 16 years. I still don't feel it's finished, but um, there's a joy there that I think.
A lot of people are kind of discovering AI for the first time right now. And it's obviously in a huge number of tools. It's obviously in Canva as well with the launch today. And you've been working with it for a long time now, and you've, you've experienced it. I, you know, you've used it, you've coded with it, you've worked with it. Uh, and you've described it as a mirror who reflects who we are. What does that mean?
So I think if you think about the fundamentals of machine intelligence, it's truly that comes from the data that we left behind as humanity. And I have been super inspired very early days of AI, 2013, 14, summer. I remember, um, very early, like, um, algorithms have been used for image pattern recognition. But I was not very sure about like, how it can be applied to creativity, because early days of AI was really understanding the patterns of life in general. Um, so I remember in my thesis, like, in the grad student, I was just dreaming that one day, the buildings can remember, can dream. And it, it was my like, kind of a, I guess, student context that for a building to dream, it has to find a way of like, a memory, which is data. And it has to find a way, a mind, or like a machine intelligence. But it was like, old speculation. And then 2016, I was very fortunate. One of our first projects as a studio, uh, was in San Francisco. And then we received beautiful response from the engineers of the field. And I got invited by the, I think Google's AMI program was just starting. Maybe some people remember, there was this very awkward image that animals were appearing and disappearing.
Yes.
I felt that, oh wow.
It was very trippy.
Exactly. Like, I mean, if a machine could dream, perhaps this could be a way of like, understanding that world. And that's the journey started. For 10 years, we collect more than, we work with more than five billion data sets and train more than 400 AI models. And I think it was a journey of inventing a thinking brush.
What was the very first kind of AI artwork that you worked on?
So 2016, uh, February was the residency started. Uh, I'm super grateful for my mentor and also teacher, was of course, and a curator and a researcher from Istanbul. He has been working with a international, is a libraries interconnected. They're all open source libraries, mostly cultural. He had 1.7 million documents, and they were like working on it, nine researchers for six years. And they said, this open source data would like to think about. And I said, wow, this is a perfect time, maybe imagine archive dreaming. The idea of, if the archive where we learn the truth and and understand our history and life. Yeah.
What happens if a machine can dream?
That was the first time we apply machine learning algorithms. These are like, uh, image recognition algorithms. And that was a time I asked a question, if a machine can learn, can it dream? Can it hallucinate? Because we artists always like asked a question that are generally unusual. And for me, it was, what is beyond reality? And that was a kind of a fun way of like, okay, can it be answered through these techniques and you know, algorithms. Um, still trying.
And it's not just technical folks who love your work. Institutions like huge cultural institutions like MoMA have exhibited. And you actually had your unsupervised artwork hanging in the lobby. It was gigantic. What did that moment mean to you?
So, first of all, I heard this joke from one of the gallerists. They said, "If you're an artist not alive, the best option is Lur Museum. If you're an artist alive, the best option is MoMA as a museum." So, happy to be alive and be at MoMA. And I didn't also know what does it mean to be a viral artwork at MoMA. So the work was started in the pandemic, thanks to our curators, Michelle Ku and Paul Antonelli, legendary curators who have been collecting from Mario Pac-Man to all the like incredible pioneers of art world for 200 years. It's an honor to touch that data for me. And seven actually, eight years ago now, they put the data on GitHub. It was available. It was open source, but I think nobody used it. And there was a moment that we just discussed, like, can I try to use this data like to make art? Like, exactly that's the reason we are now in his meeting. And thanks also Jensen Huang, our like wonderful collector and and supporter. Um, we asked like, Nia friends, can.
Founder, CEO, and founder of Nvidia.
So we asked for, is it possible to use supercomputers to try something never done before? So we took the, uh, almost 100 years of 138,000 artworks that are ethically collected and let the machine find a new kind of a vocabulary. But to make it different than any other artwork, we did, we think about a living painting. The idea of artwork not only just listens and hears, but feels the weather of New York. Once those things come together, artwork starts to dream or hallucinate. Yeah.
