Maya's Melody to Millions: Pioneering AI in Music Before the Hype

Guest Background:

Maya Ackerman, PhD., the esteemed CEO of WaveAI, has been a pioneering figure in the AI industry, leading her company to multimillion-dollar success well before the widespread recognition of AI in 2022. Recognized as a 'Woman of Influence' by the Silicon Valley Business Journal, she also serves as a professor of computer science focusing on AI and ML at Santa Clara University. Her distinguished career, marked by a Ph.D. in Computer Science from the University of Waterloo, reflects an exceptional blend of academic excellence and profound expertise in technology and innovation.

This blend of expertise found a unique expression when Maya rediscovered her passion for music. Initially studying piano in her early years, her musical journey was interrupted due to financial hardships following immigration to Canada. At 27, she reignited her love for music, ingeniously intertwining it with her vast knowledge in computer science and AI. This fusion led to the founding of WaveAI in 2016, an innovative platform at the intersection of music and technology. With products like Lyricstudio and Melody Studio, WaveAI empowers new forms of human expression, bridging the gap between art and AI.

Under Maya's visionary leadership, WaveAI has not only emerged as a pioneer in the AI music industry but also as a key player well ahead of AI's mainstream surge. Today, WaveAI is expanding its impact by fostering partnerships and nurturing emerging startups in the AI music sector.

Maya's story is not just one of overcoming adversity, but of turning personal trials into a force for global change, ensuring that music, her once-lost treasure, is now a gift she shares with the world.

This episode is a goldmine of insights, blending academic knowledge, artistic creativity, and entrepreneurial wisdom. 

Time Stamps: 

• [00:00:03] Introduction to Maya Ackerman
• [00:05:09] Maya's Childhood Journey and Early Years
• [00:14:27] The Evolution and Impact of AI in Music
• [00:24:50] A Student Project to A Multi-Million $ Business
• [00:28:43] Exploring Human-Centered AI: Balancing Innovation and Ethics
• [00:37:43] AI's Impact on Employment in the Music Industry
• [00:52:20] Waveai B2B Partnerships and Expanding Creativity
• [00:55:37] Addressing Copyright Issues in AI-Generated Music
• [01:02:32] Building a User Base 
• [01:11:03] Gender Bias in VC Funding
• [01:20:00] Maya's Advice for Aspiring Entrepreneurs
• [01:21:43] Concluding Remarks and Final Thoughts

Guest Info:

Website: Maya Ackerman
LinkedIn: Maya Ackerman

WaveAI Info:

Website: Waveai-ai.net
Instagram: @lyricstudiopro & @melodystudiopro

Tryout LyricStudio & MelodyStudio

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Chapters

• 0:03 Introduction to Maya Ackerman
• 2:55 Fun Question: Maya's Favorite Musician and Musical Influences
• 5:09 Maya's Childhood Journey and Early Years
• 7:32 Relearning Music and Piano in Adulthood
• 14:27 The Evolution and Impact of AI in Music:
• 18:53 Marketing Strategies for Startups with Limited Budgets
• 24:50 A Student project to A Multi-Million $ Business
• 26:24 Mission of Wave.AI
• 28:43 Exploring Human-Centered AI: Balancing Innovation and Ethics
• 32:36 The Concept of Truth in AI and Information Bias
• 37:43 AI's Impact on Employment in the Music Industry
• 41:56 Preparing Musicians for AI Integration and Change
• 52:20 Waveai B2B Partnerships and Expanding Creativity
• 55:37 Addressing Copyright Issues in AI-Generated Music
• 58:22 Could AI music win Grammys and Awards?
• 1:00:59 The Role of Voice to Voice Technology in Music
• 1:02:32 Building a User Base and Marketing Strategies
• 1:05:29 Communicating Technical Concepts to a Non-Tech Audience
• 1:07:36 Navigating Challenges and Rejections as an Entrepreneur
• 1:11:03 Gender Bias in Venture Capital Funding
• 1:20:00 Maya's Advice for Aspiring Entrepreneurs
• 1:21:43 WaveAI and its full Potential
• 1:23:38 Concluding Remarks and Final Thoughts

Transcript

[00:00:00] Introduction to Maya Ackerman
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[00:00:00] Maya: And it's just, it's almost like you're a discoverer, you know, you're going around and you discover this mountain of gold.

[00:00:07] Maya: And you're like, how come nobody else can see it? Is nobody else seeing it? Really? Um, and then even I would tell people about it and they, they couldn't, they still couldn't connect the dots. It was crazy. It was really only like the past year when generative AI finally became hot, which is surreal for me, that now it's the hottest thing, 

[00:00:30] today's episode features Maya Ackerman CEO of a startup that was already making millions well before AI became a buzzword in 2022. Recognize as a woman of influence by the Silicon valley business journal, Maya holds a PhD in computer science from the university of Waterloo and has completed a postdoctoral fellowship. At Caltech in computing. She's also been teaching AI and ML at Santa Clara [00:01:00] university for years. Going back to Maya's childhood. It was remarked by significant moves, transitioning from the USSR to Israel and later to Canada. She began learning piano at the age of 8, showcasing her talent to performances in Israel. However, the family's relocation to Canada when she was 12 brought some financial hardships, which unfortunately halted, her deeply cherished passion for music. Making a tragic turn. In her life. These early experiences taught her about the injustices and unfairness of the world. Maya story is not just one of overcoming adversity, but also about transforming those personal trials into a force for global change. She ensures that music, her once lost treasure is now a gift to shares with the world. Join us [00:02:00] in this conversation to gain insights, blending academy, acknowledge artistic creativity and entrepreneurial wisdom. 

