Subscribe
Share
Share
Embed
Minding Machines is a podcast dedicated to fostering thoughtful, open dialogue about artificial intelligence. The show brings together educators, students, and practitioners to explore how these tools are changing the way we teach, work, and think. Our conversations focus on practical experiences, emerging questions, and diverse perspectives across disciplines rather than establishing rigid "right or wrong" answers or settling debates about AI.
Minding Machines is an independent podcast produced at Lawrence University, Appleton, Wisconsin. The views expressed are those of the participants and do not represent the university.
Background music - Relaxing Light Background (short version) by AudioCoffee (https://freesound.org/s/725615/)
[00:00:00] (music)
[00:00:02] Abhishek: Hello and welcome to Minding Machines, a podcast dedicated to fostering thoughtful, open dialogue about artificial intelligence. The show brings together educators, students and practitioners to explore how these tools are changing the way we teach, work and think. Our conversations focus on practical experiences, emerging questions, and diverse perspectives across disciplines, rather than establishing rigid right or wrong answers or settling debates about AI. Thank you for listening. I'm your host, Abhishek Chakraborty, and I am an associate professor of statistics at Lawrence University.
[00:00:40] Abhishek: We have with us today as our guest, Abir Sud. Welcome, Abir. Abir is our first student guest on this podcast, so I'm very excited to be chatting with you and thank you so much for taking the time, amidst this is the sixth week at Lawrence, amidst everything that's going on. Thank you so much for taking the time to be with us. Before we begin, could you please tell us a little bit about yourself?
[00:01:06] Abir: Yeah, of course. Thank you so much for having me. I'm super excited to be here. My name is Abir. I'm a senior here at Lawrence, double majoring in business and entrepreneurship, and music.
[00:01:15] Abir: And over the past several months I've been part of the founding team at a startup called PlaiMusic Inc. where I'm the music domain expert for an AI powered piano learning app we're developing called ZumaPiano. It's an app where you can take an audio of any piano audio you like. It'll take that audio and convert it into sheet music and waterfall notation and from there you can use as a practice tool. And what we're working on right now is an AI coach where it'll help guide your practice sessions. And we want it to be a supplement to traditional music instruction.
[00:01:47] Abhishek: Cool. Abir, we'll definitely be talking about the app and your contributions to it later on in the episode, but I think at this stage you'll have to face our icebreaker question.
[00:01:58] Abir: Alright.
[00:01:58] Abhishek: Are you ready?
[00:01:59] Abir: I'm ready.
[00:02:00] Abhishek: All right. Abir, what's one thing you would happily automate away forever? And one thing that you would never automate, no matter how good technology gets?
[00:02:11] Abir: Yeah, I like this question. One thing I'd happily automate away forever is something that would handle my spam emails, spam texts, spam calls. Something that would hopefully never let them reach me in the first place or unsubscribe me from emails I never wanted. Maybe something that would like handle or organize my communication in general. Maybe organize meetings for me. Something like that.
[00:02:34] Abir: Something I would never want to automate. I think this might be surprising. I don't know how surprising this is based on what the app is, but I would never want to automate me playing the piano. Like I want to always be the one learning and and playing the piano, actually touching the keys. I would never want to automate that. I would happily let technology help me out, but I always want to be the one playing the piano.
[00:03:01] Abhishek: All right, cool. Thanks for sharing. Yes, I do hope that if you ever come across a tool that lets you schedule your meetings, please let me know. And also the spam email stuff. In this era of spam emails and phishing emails and all that stuff, please do let me know.
[00:03:19] Abir: Alright.
[00:03:19] Abhishek: That sounds very important.
[00:03:22] Abhishek: I would begin our conversation by asking you a general question. I mentioned that you are our first student guest on our podcast. I wanted to know your thoughts on AI from the student side of things. And I also wanted to know if you could tell us a little bit about how you've been using AI in your work and besides the app that you talked to us about. Because I'll be asking you about that later. So could you please share with us your thoughts, experiences and perspectives on AI?
[00:04:00] Abir: Yeah, sure. I think I, like many people, whether you're a student or not, I think I have very complicated feelings about AI in general. There are a lot of causes for concern and for excitement I think. I'm concerned about availability of jobs for new grads like I'm going to be, because a lot of the entry level positions I'm going to be applying for, they're either being automated already with AI or they're going to soon be automated. I'm concerned about AI use making us think differently, maybe making us think less, or making us think in more robotic ways, making us think less humanly.