And that was, I think, a breakthrough moment for the generative AI art experiments we received. So, first of all, it was a three months exhibition, and then it was the audience reaction was remarkable. And it, it extended four times for a one year, the longest exhibition. And we received three million people, the largest audience in MoMA history. But and most importantly, it was the first generative AI artwork in the collection. A positive news for anyone working with creatively with AI. I think it was a great message, great signal for other artists and creatives. Uh, the medium became, I guess, um, clear. And then the average viewing experience was almost 38 minutes.
Yeah. And you're clearly pushing the field forward and helping others, you know, follow the same path as well. Fingers crossed that you're not going to be in the Loo for a while.
Um, and all of this work has actually been building towards Data Land, which is, I got a sneak peek of it earlier, uh, last week. Uh, it's not quite open yet. But I know it's been a long journey to get there. But can you tell us what it's all about?
Yes. So a dream project, life's project, we call it with Essun, my partner. So deeply grateful for MoMA, Guggenheim, Pompidou. These are incredible institutions. They are like the most important museums in the world. And I'm so grateful that as a studio, um, we were able to execute artworks, experiment with amazing data sets, and receive remarkable audience. When it comes to the challenge of art making through technology, it is absolutely very challenging for institutions to bring complex, um, data science, complex media technologies from screens to projectors to sensors to supercomputing to cloud computing. It is a remarkable challenge for, um, already existing physical spaces. So I love architecture so much. I have so much respect and love for from Frank Gehry to Gaudi to Zaha Hadid to like Norman Foster. I'm honored to like look at their life and their work. But I was like finding some form of a missing gap when it comes to digital arts, because digital art is generally born in the in the machine space or digital space that we can't touch yet, but it's in our eyes and minds. And I felt that perhaps is a great opportunity to think about an institution from scratch and be present right now and imagine what's going on in humanity right now. The speed of AI, innovation, computation, quantum comput. Like, there's the amount of change every single day is remarkably different than a museum is designed for two years ago.
Yeah. So we felt that what happens, we take this new vision of life, applied to an architecture that is not only is concrete or a steel or glass, but has some form of intelligence and empathy in a way that art could be different.
What does that, what does that mean? How does a building have empathy?
So that's a beautiful question that that I've been asking since as a childhood, right? I mean, since I watched Blade Runner, still looking at the walls and the ceilings. Like this room, for example, where we are, the memory of this, of course, goes online, so forth. But the physical space is just a shell. We felt that what happens if the HVAC system, the power system, the network, the sensor, the media is truly cohesively designed for a world that we are entering very soon, which who knows, maybe we have AGI in a couple of years. We have, I mean, robotics coming. The society is changing so fast. How to represent this for the empathy part? I mean, I'm unfortunately lost my uncle from Alzheimer's. And it was a very powerful and emotional and moment that I realized the same year I received my residency for AI, the same year I learned that. And I asked this question always, the moment of remembering and being human, as much as AI can come, being human in our, in our, I guess, emotions and spirituality and understanding life. I felt that this was sometimes missing in digital arts. And we've thought that if we take this vision of understanding humanity and technology and ethical and sustainable AI, we find this new art form. So I'm calling this little bit generative reality, because we are in the age of seeing and feeling and smelling and remembering things that are we even sometimes don't know what is real, right? It's a new form of era we are entering. It's not XR, not VR, not AR. They are amazing technologies, but they just don't still feel what's going next for us. So the museum will understand these patterns, experiment with sensors, real-time AI applications with ethical data sources and sustainable compute practices with the education, learning, and the collection in mind.
And I've walked through this space. It's incredibly well-crafted. It's an amazing experience. You've thought about the curve of the walls as they meet the floor. You've thought about the journey that people go through. I feel like that's something that not a lot of artists have to deal with. They don't have to think about air conditioning systems and ticketing systems and the business model of their artwork. Is this a bit of a rarity in the art world?
I think so. Because first of all, being independent, I, as an art studio, we have this chance of learning so much about the art society, creative industry. And thanks to Essun, my partner, we really deep dive in understanding, um, the mechanics of the world that that art and the creativity happens. But what, what we learn is, um, by the way, all our collectors and supporters in the journey, join the forces, which we are so grateful. And also, I mean, this is like, maybe an amazing moment, like joining Ivy, I mean, who has a huge respect and love his work. He even said that it's a kind of the iPhone moment for a museum for architecture, because we meticulously work on being sure that technology is not present, but it disappears.