[00:02:10] Sam: Maya, welcome to the entrepreneur's road. I'm so, so excited that you are here today. Like, it's an honor and a privilege to interview you. You've been called Woman of Influence by Silicon Valley Business Journal. You have been teaching, Computer science with focus on AI and ML at Santa Clara University for years and way before that AI was a buzzword. You were in AI within the music industry since 2017. You had your own startup wave AI so I am so excited to delve into this conversation with you. 

[00:02:49] Maya: Thank you so much for having me. It's a pleasure to be here to speak with you. 


[00:02:54] Fun Question: Maya's Favorite Musician and Musical Influences
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[00:02:54] Sam: Awesome. Thank you, Maya. And before we actually like start getting into [00:03:00] all entrepreneurial stuff, I want to start on a fun note.

[00:03:04] Sam: How does that sound? Sounds amazing. Okay, great. So I want to know who is your favorite musician and it could be anyone that like maybe inspired you someone that you rocked to their music or someone that touched your heart in some way or shape. 

[00:03:23] Maya: You know, this is such an important question. And so many people have their favorite artists.

[00:03:32] Maya: I think what makes me a little bit different is that I like almost all genres of music, which is, with like very, very few exceptions. I'm opera trained, you know, there's like Maria Callas, uh, in there. And then, you know, of course I listen to popular music, I listen to music in other languages. So it's, um, it's very, very, I don't have a favorite artist.[00:04:00] 

[00:04:00] Maya: You know, I just like sang some John Legend for you before we started, but obviously, you know, I, I love antihero by Taylor Swift. And it's, yeah, it's almost like I can't pick favorites when if you are there. Kind of moving the music industry forward you can't play favorites and I naturally don't have favorites I I'm just in awe of so much music new and old.

[00:04:30] Sam: Yeah. Well, I I'm the same so when people ask me that question, I I can't pick a favorite artist because Exactly what you just said I like artists and specific songs in different genres That makes total sense. 

[00:04:50] Maya: Picking your favorite people. 

[00:04:52] Sam: I don't know. Yeah. Yeah. No, no. 

[00:04:56] Sam: , I'm guilty of like when I was younger, I guess when I was a teenager, maybe I [00:05:00] would post on social media, this is my favorite person, but like,, no, I can't choose a favorite person. Everyone are great. In their own unique way. 


[00:05:09] Maya's Childhood Journey and Early Years
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[00:05:09] Sam: I would love to start on a little bit about your childhood journey and early years.

[00:05:15] Sam: Yeah, 

[00:05:15] Maya: sure. Uh, just how it all 

[00:05:17] Sam: happened. Just tell me a little about it. , take us how life was for a little Maya. 

[00:05:24] Maya: So, um, I was born, uh, the second child, second daughter of a Jewish family in Belarus. Um, and, um, I lived there until I was seven years old. My family actually managed to get out just before the collapse of the U.

[00:05:41] Maya: S. S. R. So that was really, really important to sort of get out right in time because the year, excuse me, about six months after we left in 1990. Um, that's when there was sort of a lot of starvation and a lot of kind of complete economic collapse as the country tried to reconfigure [00:06:00] itself. So I lived through communism, which is kind of crazy.

[00:06:03] Maya: As a little girl. And then I spent five years in Israel, in kind of like a little, tiny, middle of nowhere place called the Fula elite. iT was like, um, like not, not an affluent neighborhood by any stretch. Uh, it was amazing. It was incredible. And then when I was 12 years old, after, um, you know, certain events transpired, we moved to Canada.

[00:06:29] Maya: And that's where my North American journey began. Uh, and it was really rough. In Israel, I learned to play the piano as a little girl. And my parents couldn't afford an instrument when we moved to Canada. And sort of like music disappeared out of my life for over a decade. Um, Declamation in Canada was complicated, you know, it kind of sounds so glamorous, move to Canada.

[00:06:54] Maya: It's like, well, it was not good for many years. And in fact, a lot of my, uh, grit and a [00:07:00] lot of my ability to sort of persevere and tolerate discomfort come from those early years. And, uh, Eventually went to computer science. I always wanted to be like, I want to be a musician, but you know that I didn't have the opportunity to practice and actually picked up music again during my PHD in computer science. I learned to sing opera, and that's when I finally bought myself an instrument and I've had a piano in my home pretty much ever since. And I've been in the States now for 11 years. It's a very very quick journey through my life. 


[00:07:32] Relearning Music and Piano in Adulthood
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[00:07:32] Sam: Yeah, thank you for sharing that.

[00:07:35] Sam: Um, so you had a disconnect, of performing from, when you were in Israel and then moving to Canada. So like, how did this transition impact your relationship with music? And how did you navigate that challenge of relearning again? I 

[00:07:55] Maya: think, you know, it's so funny for me how many kids, how [00:08:00] many parents try to force their kids to play piano.

[00:08:02] Maya: Like, it was literally like a tragedy in my life that I, that my parents couldn't afford to buy me one. Um, and they did. They were able to get me like a little tiny keyboard. But it's not a piano. There's a big, big disconnect there. And they couldn't afford to get me lessons. Um, so I just sort of started to die after a while.

[00:08:22] Maya: You know, you don't practice. You don't move forward as a little kid. And I tried, like, finding other creative outlets, but everything requires some kind of investment on the parts of the family, uh, and so it was very difficult. Part of the reason I went to computer science is because, you know, I wanted a career path that, where I could kind of support myself, but also I really fell in love with it for completely other reasons.

[00:08:48] Maya: I felt this kind of sense of magic and creation that came as computer science was, you know, coding. I thought it was so cool for so long. And then as an adult, I didn't really realize that I even could, [00:09:00] at age of 27, get back into music. So just really embracing that and realizing that I can still learn things and I can get into singing as an adult.