[00:04:38] Abir: I'm concerned about what it means for people in creative fields like myself, like in arts and music, about how people can just use AI to create things like that and replace human creators. I'm concerned about its impact on the environment and how it's affecting underprivileged communities. But at the same time as all of that, I'm also excited about the possibilities that come with rapidly evolving technology, like with AI. I'm excited about how it can make things like developing apps more accessible and easy to accomplish and how in turn that can make other things more accessible, like how we're making music education more accessible. I'm excited about how it could potentially make us focus or allow us to focus on more creative aspects of our work while it takes care of the more tedious, monotonous tasks.
[00:05:28] Abir: And on top of all that. I think I just strongly believe that AI is already a big part of our. Of our. Of our life right now. It's not going away anytime soon. I don't think it's going to go away ever at this point. And so when I got this opportunity to be involved in the startup, I was certainly hesitant about it, especially with it being AI and music. But I do realize that I think being involved with it is going to be important for me and my future. So I stuck with it and I'm glad that I did.
[00:05:58] Abhishek: Okay, cool. Let's talk about the app. Before going into the technical details of the app, I want to know, you touched on it briefly, like, how did you get involved with it? How did you become a founding member? What was the motivation? And you mentioned that you are a business and entrepreneurship major as well. So I think some of our listeners would want to know about your experience and if you have any suggestions for how to get started with a startup, if you could share that.
[00:06:32] Abir: Sure, yeah. So it started because I have a family friend back home who is the co-founder. He has a software background and the other co-founder is someone that he works with regularly in his day job. And that that person is our main AI engineer. And his daughter was the one who inspired the whole idea for the app because she wanted to be able to learn any piano piece she wanted.
[00:07:04] Abir: And they all felt that there wasn't an app out there that already existed that made that so conveniently possible. And so they started working on the app. The two co-founders, they both had that technical background, the software background, and then my family friend, he eventually came to me once they had started working on it because he knew that I had been playing piano for my whole life, basically. And he asked for feedback on the app. And so I was very impressed with what they had at the time, but it certainly wasn't musically accurate or as musically accurate as I wanted it to be.
[00:07:40] Abir: And so that sort of turned into me meeting with them regularly to give feedback on different versions that they have. I eventually became an intern on the team. And then as I started becoming more crucial to the team, as I started representing the team in pitches to various academics, investors, professors, that's when I really started becoming part of the founding team. And I guess in terms of advice, I would say make sure people know what you have going on in your life. Make sure people know people in your life know what you're good at, and you never know when they'll come to you for help and what that could turn into later on.
[00:08:22] Abhishek: All right, cool. And we will be sharing links and of course, with your permission, is the app ready to be shared with listeners?
[00:08:32] Abir: Yeah, there is an app. We have an app out there for iOS and Android. We are certainly, we're in development of it right now in terms of it being like it's, it's more, we have it more advanced than what's out there already, but we do have a version of the app that is out there. We have over 10,000 users with it right now, so. But we're, we're making significant improvements to it and it will look quite different in the near future than what it does right now.
[00:09:02] Abhishek: All right, cool. We would be sharing the link of, of course, with your permission, of the app in our show notes.
[00:09:08] Abir: Sounds good. Yeah,.
[00:09:09] Abhishek: That's great. So could you dive a little bit more into your role as the music domain expert? You already touched on it, but do you have anything else specific to say? I think this would be helpful for our students in the con as well if they are thinking about, you know, doing something similar to what you've done.
[00:09:32] Abir: Yeah, definitely. I never thought that my experience on the con would help me out this way, but it has significantly helped me in the startup experience. My role as music domain expert is pretty complicated. I'd say it involves a lot of different things. Mainly, I'm the person on the team providing all the musical context to my team, making sure that they understand everything from a musical perspective, making sure we're on the same page about what everything should look like in terms of musical accuracy.
[00:10:05] Abir: I'm also making sure the app aligns with various profiles of the users we're targeting, and I'd be happy to expand upon our target audience later, but in general, that's like teachers and students, people just wanting to learn their favorite songs that don't necessarily have time for private lessons, and even advanced students as well. I also review and give feedback on different iterations of our app that our technical team comes to me with. I propose ideas for what our pedagogy could look like and how we could gamify that experience for our users and make that more engaging. Like I said before, I'm involved with pitching the app, making sure that whoever we're pitching to, I'm adapting our pitch to their level of experience in the music and tech world so that I can accurately portray our vision. Right now, I'm currently doing a lot of testing for our app. I'm pretending that I have different levels of experience as a student to see how our AI coach responds and providing feedback and suggestions for how we can improve that coach to our team.