And I felt that when we do a show in an exhibition in a museum or gallery, we sometimes, okay, here's a piece on the wall, here's a computer, here's the cable, here. But the, this really, we want to like, change this feeling of the magical moment when technology disappears. We as humans are the present and the center point of the experience.
You've called your, you've called data your pigment and neural networks your brush. And you've talked a lot about data before. How important is it to your work and like, how do you go about finding the right data and then actually working with it to create something beautiful and moving for people?
So it's a great question. To me, data is an invisible poetic force of form of life in this new era of life. So we are so grateful over the years, we received so many collaboration requests like from the Mama La Harmonic, NASA, JPL. Um, I can count many wonderful collaborations over the years. But what I felt the largest challenge was the data sometimes comes unstructured. By the way, people sometimes forget how hard it is to make a custom AI model from scratch with a millions of images.
Yeah.
So for Data Land, we took a very serious, um, response to the current AI, uh, movement. Uh, we decided to create a custom AI model called Large Nature Model. This was a special research three years ago. I remember the first Large Language Model to arrive. I love nature. I respect nature so much. I believe it's the most important thing we have. It's a living intelligence of life. But I felt that these are the, these models were like, lack of understanding it. They were hallucinating. They were coming up with like, you know, wrong assumptions. We felt like, okay, what happens? We start from scratch. And this time, pay attention to nature in mind. So we received by permission, by questioning and asking, we receive half billion, 500 million images ethically.
Wow.
One of our great source of, uh, truth and, um, archive is Smithsonian Archives, incredible archive and research. And then we ask again, uh, support from our, uh, tech partners to train these models ethically and also sustainably. And we now have a model called Large Nature Model.
Okay.
As a 49, four, 39 million articles, precisely learned and understood from the nature patterns. Instead of hallucinating nature or or replacing nature, I thought that maybe now it's time to have a chance to have a conversation with nature. Maybe AI, I can now help us to have this unheard algorithms and unheard language of nature. Maybe we'll have a discussions and conversations, not to replace it, but to listen to nature.
What does that look like? Does it look like ChatGPT with Mother Nature?
So it's an interesting experiment. Um, so I also found that, um, the current Large Language Models are incredible, but they're a little bit like, to me, already like elasticated. So the idea of typing and chatting feels to me, it's beautiful. It's amazing that I'm, I was chatting, I guess, all my, I mean, I, I was very fortunate to witness the birth of internet, web one, two, three, and AI and quantum. But I, I always felt that there is this moment that just typing and chatting sometimes feels a limitation of language. So Large Nature Model is trained on not only just the words, not the sound, but the smell. So this model can have the, the scent molecules inside.
How do you get scent data?
So that's an exciting. In in two months, in a couple of months, we'll, we'll share this. So at Data Land, this model is, uh, real-time working as a living museum. Will be able to give us, uh, incredible scent experiences, sound experiments and experiences. We collected more than 100,000 hours sound recordings from more than 20 rainforests in the world.
You actually sent out your own folks to do recordings.
Yes. Wow. Which was a very different than just a finding data online, but we contribute to open science, be able to share with the communities. And then lastly, which is a very inspiring data for me, the time for nature is very different than time for humans, right? We, as we all have a life, but what we felt that the beautiful information how the water flow through trees, how the humidity changes, how the weather, how the rain and how the wind changes. And we also collect this beautiful patterns of nature. So the model has his sensitivity to the nature, not just, I guess, books or articles, but in a way as sensing something different that beyond the human sensory and time perception.
I love that you highlighted that nature experiences time in a totally different way to us. And like, one of the most moving experiences I've actually had was here in California when I visited Sequoia National Park. And you're seeing these immense trees that have been around for thousands of years. And I just thought of all the people flitting around them like little mosquitoes. And these trees experiencing us as humans is just this fleeting moment in their full lifetime. And getting to experience that and understand that in a unique way, I think is what the heart of your work really gets at.