[00:09:11] Maya: I relearned piano as well in my 30s. It was just kind of eye opening that it's not over if you didn't do it as a kid. 

[00:09:20] There is a nice and beautiful feeling with being a beginner and learning something and, um, progressing in it. It just feels amazing once you're getting ahead and ahead.

[00:09:32] Sam: But, how, how was that for you? Was it at times frustrating? Well, 

[00:09:36] Maya: I've, I have 10 years of education in computer science, right? I have a double degree, one in math, one in computer science. I started doing foundational machine learning, which is basically math applied to computer science during my master's and PhD.

[00:09:49] Maya: And I was forced to learn three languages as a little child. So like Learning is something I have a very healthy relationship with. It's something that I [00:10:00] find deeply gratifying. I enjoy the challenge of it. I really like that phase of learning where things are really hard. I get some sort of satisfaction for it that's almost I don't even know if it'd be good if everybody was like that.

[00:10:16] Maya: I mean, I spent my undergrad just studying all the time. That's all I really That was kind of like the main thing that I derived pleasure from and only later in life, you know, found a little bit of balance. Um, it's just who I am. It's not, uh, That's what I found worked for me and I enjoy the process and the fact that it's helpful in life to be able to learn things is almost like a nice side effect.

[00:10:44] Maya: I don't know if that's 

[00:10:45] Sam: a good answer. No, that's, that's a great answer. 

[00:10:48] Sam: And, um, how did you come across Wave AI, which initially was Alicia, a project that you were doing, , if I'm correct?[00:11:00] 

[00:11:00] Maya: Yeah, so that's, uh, That was really kind of my life's journey. So as I pointed out, I'm primarily a computer scientist. I kind of went all the way with my education, got a PhD, then I did postdocs San Diego. I then became a professor originally at Florida State University. Um, at the same time, I continued my musical journey that I'd started in grad school, which is, I was performing semi professionally pretty much that whole time.

[00:11:26] Maya: I started producing my own music, and I really wanted to create my own songs, to compose them from scratch. Which I was able to do, but they kind of all sounded like the folk songs that I grew up on, with. Which is actually quite normal, um, that's kind of what your brain is almost imprinted with. But I wanted to write something modern, right?

[00:11:44] Maya: And I wanted to write something that was actually connected with what I was feeling. And I just tried and tried and tried. I even tried to hire some teachers. And then in 2014, I discovered an academic community called Computational Creativity. This is 2014. This is a long time ago, [00:12:00] before the rise of generative AI.

[00:12:02] Maya: That group of about 150, maybe 200 scientists, mostly out of Europe. They were doing generative AI back in 2014. Wow. They were doing it for years before I discovered the community. Um, I was like, why is nobody talking about this? There are machines making art and music, condensed choreography and recipes, and nobody cares.

[00:12:22] Maya: How is that possible? I was like, stunned and very, very quickly upon discovering that research community and joining it, the dots get connected. Like literally when I attended the international conference on computational creativity. Spilled some water on my laptop. So, you know, I was really paying attention to the first talk.

[00:12:40] Maya: And somebody in passing said, um, Oh, and of course a machine can be a co creative partner. Everything froze for me. Everything froze. Like my entire life came together in one instant. A machine can be a co creative partner. A machine can be a partner in me writing my songs. It can take care of the parts I'm struggling with.

[00:12:59] Maya: I [00:13:00] got so excited. And that, like, incredibly high level of excitement is sustaining me now, almost 10 years later. Uh, it's, it was such a magical moment. I remember wondering, like, did I just, like, make up not just a research project, but, like, a product and a company? And it's just, it's almost like you're a discoverer, you know, you're going around and you discover this mountain of gold.

[00:13:23] Maya: And you're like, how come nobody else can see it? Is nobody else seeing it? Really? Um, and then even I would tell people about it and they, they couldn't, they still couldn't connect the dots. It was crazy. It was really only like the past year when generative AI finally became hot, which is surreal for me, that now it's the hottest thing, okay?

[00:13:48] Maya: Now, finally, there is some kind of understanding on how massive this is. But yeah, but I feel like I just, because of my specific life experiences, I was able to see something that was [00:14:00] just there, an opportunity ripe for the taking. Um, so we did research for three years, published papers on it, got some media attention, and in late 2017, opened WAVE AI, still a little early, given, you know, what happened last year.

[00:14:13] Maya: But we're also, as a result, um, we're really ahead of the curve and ready for this moment in a way that would not have been possible if we, you know, tried to rush to do it right now. 

[00:14:25] Sam: Wow. That's, that's incredible. My background is more business and it's not technical, but like, I can't imagine being in your community and finding this, as you mentioned, gold and Realizing like why is no one talking about it and so when you would go and talk about it, people still wouldn't pay attention.

[00:14:46] Sam: That's crazy. So, but at the same time, I'm maybe there was not use cases for people to try like you know how we ChatGPT is like right there and anyone can use it and try [00:15:00] it and see like what incredible things that it can do. There were plenty of use cases. 

[00:15:04] Maya: There were?

[00:15:05] Maya: Okay. I mean, when I, when I joined the research community, we had machines making art and music and poetry and writing stories. 

[00:15:11] Sam: So they were in your university within the community? They were 


[00:15:14] The Evolution and Impact of AI in Music:
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[00:15:14] Maya: mostly in Europe. There are some North American ones. The particular conference I attended happened to be in Park City that year.

[00:15:22] Maya: So um, The machines existed. What, how, what started happening around 2016 is a company started entering the space. So Google released, , Magenta, you know, started playing around with some elementary music generations, you know, which got a little bit more interesting over time. Um, then IBM had IBM Watson and they had like Watson Beats, which also played around with music.