[00:11:11] Abhishek: All right, so could you remind us, like the team right now has you as the music domain expert.
[00:11:18] Abir: Yes.
[00:11:18] Abhishek: Is it just you, you?
[00:11:19] Abir: I am the, yeah.
[00:11:20] Abhishek: And a few software engineers or a couple you already mentioned?
[00:11:24] Abir: Yeah, I'd say one main software engineer, our AI engineer, and then we have the other co-founder. He has a software background, but he's primarily getting us involved in these pitch competitions and getting connections for ourselves and things like that. And then we have someone in marketing as well.
[00:11:41] Abhishek: All right, cool. You mentioned about the audience, so let's talk about it. Who are your target audience? And could you tell us a little bit about how the app, right now, the published version of the app, looks like from the user's side?
[00:12:01] Abir: Sure, yeah. So that question about who our audience is, is something that we've been grappling with from the very beginning. And honestly, we've been changing our answer to that from the very beginning. At the beginning, when I was involved with the app, from my time, I was very much trying to convince our team that we should really only be targeting beginners, people that aren't invested necessarily in private lessons or wanting to go to a university level like I have, because I honestly couldn't see myself using the app at the time as a university student studying music. I also couldn't see a world where teachers would actually be willing to accept this kind of AI app in their classroom.
[00:12:50] Abir: But that was mostly when I was concerned about our ability to accurately transcribe piano audio into sheet music. But then over time, right now, what we have for the app and what we have seen users interacting with is you upload an audio of any piano piece you like, and then it'll take that audio and turn it into waterfall notes. If you don't know what that is, imagine, like, slabs of color falling down onto a keyboard. A lot of people would look up YouTube videos of these to learn music if they can't read music, and so that's what we have.
[00:13:28] Abir: And then we have various practice tools that you can use. You can use the metronome, you can adjust the tempo, things like that. So that's what we have right now. And so that's why I was really thinking that we should really only be targeting beginners because we didn't really have the sheet music capability that we do now. But since then, our AI engineer, he's had multiple breakthroughs as he's worked with various AI agents and as he's been training our AI model.
[00:13:57] Abir: And I'm sure there's been advances in AI since we have started that have surely helped him out as well. And since then, we've also talked with various professors, academics, investors, professional musicians who have been encouraging and impressed with our progress. And now that we're developing this AI coach, we're much more than an app that it's, that is just distinguished from the ability to take any piano song and learn from it.
[00:14:24] Abir: We're also a practice tool where helping people guide their practice sessions, make them feel less isolating, less lonely, and helping you understand what you should practice next while still letting your private teacher, if you would like, have the final say. And so now as I'm testing it, I've actually found myself thinking, wow, I could actually see myself using this or seeing this. I could actually see this be helpful in my own practice to have more structured, focused sessions. And so now we're really targeting students of all levels or even targeting institutions, thinking B2C. Institutions, they might find this helpful in the classroom setting as a way for teachers to see how their students are progressing between lessons, as a way for them to keep their students engaged in the time that they don't see them, and just as a way to even measure retention. So, yeah.
[00:15:22] Abhishek: Yeah. Just to make sure I'm understanding this right, the current version of the app that you guys have published, you said that is more on the beginner friendly side. And in the back end, you guys have been working to develop the app more and more, right?
[00:15:39] Abir: That's exactly right. Yeah.
[00:15:40] Abhishek: And I don't have much experience in music, although, I like listening to music and I try out, try to play instruments here and there. So it seems like the app would be something very helpful for somebody like me.
[00:15:57] Abir: Definitely.
[00:15:58] Abhishek: And your team is working on the back end to of course, improve it and have the app ready for more experienced musicians. Is that?
[00:16:09] Abir: That's right, yeah.
[00:16:12] Abhishek: And I also wanted to make sure that I'm understanding this aspect right. Did you say that currently your app only talks about piano music? And is there any, any other instrument? Pardon my lack of knowledge about music.
