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Harvard Data Science Review Podcast
Artificial Intelligence or Artificial Creativity: Which Strikes the Right Chord?
00:39:45
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- [00:03]
Liberty Vitter
Hello and welcome to the Harvard Data Science Review podcast. I'm Liberty Vitter, the future editor of the Harvard Data Science Review. Creativity is often believed to be a uniquely human trait. But what happens when artificial intelligence starts to blur the line between human imagination and machine innovation? Joining us today are four extraordinary guests who are shaping the intersection of art, design and technology. Nene Hu is a designer and art Director with over 20 years of experience working with global fashion brands and the founder of and her a company using AI to personalize fashion. PortraitXO, an award winning artist and researcher explores the symbiosis between human and machine creativity through innovative audio and visual projects. Last but certain, certainly not least, CJ and Zach from databots, pioneers in AI driven music creation who are redefining what's possible in the music industry by crafting songs entirely powered by algorithms. Together we'll dive into how AI reshapes creative fields from personalized design to algorithmic music. Can machines truly co create or are they just mirroring us? And what does this mean for the future of artistic expression? Join us as we explore these thought provoking questions on the Harvard Data Science Review podcast. You know, so Nini, you really have brought together this whole group of people and you are the author of AI and Creativity for hdsr. And what was sort of your vision in bringing together all of these artists and what did you sort of hope to have come out of this? You know, what do you see as the future of AI and creativity?
- [01:58]
Nene Hu
So three years ago when I wrote the article, I had the privilege of interviewing Rania and really exploring her creative process and music and art. And it was during that early days that the AI driven art was just beginning to emerge in the public consciousness and then the one name that kept coming up in numerous projects and collaboration with Dadabot. So like I'm excited, super excited about today's opportunity to like reconnect with Raniat and and Daraba to see how they have evolved in their work and what kind of conversation that they've been having and to really reflect on the evolving role of AI in the whole creative process. So we have from the artist perspective, we have from the developer of the tools perspective and then what I can offer is from, you know, as a designer and also the commercial applications from fashion. So that's why I thought it was really great to sort of use this as a timestamp to record the perspective, the artist, the designer, developer and the implication of that in the commerce.
- [03:05]
Liberty Vitter
Amazing. As you all know better than anyone, art comes in many, many Forms. And especially now that we have this sort of entire digital landscape to utilize. Could you each sort of briefly tell us what you do in the artistic space and how this speaks space typically interacts with AI and Portrait? Xo, I'll start with you.
- [03:28]
PortraitXO
So first. Coming from a very musical background, I very quickly became obsessed with the way technology influences the way I write and think and just perceive music making very differently to the way I ever imagined. And that's kind of how I met CJ and Zach as two musicians who are also just equally obsessed with technology in interesting ways. And we collaborated first together in 2019, where I provided a data set of vocals to be trained on their custom sample RNN model. The result of that ended up being a co creative audiovisual album which I toured for several. And then debate around ethics became a lot more critical over recent years. And it's really impossible to nod go into those areas of conversation when we talk about creative AI because copyright is such a huge ordeal, and I don't know if we're ever gonna actually solve this in a global way. It's just so challenging because everyone is addressing all of the nuances very differently. It's been also really amazing to just witness how CJ and Zach have been navigating those conversations as well. Just seeing stable audio come to life and just everything from the legal side to the business and the ethical considerations, all of that became really helpful as well for me to understand, like, how to navigate these difficulties. Because the reality is that artists get so criticized heavily for using AI. That's one thing that I hope that there's like a shift that kind of moves where artists can work with participants and public to further discourse in meaningful ways. Because the opinions about AI has been so highly polarizing. And I think some of it still is, but I think we have a lot more nuanced dialogue now.
- [06:06]
Liberty Vitter
You know, Portrait, you've done such interesting work with CJ and Zach. So I think I'll have to go to CJ and Zack from Databots, because I think the most interesting comment that I saw of you guys is sort of this tagline of eliminating humans from music. Which sounds so to someone, for me who doesn't know a lot about this seems so antithetical to music. But I also will admit that I'm like a top 40 iTunes listener. So maybe you guys could explain to me really what that means and what you all are striving to do.