[00:15:46] Maya: Um, Google actually had kind of an interesting approach. It was really focusing on exploring the limits of a certain machine learning approach. Anyways, um, these companies got a ton of press. And so some of the stuff that was coming out was not as good as [00:16:00] some of the stuff we had in academia, like objectively not as interesting, but academics don't have PR budgets and the way our world works, something that I learned, it's pretty obvious in retrospect, is that if you don't have a PR budget, you could cure cancer.

[00:16:15] Maya: And honestly, I think nobody's going to care if you can't popularize it. You could find the cure for immortality. And if you can't convince people to care, they're not going to care. The ability to get your word out there and have proper PR and have a budget that's what moves the needle for what the world cares about.

[00:16:34] Maya: Why do politicians spend so much money on, on like PR and the media? Because it's not about, well, at minimum, it's not just about the substance, right? That marketing layer is critical. And so you have like a ton of articles saying this is the first song made with AI. How many first songs made with AI can we possibly have?

[00:16:59] Maya: Right? So it's really [00:17:00] like it's not an attempt to be accurate. It's an attempt to promote specific agendas. An attempt to elevate certain companies. And so OpenAI, really their biggest accomplishment was taking research in academia, which was already talking about creating these machine brains. And we have the systems.

[00:17:20] Maya: This is not abstract. There were systems out there. Some of which, there was one Uh, called Impro Visor, for example, an amazing system for improvising together with a machine. It was public and free. Wow. Right? So it's, and by the time that I was telling people about our stuff, there were demos, there were public products we had, so not being able to try it was never a problem.

[00:17:42] Maya: OpenAI had a couple of things, uh, which helped it kind of bring awareness to this. And I'm really, really grateful to OpenAI for like, OpenAI and Stability too, for bringing awareness to this. So there were two things. First of all, they took the research and they poured way more [00:18:00] money than any researcher could have ever hoped to have.

[00:18:03] Maya: And they built these massive machine brains. The researchers could only afford to build little tiny brains. And suddenly they could afford to train on their, on the entire internet. That's the innovation. Okay. It wasn't that they invented generative AI, but we had machines in the 80s. There is like a system called Aaron that was an automated painter.

[00:18:22] Maya: And a system called Amy, EMI, that was an automated musician. That was incredible made by David Cope. Anyways, um, Aaron is by Harold Cohen. So these are old ideas. So making the machine brain much bigger. Enabled some new emergent behavior that is quite fascinating, but the old machines were already fascinating.

[00:18:42] Maya: They were already fascinating. And in fact some stuff that we have had since the 80s could still be commercialized and still be amazing to today's people. The other part, of course, that OpenAI had, if they had the money. 


[00:18:53] Marketing Strategies for Startups with Limited Budgets
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[00:18:53] Sam: WEll, it's so sad to know that this really, um, intelligent, generative [00:19:00] AI was already there and We couldn't use it because we didn't know about it.

[00:19:06] Sam: It's really sad. And there is a lot of entrepreneurs out there that, um, they have like, I guess, products and they, maybe not have the right budget to advertise their startup. Maybe they're working on a great mission. So what do you think now that we are living in a world that We still have social medias that are free.

[00:19:29] Sam: So basically everyone can be their own news outlet for free, which we didn't have that like years ago. So this could be a positive side. How do you think entrepreneurs can leverage that in order to , promote what they're passionate about, promote what they're working on? 

[00:19:46] Maya: So you created something amazing and now you want someone to know. Um, that's very, very difficult. I would say that that's probably what kills most startups. Not that they don't have, look, not all ideas are great and not all products are [00:20:00] great.

[00:20:00] Maya: But even if you just look at the great stuff out there, unambiguously, incredible innovation, a lot of them fail, a lot of them fail. And so if you want the whole world to hear you, to try your products. That's, that's very complicated and it's going to take a ton of persistence. There is no clear path to that.

[00:20:20] Maya: I mean, most of the time going on social media, you're screaming into the void, right? Like if you want to build, if you already have an audience, I mean, awesome, leverage that. You know, if you're that small percent of people who really have a good, healthy audience, that's amazing. But most people, most people come in with some kind of strength, right?

[00:20:39] Maya: Maybe they're an amazing marketer or maybe they're an amazing technologist. Maybe they recognize, maybe they're an amazing business person, right? Hardly anybody comes in with everything. And so, it's just something that most people have to figure out. And, in the end of the day, I mean, it just takes persistence.

[00:20:57] Maya: You try something, and it fails. [00:21:00] And you try something else, and it fails. And you, like, improve your product. And you try a different marketing channel. Um, and you try to get some funding. And if you get some funding, you try to utilize it in the best way. To try to get more, in part, to try to get more awareness to what you're building.

[00:21:15] Maya: I really don't think that there is any sort of universal rulebook here at Wave. ai. We've done everything, like, everything we could possibly think of. Like, for example, when we launched Lyric Studio, we had 10, 000. 10, 000 left. Of course, we weren't drawing any salaries. And, uh, I have a really good friend.

[00:21:34] Maya: Who is a self published author, and in fact, at times was one of the most well read authors in the world. Wow. And she did it all herself, and she did it with online advertising. Hmm. So this was still at a time when online advertising worked fairly well, so she taught us how to do that.

[00:21:51] Maya: And we spun the 10, 000 into over 600 in revenue that year. Wow. Uh, and that kind of helped, uh, get enough [00:22:00] traction to get a pre seed round. And then sort of continue to grow things from there, but then, recently there have been challenges that some companies are facing around online advertising.