Totally. And I think, I mean, it's always, I felt that in the human, I mean, art, human, and art history, there are always artists in love with nature. I think it's so inspiring, it's infinite inspiration, a living intelligence. I mean, when Monet inspired from the water lilies, I'm pretty confident that he has exactly in the same flow of state looking at the beautiful nature. So I don't feel I'm so different. In a neural network trained by custom, I mean, all the flowers in the world now, they're inside that. And has remembering every single pigment of any color we ever discovered. It's, it's just the same mindset, just different time and resources, I guess, of like technology.
You've used this phrase "ethically collected data" or "ethical data" a few times. What does that act, what's the difference between ethical and unethical data?
So I think the majority of our artist friends and creative friends have this very significant tone when it comes to knowing that what is inside this pigment, what is in this like brush. I totally agree with their responses. For me also, for 10 years, we are grateful, we create our own models, our own data. It's a privilege to be here. But I felt that what happens from scratch in the model that's just, but just nature. And this was always a question because some artist friends felt uncomfortable to use someone else's creativity, someone else's, I guess, techniques or styles and aesthetics, which completely respect. But I felt that I would love to start with nature as a base. I hope that nobody says that this tree is mine or this flower is mine. But that, that is like this, if nature is the fundamental layer of reality for that model, and that can be trained by the by the creator's expectation model. Perhaps we have a new technique, a new style, a new approach to the, on the, uh, creator's own language and vocabulary. For example, we take the larger model and train it. Our 10 years of artworks now have its own distinct style that I know exactly where it comes from. So I think we are trying to solve this pretty much a solid problem by showing how it may work. And so far, it's working.
I would love to bring up one of your artworks and for you to kind of walk us through the creative process of it. Uh, I think we have one of them, which is Qualia.
Yes.
Is this it?
Yes.
Um, there we go. Uh, so with Qualia, what, what does the end result look like and how did you get there? Were you like sketching things, or do you immediately start programming, or are you in an Excel spreadsheet coloring cells to like figure out what the data is going to look like? What does it actually look like?
So, so Qualia is a wonderful experiment in our studio. We have a robotic experiments going on for now almost nine years. So our first, the same robot we see here, KUKA robot, was used for 3D printing, um, one of our data sculptures. And by the way, we use ocean plastic waste and recycle them and turn them into a data sculptures.
You're always thinking about sustainability. I love it.
It was very like, um, inspiring to use technology that is beyond a chisel or a marble or a concrete. And we felt that this type of technology allows us to to use, um, in a different way. But as I mentioned, I, I can't draw properly. And it's this urge to like, you know, find that way. But on the other hand, for Data Land, as mentioned, we have a very unique, uh, information will be shared very soon. On the other hand, as mentioned, brain signals, we have been working with, um, and biosensing, we have been working. It was the moment that perhaps these millions of information with a, which human cannot perceive, but still a chance to give it a chance for being painted was the was the reason behind that. So it's not about like replacing a painter, replacing the paint, the act of painting, but in fact, enhancing the creativity by machine intelligence. I know exactly where my limit is. I would never remember four million data points to be able to turn into this beautiful like forms. But I felt that perhaps there's a world where the where the human, um, I guess, um, practice of physicality and I guess cognitive skills limits, but where that that unlocks any world that I see it, machine human collaboration, 50% machine, 50% human.
Do you immediately see the art in a piece of data, or does it take a little while for you to tease out something? Do you look at your tax returns and be like, this could hang on a wall?
I mean, maybe the blockchain ones, that's sometimes it's more easy to compute. Um, the, the thing that I felt sometimes, I mean, the data is again, some people see as like, a very boring numbers, right? I see a truly a form of memory. And I see that that memory can take any shape, any form, any color. And to do that is a lot of experiments. So like, we have a rigorous like research as a team, look at the data, where it comes from, what it says, the time domain, inside the context and discourse of it. And then also, there's a lot of like, I mean, majority of our works is using fluid dynamics. I'm in love with nature, as I always say, the water, uh, in Istanbul, my hometown, there's Bosphorus forest that connects, um, literally the west and the east. And that water to me, a connected tissue for humanity, or a feeling of digital and physical. I feel like these are always first starts with the, the very intentional, very personal, very emotional context. And then the scientific context comes, which I think art happens exactly in that, uh, place. But always use technology tools and recent algorithms. And with AI right now, you can imagine, I mean, the speed of, um, things we could do is way different than two years ago.