- [06:37]
CJ
Cj, you want me to take this? Cool. Well, eliminating humans from music is a multifaceted statement, I'd say, but one of the ways we can take it is we are musicians seduced by math. And what I had realized studying composition in my undergrad was that math, whether it is a means to remove some of your personality in a way, like from a romantic composition standpoint, moving to a more modernist composition standpoint, where the process is really visible by everybody, you're creating new structures of music that are not necessarily aligned just with traditions, or you're creating sounds and sound design in a way that you might be controlling with traditional performance means. All of these different approaches became fascinating to me. And when I was studying music technology, I realized there was a constant kind of pulling away from some of the more, let's say, like Beethoven esque approaches to making music that were very much this divine sound is flowing through you, the composer reaching the paper, then reaching a performer who interprets those notes. And I was fascinated with what will come next through either synthesis or totally algorithmic means of making compositions. And could we start thinking about, rather than the notes themselves, the sections of composition? Could our palette of composition be something broader, like genre? Could we compose genres as our new material? Could we pinpoint artists that never were and create some retro future version of some idea from the past that we take further? And that was one of the things that made me realize, okay, machine learning will be applied to music technology in a way that I really want to be part of in the future. So it really all came from. I was originally in a bunch of punk bands playing music very traditionally. And then I got interested in electronic music. And then I met CJ at Berkeley College when we were interns and started to learn more and more about computer science and figured out how we could blend these ideas of almost designing a genre, designing an artist. And so that's one of the ways that I think the tagline came to be. Cj, do you have any other thoughts on that?
- [09:15]
Zach
Right, yeah. And aesthetically, you know, we're metalheads. We're coming from the world of metal. And is there anything more metal than eliminating humans from music? For example, like Death Clock, the cartoon death metal band, like, frequently they might release an album, say, like, not for human consumption, like for fish only is of course, completely tongue in cheek. And I think, like Zach and I, we have a crazy sense of humors. And whenever we come up with an idea and it makes us laugh, we just go, go and do it. That's kind of our, Our North Star. And of course, on the other hand, this, like leaning into the, the fears that people have that AI will replace them, which a hundred years ago people were also having this fear during the invention of recorded music, when orchestras who were playing four silent films are afraid of being replaced. And this kind of fear is just a limited window in history. Even now, as people are getting used to this new technology, eventually it'll be very normal, very just a part of everyone's lives.
- [10:17]
Liberty Vitter
So I just have to follow up on two things. Zach. It was such a. I don't really know what other word to use. It's almost like an ethereal way of talking about it, of the artist creating the artist that never was. Can I just want to make sure I understand that. So forgive me if this sounds really dumb, but it sounded so beautiful to think about. Is that like saying that AI could create a Beethoven that never was? You know, we could have someone called Beethoven 2 and it can create an entire new volumes of sounds and music that would have been classical music if there had been somebody there to create it. Is that what you mean by that?
- [10:53]
CJ
I think even more than imitation, what we're really fascinated by is what would Beethoven do today? What would Beethoven do after listening to Public Enemy? What would be the type of output Beethoven could do with the modern day tools we all have and all of the cultural implications of what those different genres had meant. And I do think genre is actually a really amazing thing to work in because it's sort of a cultural understanding we all have where there are some unspoken set of rules, whether it's cultural or music theory based rules. And it's just lovely to figure out how to create a hybrid of genres that maybe takes the really important elements and creates a synergy that is complementary to all. And it's turning out from my exploration of large models that have heard lots of music, that finding cross cultural connections through large AI models, it's very effective. And there might be things in common between different groups of people who have never actually thought to blend their music. And just through the statistics in common with them, this fusion could naturally come out.