[00:22:11] Maya: And so we've tried a whole bunch of other stuff. We've done a blog. Um, we've done influencers and we've tried everything under the sun. And ultimately, even when you figure something out, you might then have to go from scratch when the world changes. And so it's. It's a constantly evolving system, you just can't give up.

[00:22:34] Maya: If you know in your heart that you have something great, you can get all the signals in the world that what you have, nobody cares about. But if you know that you have something, then you have, you always have the option to persist and to try another channel and to try a different approach and to try to get another person excited to help you and to try to get another investor excited too.

[00:22:57] Maya: you know, help you financially. Um, [00:23:00] we've had millions of songs made with our platform. We've had number one hits. We've had viral songs. We have about 10, 000 people a day playing with our AI and I feel like this is still like such a tiny percent of what we set out to do, you know, you think it gets easier.

[00:23:15] Maya: Really?

[00:23:19] Sam: I can't imagine because, um, every second is just changing and change is just part of the process. You are done with one fire, another one starts, another shift. Um, but before I ask more about your startup, I don't think like I asked you what does Wave AI does. 

[00:23:41] Maya: Yeah, so Wave AI, fundamentally, our role is to support musicians and technologists with the best musical AI platforms.

[00:23:53] Maya: So we are, our strength is creating AI systems that can assist [00:24:00] the human musician, the human user in making music. And we have our direct to user systems like Lyric Studio and Melody Studio, which are powered by our own AI. But we've done everything. We made the AI we build the U. I. U. X. Um, we do all the promotion.

[00:24:16] Maya: So that's that its own kind of its own kind of magic to create that whole pipeline. And then, of course, we learned so much from our users. And then on the other side, um, Recently, we have been focusing more and more on supporting other companies who are either already in the music space or new startups that want to be in the music space and who are looking to either enhance our offering or kind of create a new offering centered around musical AI.

[00:24:46] Maya: And so we provide that AI to these other companies, which is also super 


[00:24:51] A Student project to A Multi-Million $ Business
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[00:24:51] Sam: fun. So just going back to the history of wave AI and then I'll have some follow up questions about like your new strategy, [00:25:00] which is like helping more, um, other startups. But how did that like projects turn into a business?

[00:25:08] Maya: Yeah, it was the moment that I had the idea back in 2014, I felt that this is probably should be a business. Um, but as we released the research, and you know, we built a system where you gave it lyrics and it would find different ways that you could sing them. So for example, This is such a cool red wall.

[00:25:29] Maya: How can you sing that? This is such a cool red wall. Or maybe, This is such a cool red wall. Right? There are so many ways that you can sing any one phrase. And so that was the hardest part for me, sort of exploring that space of melodic possibility. So we built a system that did that. We got some media attention, which was cool.

[00:25:49] Maya: Some people asking to use it. And then it just became really, really, really obvious to me. That if we just continue this as research, it's not going to have any serious impact. I [00:26:00] wanted people to be able to use it. And if when you want people to be able to use it, you don't like hope that somebody will one day commercialize your stuff.

[00:26:10] Maya: You got to do it yourself. And so that's why in 2017 we decided to commercialize it. I think I Pretty much my whole life up until that moment in 2014 was preparation for that moment. But when you see it, you see it. So I knew it had to be a 


[00:26:23] Mission of Wave.AI
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[00:26:23] Sam: product. Absolutely. And what impact, Wave.

[00:26:28] Sam: ai, was hoping to make, , on the target audience that you were serving? You know, 

[00:26:35] Maya: songwriting is such a personal thing. We listen to songs because we want to understand. We want to, heh, we want to communicate with other people, really. A songwriter, a musician, communicates their feelings through their songs.

[00:26:51] Maya: And, uh, it's deeply therapeutic. So, for example, we were able to show that, um, [00:27:00] in a bereavement study, we were able to show that writing songs with our AI helps people process their bereavement. It's healing for them. I think it's good to have tools that help you express yourself. Self expression is healing.

[00:27:14] Maya: Self expression is therapy. And so, um, I mean, we've had these incredible, like, simple songs made by people who are new to songwriting. There was this one song about A girl talking about her math teacher being mean to her and the kids bullying her. Simple tiny little song, but it was so human. So if we're helping this little girl share some of her pain, maybe in a way that she can't do quite as honestly in other contexts, that's a big deal.

[00:27:44] Maya: I think that's a really, really big deal, helping people express themselves. The products, you know, Lyric Studio, Melody Studio, are really built with the idea that the human Is conducting the show. The human is in the driver's seat and the AI is there to help. And that's beautiful. [00:28:00] And people, you know, there's so much, um, Legitimate fear about AI these days, but our users really like to highlight How much they find the AI helpful rather than hindering.

[00:28:14] Maya: And that's, uh, in the end of the day, the core of the mission. 

[00:28:18] Sam: Absolutely. Um, my brother is a musician, so I am very grateful that just because of him, I sang a few songs at some karaoke nights with my family. It's like really like it's such a release in energy. I love it. Um, and we're gonna like try a few songs today Just please don't laugh at me 

[00:28:40] Maya: I'm so excited to hear you sing Yeah 


[00:28:43] Exploring Human-Centered AI: Balancing Innovation and Ethics 
---

[00:28:43] Sam: Um, and I really love the concepts that you touch base on that AI can be helpful and The concept of human centered AI, if you can a little tell our audience, what does that [00:29:00] mean?

[00:29:00] Sam: And how can we shift our focus from AI replacing us by human centered AI that AI can just like help us instead and elevate us? 

[00:29:15] Maya: Yeah, great question. It's very complicated. Because AI is neutral. The AI doesn't care what you do with it. Um, and the truth is that with almost any innovation, you can apply it in a way that helps people, you can apply it in a way that hurts people, you can also apply it in a way that helps only certain people and hurts other people.