[00:16:34] Abir: No, you're great. Yeah, yeah, that's right. We're only with piano right now, and down the line we definitely see ourselves expanding to other instruments, but right now we're really focusing on piano.
[00:16:47] Abhishek: Okay. And I don't know if this is something you can share, but you mentioned about your AI engineer working and experimenting with different AI models and agents. Is there a specific AI tool that your team is using in the sense, like ChatGPT or Gemini or Claude? Or, is there something that you're using, of course, which is more targeted towards music that I'm not necessarily aware of?
[00:17:17] Abir: Yeah, that's interesting. I don't have that full expertise, but I know that a lot of what he's been working with is Claude code. And then the AI model that we're specifically using is actually a life sciences model. It's not geared towards music, but. But we've actually been working with that kind of model to train it and work with music. And that's been working out. Yeah.
[00:17:41] Abhishek: Yeah, that's cool. And as you were talking, I was thinking that music is a very broad field and of course piano music is, you know, is also broad. So how do you make sure, in terms of, in terms of training the AI models, I was thinking how does your team make sure that your training data is representative of the diversity that exists in music in general? But of course, in your case, in terms of piano music.
[00:18:16] Abir: Yeah, that's a very good and important question to ask. For now, we're really trying to make sure that our sheet music is as accurate as possible. We did start with pieces from the Western classical canon, and we really want to make sure we get that right first because there are aspects of that notation that other apps haven't gotten right or that we know is very difficult to get right. So we really want to focus on getting that right first. And then once we get that right, the plan is that as we test our coach, as we're testing it, we're going to be uploading music from various music libraries from around the world, while also seeing what kinds of music our users are uploading to see where we're lacking and where we're strong in.
[00:19:04] Abir: Right now we're confident in our waterfall notation being able to handle any kind of piano music, no matter where it's from or what style it's in. But hopefully in the future, we'll be able to support other styles and notation as well.
[00:19:17] Abhishek: Kind of follow up question. You mentioned about uploading music, and so this is something that is freely available on the internet. Like how are you getting specific permissions if you're getting those in the sense like, or most of the stuff that you're using is just openly available and can be used.
[00:19:40] Abir: So I'd say I don't have the specific expertise to talk about this sort of thing necessarily, but from my understanding, what we're uploading is something that we're not necessarily keeping track of long term. It's just staying within the app. We're not retaining it, we're not retaining all that information. When we're training the data, that's a different story, I guess. But I would defer that to my team to talk about more.
[00:20:14] Abhishek: All right. Yeah, yeah, sure. I want to know. You mentioned of having more than 10,000 users already, that's exciting. I want to know, what feedback have you received? How is your team working on that feedback? Probably that's a more technical question. But I also want to know, on a different side, what pushbacks have you faced? You mentioned having gone to investors and possibly considering reaching out to institutions as well. You are yourself a musician with a lot of experience. I just want to know both sides of that. Like, what feedback have you received and what pushback has your team received?
[00:21:02] Abir: Yeah, I find this really interesting. Every time we talk with someone, it's a different story. Yeah, it's very conflicting because we've had professors of music tell us that there's no app out there that exists like ours and that they could see it being useful. And then we've had other professors or other investors in the music industry tell us that they have already seen things like this or that there very soon will be things that exist like this. We've also had teachers tell us, like teachers of music, private teachers tell us that they could see our app being useful in a classroom setting or that they would be willing to test our product with their students. But then we've had teachers tell us that they want nothing to do with our journey at all. And I'm sure that's because they feel threatened in some way in terms of their job. And I understand that feeling, but that is definitely not what we're doing. We're trying to make it clear that we want to work with a teacher and not replace them. We want to be a supplement to them.
[00:22:02] Abir: So with all that conflicting feedback and pushbacks we've been receiving, our plan is just to continue what we're doing, perfect what we're working on, continue talking to people of interest and getting feedback from them. And then as we continue to update our app, continue getting feedback, we'll continue to find ways that differentiate us and continue to find potential connections that will take us to that next step.
[00:22:26] Abhishek: And it seems like you, your team is using that feedback to develop the app further. Right?
[00:22:33] Abir: Yeah.
[00:22:33] Abhishek: Yeah, that's nice to know. You mentioned a little bit about this. I want to know about the future plans for your team. So where do you see the app a year from now and possibly in the near future?