- [12:13]
Liberty Vitter
You know, everyone's so afraid of AI and that it's going to replace jobs and that no one's going to have work anymore. And it's really interesting, interesting that you talked about like, you know, silent films to then recorded music and how everyone was so afraid. It all works out in the end and there's new jobs created and people adapt and you have these sort of incredible movements forward. So is that how you guys sort of see it is like this is like the one of Many scary things that have happened over the hundreds of years and thousands of years that society has moved on. And people are just afraid because they don't know. But it's all going to work out.
- [12:46]
Zach
Yeah, sure. And actually, Zach and I were invited to the UN earlier this year. The event AI for good. And we met people working in AI in all kinds of fields, and they weren't sure about AI music and we weren't sure about them. But again and again, like, for example, we met this group who was trying to, you know, regulate the international use of drones and autonomous weapons. And their biggest concern was, you know, massive death. And we were telling them about, like, okay, what, what's the biggest problems in AI music? And I'm like, well, some musicians aren't gonna get paid and we like, there's gonna be a lot of job loss and we need to figure out the system. And they literally laughed in our face. They're like, that's it. Like, like we're worried about, like, the major powers of the world, like, accumulating autonomous weapons to fight each other.
- [13:36]
Liberty Vitter
You're just worried about destruction of civilization.
- [13:38]
Zach
Yeah, right. And of course, on the flip side, which we've seen from the start, is that, like, here's opportunity for new value creation, new jobs. At Stable Audio, we were able to create the first example of a foundational model where the royalties from the subscriptions go back to pay the contributors of that training data. And also with our other company, Datamined Audio, we. We have music producers who train their own models and they go into the plugin and there's like a 50, 50 split there and there's this whole. Yeah, whole new kinds of revenue streams and value creation for artists thinking about generative music. So, yeah, the future seems right from our point of view.
- [14:24]
Liberty Vitter
You know, I can't help but wonder. And cj, you kind of alluded to this. You know, how do you all see audiences or people like me who don't know a lot about music responding? Or by the way, musicians themselves responding to these AI driven creations? You know, whether it's Nene with your fashion or you all with your sort of experimental soundscapes, if that's an okay way to put it. You know, do they care that AI is involved? And do you see it with different people? You know, you see musicians respond one way, the general public respond one way. You know, where do you sort of see that and portrait. I'll start with you, if that's okay.
- [15:01]
PortraitXO
Sure. So I think the audience has been pretty critical just because of the mainstream narrative that AI has fed mass media from like Terminator to the endless science fiction movies that have come out that don't have happy endings. So I think all of that contributed to the general kind of pushback. And so when I speak with traditional musicians, they're very afraid. But this is also not an AI problem. I think that history has shown this as like a very human problem that has shown up in many times over and over. Like when Bob Dylan transitioned from acoustic to electric guitar, there was a huge backlash against his move. And I think that even before AI happened, if you're an artist and you perform on stage with a computer, just even having a laptop makes you be critiqued in a very specific way. Like, oh, this person has a laptop. Like, what are the things that they're hearing are actually like, generated real time by the artist if the artist doesn't have, say, like traditional music, musical instruments on stage with them? So perception and all of that has all. It's been a long topic for especially electronic musicians. I think the bigger focus now is seeing the movements of Hollywood pushing back on having anything AI generated copyrightable because the data itself is unethical. And in the creative world, I hear a lot more of these conversations happening. But in the audience perspective, I would say it's a mixed bag. There are some people who are just really fascinated and they're in awe, especially when I do a performance because there's like a huge amount of data activism. In my more recent work where I sonified the entire UN's 17 sustainable development goals, sonified all this data. And so I have this new audiovisual performance where it's about bringing awareness to all these critical data sets that actually uses some AI and then non AI tools. So I think if we were to continue to use AI as a collaborative sparring partner, where it pushes us and provoking us to go in ways that maybe we normally wouldn't, just simply by witnessing our work speed thrown back in these peculiar ways, I think that is a really creatively inspiring way to work with the tools that we have.