[00:29:39] Maya: It's complicated. The truth is complicated. Um, that's why when musicians express concerns to me, Over time, I've become more and more sympathetic to them, and I think, um, I think some of their fears are legitimate, and should be taken really, really seriously, especially by people building companies around musical [00:30:00] AI, or AI in general.

[00:30:02] Maya: So, that's really, really important. The way that I like to use AI, the use cases that I'm excited by are those that support human creativity. The extent to which AI can support human creativity is surreal. I mean, look at what we've created. Just okay, let's look at some of the most famous use cases, the large models like Midjourney and ChatGPT

[00:30:27] Maya: sure. We're taking the creativity and intelligence of to simplify all of humanity, right? This data that we have accumulated over At least decades, if not centuries, really centuries to some degree, and we're able to train these machine brains on these insane amounts of data that no human could ever hope to consume.

[00:30:47] Maya: So if you design the systems, which is a critical part here, if you design them to really collaborate with a person, you're essentially collaborating with an entity that embodies the creativity of the entire human [00:31:00] race. That's why all the possibilities are surreal. By not focusing on that, we're missing, really, we're missing the opportunity to evolve humanity.

[00:31:12] Maya: A real step in human, human evolution is at our fingertips. So the positive side here is incredible. What's missing sometimes is the right attitude, right? We're so focused on traditional use cases, have the AI be accurate and have it do all the boring, annoying stuff that we Are trying to take this creative magical entity and turn it into like the servant robot.

[00:31:40] Maya: We're so stuck in this servant robot mindset. The job of the AI is to just be fast and accurate and make my jobs easier. Um, That's not what we're dealing with here is generative ai. That's not the greatest opportunity. And so people get frustrated at ChatGPT hallucinating. It's a fundamentally [00:32:00] hallucinatory object.

[00:32:01] Maya: It's this imaginative being, it's gonna hallucinate if open AI ever manages to get it to stop hallucinating. I'm not even sure what that could look like. Mm-Hmm. From a technological standpoint, it's, it's just like taking something and trying to fundamentally turn it into something else. Um, so yeah, I think we should lean in to the creative aspect of AI and stop thinking about it as our servant that must always be right and really lean into what it really is, which is an opportunity for us to be creative on a level that was inconceivable previously.

[00:32:33] Maya: That's at a high level. Mm hmm. Mm hmm. 


[00:32:36] The Concept of Truth in AI and Information Bias
---

[00:32:36] Sam: And you know, when you mentioned we want the ChatGPT to be right, I mean, Do we even have rights? For example, Maybe the narrative of a fact from certain demographic to another demographic is different from each other. Maybe they experience things differently.

[00:32:56] Sam: So if we have like one right truth, isn't [00:33:00] that going to create a lot of Bias and ignore a lot of different experiences that people went through. 

[00:33:07] Maya: What does it mean for a machine to tell us what the truth is? It's absurd, right? The whole goal is a little surreal. I mean, in reality, um, OpenAI was brilliant by reframing a generative model as a chatbot.

[00:33:21] Maya: That's part of what's enabling it to have the success that it's been having with the ChatGPT but it's not a chatbot. It's a generative model. Uh, we should, the chatbots that we have that are accurate out there are extremely limited in scope, right? They're often just, I mean, the most basic chatbots literally just have like a decision tree of answers they can give you.

[00:33:44] Maya: So it's trivial to make them accurate they're dealing with a teeny tiny, like absolutely minuscule domain expertise. And then, yeah, then you can have control and you can argue whether it's true or not. But when you have something in the scope of ChatGPT where you can talk with it about anything.[00:34:00] 

[00:34:00] Maya: Forget about it. Like, you're not gonna get to the truth on everything, do we really want machines dictating what's true and false for us? Yeah, I think we just need to shift our whole perspective onto what machines are in order to make room for generative AI, and also To decrease the risk of misinformation, because if you do look at ChatGPT as a source of truth, the risk of misinformation is guaranteed.

[00:34:24] Maya: It's not even a risk. We need to change our perspective, not just criticize companies. 

[00:34:30] Sam: Yeah, absolutely. And, how do you think we can shift the traditional use cases with novel ones? 

[00:34:39] Maya: Making art, music, ideating, even like scientific research can be aided by generative AI as far as exploring the space of scientific research as creative. Um, recipe creation, dance choreography, anything under the sun. Um, I've seen some stuff around like creating [00:35:00] slideshows. Anywhere where there is human creativity, it's possible to create systems that would push that creativity forward. 

[00:35:07] Sam: Mm hmm.

[00:35:08] Sam: So how do you think Wave AI is contributing to leveling the playing field in music creation, um, particularly in addressing like barriers or disparities that artists might face? 

[00:35:26] Maya: The music industry is very complicated. 

[00:35:27] Maya: Our main focus and kind of like how we came into the space was more focusing on helping human beings express themselves.

[00:35:36] Maya: And it can be a music professional who's already signed, who's writing hits, who wants to kind of expand their creativity, go in a new direction they never tried before. Or maybe they're feeling a little bit stuck. They just need to sort of rejuvenate their own creativity. And we have professionals using our system.

[00:35:55] Maya: A really sizable portion of our users are already people who are musicians. Then there is a [00:36:00] segment of the market, uh, called aspiring artists, and that could be your bedroom producer. It could be your developer by day, guitar player by night kind of person. There's a lot of ways that a person can be an aspiring musician.

[00:36:14] Maya: It's basically music is often their favorite thing in the world, but they're making money in some other way, either temporarily or more permanently. And so helping these people perhaps, perhaps, They don't have someone who can write lyrics for them, and it's an area that they struggle with, so they can use Lyric Studio, so it's almost like Lyric Studio becomes part of their little team, um, or it could be that this is a skill that they actually want to learn, so they can use our tools to essentially become good lyricists, to become a good melody writer, and I love that.