[00:22:51] Abir: Yeah, I think that's very difficult, because first I don't think any of us can understand where AI is going to be a year from now. I don't think we know where it's going to be a few months from now. And then besides that, we're developing our app every day. We're meeting every week with each other to provide feedback to each other, to continuously get new ideas and update it. But I think I'll give a few like ideas that I have and that our team has talked about for the future.
[00:23:27] Abir: I think I mentioned this a little before. I think we do see our app extending beyond piano to other instruments. We do see that as a very big possibility. Maybe bands and orchestras can use our app as a way for its individual members to learn their individual parts and then for them to come and rehearse together as well. Hopefully, we'll see private teachers implementing our app in some sort of way, encouraging their students to use it as a practice tool.
[00:23:55] Abir: Maybe it's used in classroom settings as well. Maybe we partner with an existing piano company and become integrated into their digital pianos to help with that, to help with their, to help with just general instruction that way. So, yeah, there are several directions we could go in, and we're excited about all the possibilities.
[00:24:14] Abhishek: Yeah, that's great to know. I'm so glad that you're considering looking at the future from now. And that's exciting, of course. Do you have anything else to share about your app? Because I was thinking of going back to our general discussion, but I wanted to give you some time to share anything that I might have missed asking you, or is there anything else beyond what you have already shared?
[00:24:43] Abir: No, I think we're good to go to that general discussion.
[00:24:45] Abhishek: Okay, cool. And to our listeners, as I already mentioned, Abir is our first student guest, so I'm going to kind of put you on the spot here. Can you give us a sense of the AI sentiment at Lawrence right now? What has been your impression about the student sentiment regarding AI?
[00:25:12] Abir: Yeah, I think I'd say AI is a taboo topic at best here at Lawrence. As someone in both the college and the conservatory, I can say that it is much more acceptable to talk about AI in relation to student work, specifically in the college, than the conservatory, specifically in the business classes that I've taken, where professors are much. They talk about AI a lot more, even if it's a little bit. They talk about AI much more than they do in the conservatory. And they do encourage you to use AI a lot more in the college than in the conservatory.
[00:25:45] Abir: In the conservatory, I don't really hear people talking about AI at all. When I do hear people talking about AI, when I hear students talking about AI, it's never in a positive way and it's never in a nuanced way. It's always in a negative way. It's always anti AI, that AI is a problem that we need to get rid of.
[00:26:06] Abir: We're all concerned about the environment. We're concerned about how it can unethically create content without care for the people's work that it's using or for the humans that they're replacing. And we're definitely all concerned about the job market and how it's more difficult now because of AI.
[00:26:21] Abhishek: Abir, I also wanted to know about your personal use of AI. Have you been using AI and in what form? Besides your music classes, of course, your app, besides your app and your business and entrepreneurship classes. If you could tell us a little bit about your experiences, I think the listeners would find it helpful.
[00:26:45] Abir: Yeah, definitely. I'm using it for various coding classes or I have used it for various coding classes to write code for me or to explain code that I don't understand. And that's been super helpful because as we're working with code, a lot of the ways that our professors have taught us is that we're looking at code chunks and we're not learning about each individual specific aspect of the code, but we're looking at as a whole. And I think I found that AI has helped me understand that better or reinforce my understanding. I've also just been in general using it across all my classes outside of business and music as a way to fill in gaps in my own understanding where I have my own notes, maybe I can use it to organize my notes better in a way that I could better understand. Or if I have to share any information with someone, maybe I can use AI to word things a little differently or word things more formally. So yeah, I think it's been really helpful for me in filling in gaps in my own understanding, explaining things that have been put in ways that I don't understand at first and making me understand things better.
[00:27:55] Abir: Yeah, I have used AI I'm using in my job applications right now to like, use it as a template for things like my resume and cover letters. I never treat it as the final thing. And I think that's where like my liberal arts education, my good education in general comes in, where I know where I fall short and where I can improve upon it.
[00:28:19] Abhishek: I want to sort of follow up on this question. Where have you seen AI genuinely helping you and where do you think AI is genuinely helpful when it comes to student learning? And you mentioned about your concerns at the beginning of this episode. So where has it become? Where do you feel it could easily become a shortcut that undercuts learning?
[00:28:45] Abir: Yeah, I'd say that AI is useful when you don't let it do everything for you. When you have some sort of starting point, hopefully a good starting point, when you can use it to fill in those gaps in your understanding, I think it can be very helpful or to organize information that you already have. So, yeah, when you start with something or some understanding of what you're doing, I think then it can be very helpful and allowing you to take next steps or finishing a task.