- [18:14]
Liberty Vitter
You know, I see Jay and Zach, I know you guys, you said that you were at the AI for Good conference at the UN and you also had some sort of pushback. Is it similar to portraits or is that sort of how you all see it?
- [18:26]
Zach
Yeah, well, in general, the culture is split on this topic and that is great news for the art form. That means that the art form is alive. The culture has not made up its mind yet. It's riding this critical edge where Butterfly effects can influence the outcome, which is a fun, fun place to be in. And the. Yeah, the kinds of pushback that are existing these days. I think it really started when the mainstream started taking an interest in generative AI. And right now, with the current, like mainstream available music tools that most people are using, like Suno, the criticism that we hear a lot is that it's like regurgitating a pastiche of what currently exists. And this is just a very, very small window in the history of what AI music is. Where it's like, yeah, yep, it can nail it, it can replicate it, it sounds just like regular music. Whereas this phase that came before it was like, it couldn't do that. And so you had this experimental weirdness that came out of that vintage AI. And then after this, you have the ability to explore the power set of combinations of things. Like, for example, what if you could fuse every genre with every other genre and listen to that. You would find genre fusions that hadn't existed before that are doing something new. This kind of tool isn't yet available to the masses. So I think like, once we make those kinds of things more available to the masses where they can tinker with it, where it feels like an instrument and it's like readily going into these places in the space of possible music that have, like, have never existed before, we'll have a turn of opinion for sure.
- [20:11]
Liberty Vitter
So I can't help but wonder, you know, you have the naysayers or non believers in this using AI and music and that AI is ruining music, what's your argument against the concept that this ruins progress? You know, one of the biggest arguments is that models, you know, are only as good as the data and the people that are used to train them. So if there's no new creative made by people, because these models are just basing new songs off of the ones we already have, even if that means combining two genres. How do we ever get new music or something different beyond combining genres? Or where does that new creative come from if no one's programmed it in the first place?
- [20:55]
CJ
That's a great question. And it actually is my focus with research right now, which is controllability. Right now we've seen a very primitive, naive approach to making music, which is I will type a sentence or prompt and I get a finished piece of music. And that type of distribution ready push button art is very different than how musicians have worked traditionally. It might be that they've used technology to synthesize some drums and then they'll play guitar and Sing over that. Or it's an element in their production, such as auto tune or something like that, that an algorithm might serve. And what really could change the story for very serious musicians would be an ability for AI to listen to you, and not just listen to a recording you've had, but moving to a live setting, be able to listen to the input and keep up with either a call and response or an improvisation the way a normal musician would. So when we say AI, it is a very big umbrella term and sometimes we just mean we have a finished piece of art that's push button and that's of interest to people who maybe need background music for their videos or some free stock music or advertisement music. But how does it really hit the level that a musician who has gone to a conservatory and studied playing with people in a way that is responsive and reactive, how can we get towards that? And we're just at the very, very beginning of seeing any types of functionality like that. So I think there is still a long way to come. So I would hope that people can rejudge these things as they develop in the future, because new things that will create more expressivity and new inputs will be more abundant. And in the end, what really is going to drive any artist is that you have an aesthetic that people come to you for. And whether you use AI tools or not, that aesthetic will be your own as the creator, as the artist. And I think that has been the past and that will be the future with these tools too.
- [23:22]
Liberty Vitter
Super interesting, you know, portrait. When you said this whole idea that if someone has a computer, it like, it's like, well, is that real music or not? And I can't help but think like whenever I see DJs, you know, up in front of big crowds and they're turning the dials, I sort of think like, well, did they just record that, you know, beforehand? And now they're sort of fake turning the dials. So where, where does the human come into this decision? Like, you've all, you know, sort of delved into sounds and visuals and performance. You know, how do you decide what part, part of the creative process should be left to AI? And what still includes human decision making? What still includes the concept of I'm going to try to put classical genre and rock genre together and see what happens. Like, where's the human element and where's the AI?