[00:36:48] Maya: I love it when people tell me, Oh, you know, I used to have such trouble writing melodies, and I'm actually pretty good. They might still use Melody Studio to keep pushing themselves forward, but I It actually makes them better pen on [00:37:00] paper songwriters using our tools. And that's a perspective we don't hear about AI at all.

[00:37:05] Maya: Like the AI that, that really helps you learn. Like if you and I collaborate on anything, if we go dancing, right? We might, we're going to learn from each other how to dance, right? I'll probably learn from you, right? Um, but it's, um, well, you know, if, if that's something that you focus on. Um, but it's. Why can't we be learning from an AI if it's, if it's set up if the user experience is set up in a certain way, it can really foster learning, which I think is really important.

[00:37:31] Maya: Yeah, so fundamentally, we are about supporting human creativity, regardless of where a person is in their, in their journey and what sort of end use they might have for their music. Yeah. 


[00:37:43] AI's Impact on Employment in the Music Industry
---

[00:37:43] Sam: Um, that reminds me of, I don't know if this is a big statement or not, but like, how, unfortunately, it's very hard to be a musician for, to be your full time job.

[00:37:55] Sam: I think like the, um, U. S. economy or just [00:38:00] how it is set up, it's not really supporting, , someone to become a full time artist and be, be able to like earn a decent living out of it. So like, it's really great that if there is companies that make the process like easier for you. So you don't have to like spend like.

[00:38:18] Sam: I don't know, 10 hours a day working on becoming a professional musician because there are devices out there that can help you cut that time, , significantly. So I think in that perspective is very exciting. As you said, I'm just hoping, With technologies that we have, it's in the hands of, good human beings that, , focused on, human centered AI, like, people like you that, take this, technology in a way that is responsible and ethical. Appreciate it. 

[00:38:50] Sam: Yeah. Um, so This might be a question that you get asked a lot from other artists. I don't [00:39:00] know what is their number one concern, but I think like you touched based on it a little bit. So with , rise of AI within the music creation, what are your thoughts on its potential impact on employment in the music industry? 

[00:39:17] Maya: So a lot of it is going to depend on how things play out. on which, whether we end up, well, I hope we end up with, in a situation where the tools work together with human beings. Really, musicians need more opportunities, not, not less. And just like, you know, the technologies that support streaming didn't have to have the impact that it did.

[00:39:47] Maya: There were some choices made along the way that ended up cutting into The revenue of artists to the extent that most good musicians can't really make a [00:40:00] normal living these days. So there's a lot of business decisions that come along the way, um, that sort of end up having the impact that we see. So what I'm hoping is that, and definitely what I'm working really, really hard on through Wave AI, is to pave the way to a world where it's more focusing on assisting creatives rather than replacing them.

[00:40:23] Maya: But yeah, it's gonna depend on many factors. Part of that is, , I think musicians having clarity on what they want, and I think, if, uh, we do know that a lot of musicians use AI tools, right? And I definitely do my best to listen , to what artists want. And if they get more and more involved and really kind of get their voices heard on what they don't want to happen.

[00:40:47] Maya: And, but also what they do like, I feel like sometimes we have, which is so, so good that we have. Some clear idea on what they don't want. I'm really, really glad that that's happening. But we also need a little bit more about, okay, [00:41:00] what are they okay with? What is helpful, right? To have some clarity around that.

[00:41:04] Maya: And then hopefully together we shape a world that benefits everybody, that benefits musicians. We need musicians. We love musicians. We listen to music all the time. So I think we need to be appreciating these people and caring about what they want and hopefully, hopefully actually making things better for them rather than worse.

[00:41:22] Maya: But human intent is really important and the intent of the powerful players in the space are really, really important. And so there is nothing that technology can do to override human greed. Um, that's not the role of technology. It's not something that has the capacity to do.

[00:41:41] Maya: And so I think we need ethical people with a deep moral campus, , at least being involved in the shaping of the future of creativity. Mm hmm. 


[00:41:56] Preparing Musicians for AI Integration and Change
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[00:41:56] Sam: So if I was a musician, which I wish I [00:42:00] could be, I don't think I have the talents, but we'll see today. We'll see. but I would want to know how would I get ready for this change?

[00:42:12] Sam: in, shifting the music industry and also, maybe I wouldn't want to just accept it as you said, like, I want my voice being heard, and be part of shaping it. So how would I go about that? 

[00:42:28] Maya: I think there are different things that musicians are doing. For example, there's an organization called ASCAP, which is kind of one of the dominant organizations representing musicians in the country.

[00:42:42] Maya: They are, uh, I went to one of their events, and musicians are very expressive there about what they want, and they're emailing the association, so I was really, really happy to see that that's one avenue where musicians are expressing themselves. We get a lot of emails, my company gets a lot of input from our users, and from people who are not our [00:43:00] users, expressing different concerns and different things that they would like to see us do, and, you know, occasionally sharing things that they like as well, which of course is always a delight.

[00:43:09] Maya: Um, even like, Posts on social media can be helpful. Email companies, attend meetings of organizations. There are different, like, musical meetings, like NAMM, where there's a lot of companies represented, and a lot of panels where you can ask questions, and you can speak with panelists. I mean, I can't really speak for others very well, receptivity to to wanting to hear the voices of musicians.

[00:43:35] Maya: You know, if we're trying to build tools that help artists, You can't do it without the artists. It's completely like when you do see this sort of top down stuff of like non musicians making stuff for musicians, it never works. It never works. It doesn't make any sense. How can somebody be so conceited as to imagine that they know what this group of people needs without interacting with these [00:44:00] people and you, you kind of see this in many different ways.