You mentioned memory again. And I think you've referred to data and what AI can do with it as kind of a collective memory. So that's like the memory of all of us and all of humanity, right?
Yes.
What does, what does it mean when we have a collective memory, or when it comes to the fore in one of your artworks?
I think collective memory is like, if you look at our work for 10 years, the pattern is, you will see that we work with nature, space, urban culture, time domain, or scientific discoveries that has a powerful impact for humanity. I felt that these are one of the most wonderful memories of our life. But I want to be also sure that this is a incredible opportunity for humanity to say something more than what we said before. For example, when I say collective memory, I feel that it's a path to find our collective dreams in a world that we have separations, wars, and problems. Can we find the positive? And can we find our common language, the language of humanity? I guess that is connects all the beautiful things we as humans, as humanity, we do and we want to do. Um, so there's that always this positive impact in my mind that when I think about collective memories, it's a lead to collective dreams, which eventually leads to collective consciousness, right? Um, very fundamental, I guess, uh, understanding of life. So that's, I think, coming from there. Like, um, you create, you create your own AI models. You're training, you're training your own AI models. But are you using AI tools like all of us are using? Are you chatting to Claude or ChatGPT about what it thinks art should be and what it wants to create?
Absolutely. I mean, we, and all our teams are extremely native in AI and in every single, like perspectives. Because first of all, we're a small team, like only 20 people in Los Angeles, but we feel like sometimes 200 people because we don't have any more, I feel like a limitation of information and knowledge and knowledge when experience still big question marks. But I think the speed of accessing, um, technological challenges and reaching a level of, I guess, solutions, uh, very different than, again, a couple of years ago. So we are AI natives, I will say. And then we love to work with neural networks, deconstruct them. By the way, this also very exciting. So people are thinking like, where is art happening with AI, right? So we artists don't like a perfect working systems, by the way. And the AI systems are so good, try to be so perfect. But at the meantime, art happens in glitch, error, imperfections, and and where things are not okay or right.
Real, real collisions between things.
Yeah. So we love to like, you know, take these models and break them in a way that in a fun way, and and reconstruct them. And I think that is really what the AI art is happening. And both understanding data, neural networks, and their limitations and capacities, and then find that the unique world or let them have conversations and like lost their pets and so forth. So there's so much fun there.
Do you think AI can inherently be creative, or that's purely a human skill?
My hope from my heart, we are humans, and we are the creatives. I hope we will never lose our compass. I always see AI not as a replacement, as a just a great friend, as a chance to help us. And and I hope this doesn't change. Because I believe creativity should be in the hands of humans. We all, and I think we should ethically be careful, uh, how we navigate that, I guess, water. Um, and and I hope that we all can remain creative as we wish for.
You mentioned breaking things and like the wonderfulness that happens when things go wrong. Uh, and you've also talked about something called productive transgressions, which is when you use technology for things that wasn't meant to. Do you have a good example of that?
I think I can count many rejections. Uh, I can count many things that didn't like, click well for the art world. So, when I think for many pioneers, I'm pretty confident it's the same thing. When we start to see beyond what is possible of any field, I feel like there's this beautiful walls to break, new mountains to climb, and new places to discover. As a child, I always felt that inspiration would love to discover new world, love to find something new, and ask my family and friends, I found something new, like, you want to check this out? That feeling never goes away, I think. And that feeling always hit the same walls that are, this is not art, you can't use data, you can't use computers. I remember very clearly the first critics, why are you using computer to make art? Like, is it, I mean, like, and there was like, always that challenges came from. But the more those challenges are hits the right walls, I guess, the more the pioneering that field happens. Um, when we work with the first neuroscientific data, I remember, oh, you can't use human brain data, it cannot be art. But then one month later, we work with a beautiful desk of five children's, all their brain data healed from Lausanne Hospital. We made an artwork called Sense of Healing, and auction for €1.7 million euro to fundraise for UNICEF.
That's amazing. That's incredible.
That is like where that no, you cannot do that turns into a value for humanity, can be also part of art and design and culture. So we, as a studio, love to be in the places where there's a fear or concern or hysteria, instead of just talking, doing it, experimenting with it, hands-on, and then have an opinion. Because I don't believe that technologies are just, is just talk about it without using, experimenting.