- [24:07]
Zach
Like Zach said, AI is a huge umbrella term. But specifically when we're looking at models that just spit out full 3, 4 minute tracks, DJing is like such A great place for this one because Normally when you're DJing, you're playing tracks that already exist, but what if the tracks didn't exist yet? And this adds like a whole other complication and sort of ceiling of virtuosity for what DJing can become. And it opens up more audience interaction. So one thing that we've been experimenting for the past year, we've been calling prompt jockeying. What we will do is it will like put our phone numbers up on the screen and people in the audience would text in prompt requests, mixtures of genres or artists or sounds that they wanted to party to. And like on the stage right then and there, Zach and I would try to fulfill some of those requests for the people. And what we found is that a lot of people that were in the audience who were originally sort of AI naysayers like thinking that, oh, this removes the humanity. They're actually surprised how it introduced more humanity to it because it brought more of that communalness together as a result.
- [25:26]
Liberty Vitter
Nini, you know, you brought everybody together. You've, I'm sure, seen the same, you know, you've seen the pushback or the push and pull between all this. You know, where do you sort of see the future of AI and creativity going?
- [25:39]
Nene Hu
I mean, so for us, it's really more about the change in workflow. You know, before, when you start with a collection, a fashion collection, you start with tears, you start with images, you start with fabric, you start with color, you start with proportion. And that's not going away because majority of it is still very tactile. Your end product is the actual piece of clothing that people are going to put it on, whether it's a jacket with a T shirt, a sweater or a pair of jeans. And it's. You're still bringing that hard product to the customers. Would they care in AI design, all that? Probably not, I'm not sure. You know, would you mind if, like this T shirt, this logo is designed by AI generated or a human who's hand painting it, or somebody putting in a prompt and say, I want this logo in the style of a hand painted, you know, for us, you know, when I'm directing a photo shoot before, it's again, this starts with imageries, models, clothing, outfits. And now I toggle between, you know, different AI tools to create an imagery that I can say, I want the lighting to come from here, I want the lens to look like this and I want the set design to have this kind of plan just as a starting point, as a communication tools to the photographer, to the set designer, to the assistants who are going to be prepping the space. And then magical happened on set. But that was a different starting point. And instead of me spending hours trying to pull the right imageries together, I'm creating that from the very beginning. To say, this is kind of what I want. Not exactly, but I'm just using as.
- [27:23]
Liberty Vitter
A tool, I think probably people's knowledge of whether something is AI created just with what people think, think right now must have such a huge effect on their feeling. Because, you know, if I was going to try on a dress, I wouldn't care whether it was AI or a fashion designer. I want what looks best, right? Whichever one's best. And I think I feel the same way about music, but I don't think I'd know, you know, if I was listening to music. I don't think I'd know whether it was AI generated or person generated. In the end, you should probably just want what. What's the best or what's the most interesting or what makes you feel the best. I know I cook. I'm a chef, and I made a cake for my brother, and he's this huge believer in all ingredients have to be, like, perfectly fresh and the most special and flown in from God knows where. And did you get that flower from France or from, you know, like, he's like, very much like this. And I took the Duncan Hines yellow cake mix and I souped it up a little bit, like, put some interesting things. And he goes, this is the best cake I've ever had. And then as soon as I told him it was Duncan Hines cake mix, he started to find things that were wrong with it. And it's not to put AI with Duncan Hines, but it's that same concept that prior knowledge bias on part of the audience or the listener can maybe actually stop them from really appreciating what is the best or what is the, you know, the most inspiring or what could be the most interesting for them to hear something they've never heard, tasted, or worn before.
- [28:45]
Nene Hu
But I also want to highlight the joy of creating something, you know, like savor a chef. You know, yes to the end product is important, but going to the market to pick out the fresh ingredients, the temperature play of, you know, different techniques they're using, different plating. All that steps are creating. And maybe you use AI to generate a new combination of taste, but that actually help you to complete what you really want, what your intention was from the very beginning, and then give maybe something new to the audience at as an end product, and that benefits everybody. I'm just really a big believer that having that tool is going to augment our creativity.