[00:29:12] Abir: Where I see it could undercut learning is when you use it to do every part of a process. That's when you miss out on understanding, and I think that's where you miss out on having the best results. I think that's very true. Especially true when you have it summarize like a reading, for example, that you have not interacted with, or when you have it write a whole essay for you or something like that. And yeah, that's where I do really think that a good liberal arts education really comes in handy. Where you can see where AI falls short, you can recognize where it falls short and where you need to improve upon, where you need to update it upon what it gives you and treat it as a very basic template for what you're doing.
[00:29:58] Abhishek: Yeah, I'm glad to know that you're sharing these things with us because on the faculty side, we are concerned about cognitive offloading and we do want, at least I do want students to have some experience with AI because the world that they will be going out to is probably already using AI, but it seems like it's a skill to know how to use it in a good way, in a constructive way.
[00:30:31] Abhishek: I want to ask. Our conversation has been about AI, and that's the theme of the podcast. I want to ask what's the question about AI that you haven't figured out yet? And this could be related to your personal experience and this could also be related to your startup, your team.
[00:30:53] Abir: Yeah, I think in terms of our app and our team, a question we're really grappling with right now in terms of AI, is what personalization looks like, whether that's personalized feedback, whether that's personalized teacher profiles, like having different kinds of personalities of a teacher or a coach for our users to interact with, or is it personalized practice tools or a combination of those, some combination of those. And along similar lines, we're trying to figure out, you know, what, what we need to know about our users in order to achieve that personalization, what exactly we need to know about them in order to personalize their learning. So we're really, really trying to understand AI's capabilities and adapting to user needs, but also seeing how we can best have that AI coach interact with a human teacher's feedback that we certainly value, hopefully above the AI coach that we're, that we're working with.
[00:31:53] Abhishek: All right, thank you for sharing that. What advice would you have for a current student about future career, about their AI mindset? I asked this because you mentioned that you're preparing to graduate this this year and definitely good luck, best wishes for your future. So I feel like it's a timely question that if you want to say something about it. And also I want to add another possibly heavier question, which is what advice would you have for us faculty as part of the overall Lawrence community?
[00:32:33] Abir: Yeah, sure. I would say to fellow students that it's important to not be fully anti AI or fully pro AI. It's AI is a part of our world and I think we need to embrace it at least a little bit in order to be able to secure good positions in our future and in order to be efficient in our work. Because I think people that are involved with AI right now and have been early on, they will be able to get ahead much faster and much quicker and much better than people who are not involved with AI. So because of that, I would tell faculty that you should encourage the use of AI and students work because it is impacting every field. I would never have expected it to impact music as it has as we're doing with it right now. And then while you encourage that use of AI, I think that is your chance to also emphasize the value of a liberal arts education and the value of creative work, because those studies is what I think will be useful in determining how we use, how we adapt, and how we regulate AI.
[00:33:41] Abhishek: All right, cool. Abir, thank you so much for your time and for sharing your thoughts. I usually end by asking guests, what are you working towards and building towards and what's on your mind in the next few years? I think you've already answered those things. You are planning to work with your team on the app. You are preparing for graduation. Is there anything happening that's exciting? Not that those things are not exciting, but is there anything else that you want to share with our listeners.
[00:34:14] Abir: I guess I just say that I'm going to just keep myself open to different opportunities in business and music and yeah, I'm just excited for the future in general.
[00:34:25] Abhishek: All right, cool, thank you so much. To our listeners, thank you for tuning into Minding Machines. Full show notes, resources mentioned in this episode, including Abir's app, and a complete written transcript, are available on our podcast page. If you have an idea for a future topic, a question you would like us to explore, or if you have suggestions for guests, whether they're educator, colleagues or students, please reach out through our feedback form linked in the Show Notes.
[00:34:52] Abhishek: This episode also wraps up the fall 2026 season of Minding Machines. My sincere thanks to our listeners and Lawrence University for their support. Until next time, stay curious and keep prompting thoughtful questions.
[00:35:07] Abhishek: Minding Machines is an independent podcast produced at Lawrence University. The views expressed are those of the participants and do not represent the university. This podcast is also separate from my teaching and research roles at Lawrence University.