You showed me one of the data clusters that's powering Data Land. There's like 150 GPUs or something. Uh, it's like huge scale. And when you walk into this environment that's so rich and visual and it's pulsing with life, it's a huge experience that I imagine must take a lot of people to bring it together. Are you still coding on a Commodore 64 to make it happen, or or what does the team look like to bring this to life?
So, first of all, I mean, deeply grateful for a great team. Um, small team, yes, but a wonderful team. And again, we never built any physical space before in our lives. We just learn by doing, by experimenting with our partners who teach us how to build a space, how to engineer a space. And then I think trust and courage is very important. Because these are like, um, I guess for some people, dark waters that, or a new, a new, a new water to discover how deep it is, how dangerous it is, what happens if you will, like that type of feeling is when we build an institution from scratch. But the AI really help us so much in this practice. We learn about some, uh, from the permits in the city, uh, to like, you know, engineering a very complex network systems, from training an AI model in the cloud and inferencing in real time when the museum is alive. We had, does we have many, many challenges that solved by the team. Um, we have a remarkable computation that is needed for a living museum concept, which is again, never done before. So this is like the challenges, right? You just can't Google it because it just doesn't exist. Like, you know, you ask AI and, yeah, you just come up with like things, but it really doesn't fit in the reality of life, right? Just like, you know, hallucinations. So that was a really beautiful challenge to like, navigate unknown part of when the digital and physical connects, I guess.
Are you starting to see AI change the shape of your team? Like, who you need on it? The different skills that you need? Is it a different mix now?
I think the team is really, I mean, again, 20 is a number. I feel like I'm in a class I'm teaching last 10 years, literally my class is 20 people. I have this honest connection and everyday connection. There's just something honest about that small but mighty connection. Um, but yes, everyone felt much more connected. So we, we had days that we were limited by resources and knowledge. And because we are not a company, as an art studio, it stays to be so really small intentionally. Um, but AI, I, I think help us so much. Um, so we are, of course, have an amazing summer internship programs where every summer, uh, wonderful brilliant minds joining us and experimenting. So like robotics to neuroscience, um, to biochem, I mean, we have a lot of fun in the studio that keeps growing a very minimal but ready for AI revolution all the time.
Where do you see the next five or 10 years heading, particularly in the world of arts? Like, do you think AI technology is going to bleed beyond the work of someone like yourself? Is it going to affect all artists? Is it going to affect what creativity means and what we as society value in the creative arts?
I think clearly the future I can see now much clearer is human-machine collaboration. I think this is the way to, for me at least personally, understand our compass that allows us to understand how the system, the software, the hardware, the education, and anything and everything really is transforming. I always asked this, like, if AI means anything and everything, it has to be for anyone and everyone. And if we balance this with ethically and sustainably, I see a beautiful, uh, potential for all of us that can, you know, just, um, drive new worlds. And and I also felt that when, um, machine intelligence becomes powerful for solving problems such as disease and other issues, there will be, I think, a different world waiting us. But on the other hand, for creativity, I hope that we all have this powerful thinking brush that allows us to, um, I guess, imagine anything and everything that we are trying to solve. On the other hand, for the art world, I see that for Data Land perspective, because we would love to, um, become as an institution, as a studio, be present and navigate this five years, not only just creating art, but also talking about it, um, educating about it. I mean, again, as a teacher, I love to share so much that there is so much to learn beyond just beautiful videos online. There is still a beautiful world being physically in the same room at the same time, explore the mission intelligence and creativity. So I think next five years for me, both as a teacher and a founder of Data Land and our studio, um, be sure that we are absolutely on a positive compass, uh, to understand this new thing for humanity.
Well, that is great to hear from an expert on AI. Um, there's a segment that we love to do on the Prompted podcast, which we've never done with an artist before, so I'm fascinated to hear your answers. And that is to hear about your all-star creative team.
Oh.
So, with your all-star creative team, you get to choose four people who can be dead, alive, they might not have been born yet, they can be 500 years from the future. It could be Leonardo da Vinci from 500 years in the past. I hope you, I didn't steal one of your choices, but like, who would be the four people that you would have on your all-star creative team?