- [29:31]
Liberty Vitter
Yeah. And the challenge of it, of using something new, I mean, I would imagine that that's part of what you all run into as sort of the naysayers and the non believers, is they just. I mean, it's scary. They don't know how to use it. I mean, it's something you have to learn. It's a new skill that you all have to learn that a lot of people have to learn. But I think sort of looking ahead beyond what capabilities already exist when it comes to AI and these creative arts, what sort of emerging technologies or ones that haven't been created yet are you sort of most excited about? How do you see the future? Really pushing the boundaries of creativity and portrait? I'll start with you.
- [30:13]
PortraitXO
So I'm gonna say something really boring because I do feel like there's a really huge hurdle that really needs to be figured out. Kind of like not so nice aspects of what has been happening that does need to be addressed is like. So I'll just mention some information that I found out in October where I was at this event called ade, which is a very large music conference festival called Amsterdam Dance Event. And I met a man who runs a company in the US that detects fraudulent activity on Spotify and then demonetizes it. And so he mentioned that it's 80% of Spotify revenue that is fraudulent activities, and that number has exponentially increased because of AI generative music. And so there are these kind of, like, not so nice and ethical things that are happening. And, you know, once we can figure out, like, fair ways. And I think, like, remuneration is really important if somehow, like, everyone can somehow be incentivized or these companies can be socially held accountable in a way where they give back to society somehow, perhaps. I think these are things where it makes people feel really uncomfortable, you know, because when we talk about copyright, it's not just about authorship over creativity, but it's actually about human rights. It's our data, it's our identity across everything. Like our information to image, audio, video. It touches everything. So there are these huge, daunting challenges that we need to figure out. And I do feel like once we get a handle in fair ways to move forward with all of this, that would ease everyone who's been afraid of it. And. And because I understand their fears as well. And I think that, you know, like, people suing open AI and finding text information in there that they know has been derived of, you know, all of our works collapse combined as an entire humanity and the whole history of the Internet. Like these are very important issues that, that we do need to figure out.
- [32:35]
Liberty Vitter
C.J. and Zach, what about you guys?
- [32:37]
Zach
I think for emerging technologies, four things on the near future that excite me. One, like Zach was saying, like live auto accompaniment. Like if I can play guitar live and have the entire other band improvised with AI immediately, like immediately there. I'm also a beatboxer. I would love to do a beatbox performance where I'm just improvising with my voice and like a full production, EDM production can accompany that. I think it's one, two, a video creation I want to hear. I can't wait to see like bedroom Hollywood film producers, we like bedroom music producers has already become a thing. We've had like Billie Eilish just you know, top the charts producing everything with her brother in their bedroom. Eventually we're going to have hot like Hollywood level films done this way very cheaply and that, that, that excites me. Three, hearing music come out of quantum computing is going to be very interesting as a way, as a window into helping the mainstream understand the behaviors of, of quantum computing. And four is this, this moment when everyone like, like having their own furby can have a, their own personal AI music generator that runs on their laptop locally and then they're just FE and music and it is producing a radio stream and we can all like tune into each other's radio streams.
- [34:05]
Liberty Vitter
Awesome.
- [34:06]
CJ
So many awesome ideas have been covered. I'm so super interested in everything both Portrait and CJ said and to throw one very, very science fictiony thing out there. I'm interested also in when machines start listening and collecting and consuming music to the point that machines become influencers and what if they go so far away from human creation that it's totally diverged from what any journalist in the music space would have traditionally written about. That starts to sound very alien. But then at some point we realize there's something of value that humans are interested in again. So that's my very far off sci fi concept that maybe will happen or maybe won't.
- [34:59]
Liberty Vitter
Awesome Nini.
- [35:00]
Nene Hu
I think it's education. A lot of people don't know what they can have access to free and that can, you know, just by knowing the tools and they can experiment and that can spark creativity and then also give feedback and then people can build better products, more controllabilities and to help us Continue to evolve and have more, you know, to try. Continue to argument.
- [35:25]
PortraitXO
Oh my God. Sorry. I just wanted to nod about the democratization of education. And just as Nini, you were saying that I was also thinking about democratizing mental health. Like, I've used ChatGPT as a therapist, having a real like audio. Audio to audio conversation. And it was pretty good. It was actually really, really good. It helped me work through some like, inner thoughts or question.
- [35:51]
Liberty Vitter
Yeah, I love that idea. I. I think that's such a cool way to think about it and how what the best way is to educate young people and sort of get them engaged. I know. I remember I told my class that they were allowed to use ChatGPT to do their homework and it was like, oh my God, they all got so good at chat GBT so fast. And like that was the best education tool to teach them. Existed.
- [36:14]
Nene Hu
But.
- [36:15]
Liberty Vitter
Okay, I could. I have like 8, 000 more questions for you guys. But I. I will finish with our final one. We always do a magic wand question. So I'm going to ask all four of you, if you could wave your magic wand and work with any one artist, living or dead, who would it be? Who would like to go first?
- [36:37]
CJ
Jimi Hendrix.
- [36:38]
Liberty Vitter
Okay, Zach's got Jimi Hendrix.
- [36:41]
CJ
He pushed the limits of what a guitar amp could do and for his own expression and that connected to it, an audience. So it's. It's quite synonymous with pusheen technology.
- [36:52]
Zach
Yeah, mine too.
- [36:53]
PortraitXO
Oh, both you guys are.
- [36:54]
Zach
Both.
- [36:54]
Liberty Vitter
You copy each other. You got to come up with somebody else.
- [36:57]
Zach
Okay. No. Mike Patton.
- [37:00]
PortraitXO
Oh, my God.
- [37:01]
Liberty Vitter
I don't know who that is.
- [37:03]
Zach
Yeah, like Mr. Bungle, Tomahawk. Just the kind of insane, multi genre, fusion, smashing kind of music that is inspiring us to do the same thing with AI right now.
- [37:18]
Liberty Vitter
Awesome.
- [37:18]
Nene Hu
Nini, Mr. Dior. But this is something separate. So I don't know if everybody had time. So Rick Rubin, who's a really big famous producer, so he has this podcast and he started doing these little series called Unexpected Conversations. So he had conversation with Jim Morrison, Alfred Hitchcock. So effort. Some people thought it was AI But I think what happened was he found a really old recording and he just sort of replaced the reviewer with his voice. But when it was the idea of AI like you can crunch somebody's data and actually really conduct an interview with a dead person. And that is something that can never be done before. And it could be really interesting portrait.
- [38:05]
Liberty Vitter
What do you think?
- [38:07]
PortraitXO
It's a really, really hard question. I'm gonna say Leonardo DaVinci. Why it's just so fascinating because he was, he was a polymath and he was interested in science and engineering. And I feel like I could, I would just love to have many, many dinner conversations with him. And I feel like he would be a perfect human from the past who would use AI in really fascinating ways. And I'd be curious, like, how would he maybe challenge some of his scientific ways of thinking with the integration of AI into his practice as like a traditional painter as well.
- [38:56]
Liberty Vitter
Well, I can't thank the four of you enough for joining us today. Thank you you so much. It was so appreciated and I cannot wait to go listen to all of this music tonight. Thank you for listening to this week's episode of the Harvard Data Science Review podcast. To stay updated with all things HDSR, you can visit our website at HDSR, mitpress, mit.edu, or follow us on X and Instagram @the HDSR. A special thanks to our executive producer, Rebecca McLeod, producers Tina, Toby Mack, Aryan and Frank Gavin Yang and Belle Reilly. If you liked this episode, please leave us a review on Spotify, Apple or wherever you get your podcasts. This has been the Harvard Data Science Review. Everything Data Science and Data Science for everyone.