So, I think would love to bring Da Vinci, lots of love and respect. I would also will be honored to have Rumi.
Who's that?
Rumi is a Persian poet that transformed philosophically, Messi. His 19 language and incredible teaching and learning of philosophically from spirituality, like to many perspectives that I think Geralyn Rumi to be much, much full name, and Rumi to me was like one of those spiritually grounding humanities beliefs and values. And I think Denis Habis, which I have a huge respect to his work, who got the Nobel Prize for solving protein folding. And then I think I will be honored to have Johnny Ive, to like, you know, okay, a designer, a philosopher. Let's go like some an amazing, I guess, uh, room of unique thinking.
I, I don't know about, I don't know what Rumi looked like, but Leonardo, Johnny, Denis Habis, not a lot of hair on that team.
And I hope you've also got a good translator, cuz like, Leonardo will be in Italian, Rumi was probably in Arabic. Yeah.
Johnny Ive has, yeah. Denis, you can, you can have a good chat too. Uh, maybe AI can help you translate between all of them.
Never getting to. And is that you as creative director of all of those folks?
I will be honored. We'll be honored to to be in a room like that and bringing coffee and like, what are we doing?
All right. Well, the very last segment we have on the podcast is always some rapid fire questions. Uh, and I think we actually got AI to help out on some of these questions. Do a bit of research on Rafi and figure out what would be great questions to ask you. Are you ready for some rapid fire?
Yes.
One word is perfectly fine. In fact, one word can often be the best answer, but feel free to expand. Very first question, what is the most beautiful piece of data you've ever seen?
It was a little bit long answer, but it was a beautiful painting series from the Yawanawá family from Amazonia, Brazil.
People. They were called Kunis. This is a very beautiful painting technique that belongs to them. And they were able to, we collaborate with Essun, my partner, and I. And it was the most beautiful data ever with ethically, we use to train an AI model to make a beautiful fundraising to make the first Amazonian museum and university in the heart of Amazonia. That data, that only 12 paintings, maybe one of the smallest data we ever work, but the most meaningful and purposeful and most emotional data we ever work.
Wow. I'm going to have to break rapid fire here because I love it. Um, did those people get to see the final AI artwork that you produced?
Yes. Amazing.
Deeply grateful for that data set that are so rare but are so meaningful.
Okay, back into rapid fire. Um, what does a machine dream about when no one's watching?
I think hard one.
If it's too tough, you can just pass.
Daydreaming. I think it's still daydreaming in a flow state of its own latent space.
Okay. A collaboration with one artist living or dead. Who would it be?
Actually, um, can I say Rumi?
Go for it.
Because Rumi, I think I would like to come back. If I can find, I was just want to say one of the reason is long answer, but he has this amazing seven advices.
Okay.
For generosity, be like the river. For compassion, be like the sun. Concealing faults, be like the night. For anger, be like the dead. For modesty and humility, be like the soil. For tolerance, be like the ocean. For authenticity, either exist as you are or be as who you are. So, he was a powerful person that I think can enhance.
That is beautiful and deeply connected to nature. Again, uh, what is a piece of data that changed how you understand humanity?
I will still go back to nature. It was so profoundly powerful to think how incredible nature is, a form of living intelligence. I think nature is a form of AI. We just don't know yet.
If all your tools disappeared tomorrow, if we smashed your Commodore 64, uh, what would you do?
I will ask my partner first. I would love to go back to the most deepest, honest, clear nature world to understand more nature.
What's your favorite underrated AI tool?
I think I am still going back to the GAN algorithms. They are called Generative Adversarial Networks. Um, very early generative AI models, pre-diffusion models. Yeah.
They are incredible. They are unsupervised and they allow you to break things much quicker.
They produce those trippy Google visuals, right?
Beautiful world.
Sum up AI in one word.
A mirror for humanity.
All right.
A mirror.
And very last quick question, finish this sentence. A surprising thing AI taught me about myself is...
Human-machine collaboration.
All right. Well, thank you, Rafi. I think we've covered so much amazing stuff here.
So much. Thank you so much. And I hope to see you at the Land, hopefully. Hope to see you. And thank the audience for being here for a live recording of Prompted, which is a very rare.