[00:44:02] Maya: I mean, it's fun technologically, but it's not, it's not going to help those people if you don't work with them. I think the fact that I'm a musician myself is the only reason that we're able to build, that, that I was able to have the vision to build tools that actually help people. But there was a lot of engagement with other musicians along the way.

[00:44:20] Maya: My co founders are also part time musicians, but then we listen to so many users. A lot of people who work with us as employees are also musicians. We kind of like collect both what's called explicit and implicit feedback. We love it when people tell us stuff, but we also pay attention to how they actually use the product.

[00:44:39] Maya: So from that, you also learn a lot of what's actually helping and what's useless. And you watch creative ways that people use your product that you never thought about. So we learn from our users constantly and those who are willing to openly share their thoughts. That's always appreciated. 

[00:44:52] Sam: Yeah. And any entrepreneur that's are working on their startup, I think the first thing is to just to [00:45:00] study your target audience and what they want, test your idea because your idea might not.

[00:45:07] Sam: That's what the target audience wants, um, so, Yesterday, I was listening to the Ghostwriter song of Drake and The Weeknd, , Heart on My Sleeve. And it was like, this is good, like I was like actually jamming on it. And just the fact that 60 percent of artists, they already use AI within their -projects.

[00:45:35] Sam: And the songs like This one, that is really cool. Like just within a few days, it got 11 million views, on social media. And of course, Universal Music Group, they reached out to, the social media platforms and like asked to take this music down. And there are like Other musicians, I guess like a high profile one is Grimms, [00:46:00] that she even made a technology and asked, artists to use her voice and just share, the royalty with her.

[00:46:09] And I'm just wondering, going back to a little bit in the history of how, when artists started sampling on original artists and original artists didn't want the sampling and they felt like it's a threat, but then actually they started like Allowing the artists to use it and it brought like so much creativity and also it benefited them financially.

[00:46:36] Sam: how do you think today or in the future we are going to Change and shifts our structure, the way it is with laws and copyrights and all that to adjust to the new AI world and other artists wanting to use their creative side and create [00:47:00] songs like, um, the ghostwriter heart on my sleeve.

[00:47:04] Maya: Wow. There's so much in there. You hit on so many interesting things with this question. So kind of to address the kind of the ending of the actual question. I think anything that happens will have to happen with the permission of the artists. We saw that with sampling as well. You know, right now there are artists selling loops and samples that they've created rather than, you know, people just stealing their stuff.

[00:47:24] Maya: So I think doing it together with artists Artists is core key and nobody should try to go around that. Um, AI should not make it possible to imitate any artists without their explicit permission. Obviously, how is this not obvious? I don't know how this is not obvious. Like, why did, I mean, I know why, right?

[00:47:44] Maya: Like we had certain very large companies decide actually in their promotion of their tools, they would encourage people to use the tools to imitate artists. That was like literally the prompts that, They were pushing in the beginning and then they stopped doing that. [00:48:00] It's almost like they were trying to see how far they can go and it's, well, why would you want to go to that place?

[00:48:05] Maya: Why would you want to rip off artists to make it possible to utilize their style? That is their bread and butter. Mm hmm. Without their permission there were artists whose works got buried in replicas of their style so you couldn't even find the original stuff. So, terrible. So there's a lot of a lot of nonsense that happened there.

[00:48:23] Maya: So I think I really hope to, I'm seeing a lot of pushback against that, so I hope that's gonna be form, like, formalized, that you can't invite people to imitate to the style of people who have not consented to that, so, that's one area that I think is really important. But you brought up a lot of other really interesting things in the question, which is, you know, Heart on My Sleeve, the, the, the song in Drake's voice, which really had a big impact.

[00:48:48] Maya: A lot of impact on the music industry sort of woke up the industry to generative AI. And what I find really notable there is that the technology, that voice to voice technology, is not generative AI. [00:49:00] That's technology that we've had for several years. It's voice to voice technology, which is, you know, vocal synthesis.

[00:49:06] Maya: Uh, there is, it just falls under a different research bucket. It's not generative AI. Uh, and we've had it for a while, and what you have to do to use that technology is you have to record the song in someone's voice. And then it gets converted and you actually have to sing in a way that's like I can't sing opera and then have a good have it converted to Drake and I can't even sing like with a little bit of a classical tinge and then have it really sound like Taylor Swift with the corresponding technology, which of course, I don't think she gave anybody permission.

[00:49:39] Maya: So just as an example. Um, so it's You really have to sing a little bit. You need to have some, some ability to sing, some ability to minimally imitate the style of the artist. Doesn't have to be very sophisticated for it to really sound like them. Otherwise, you immediately tell that it's not them. So this is not easy [00:50:00] technology to use.

[00:50:01] Maya: And this technology doesn't simplify songwriting. It just makes you sound like someone famous. It's really cool, especially when somebody like Grimes actually wants you to use it. That is cool. Elf tech, which Grimes created. I think that's amazing and it's so many awesome songs were made in her voice now, uh, with her blessing of course, sharing any proceeds with her.

[00:50:24] Maya: I think that's genius and you know, I think more and more artists, probably not everybody, probably it's never going to be everybody, but I think it's going to be like a lot of artists who lean into this specific thing. And there's so much more opportunity than just voice. We can capture so much more with Wave AI technology.

[00:50:40] Maya: We can capture other aspects of a writer's life. of a songwriter's style that go beyond voice and really lean into generative AI and not voice synthesis. It's an interesting moment in time we're living through. 

[00:50:55] Sam: Absolutely. I actually yesterday I joined a discord channel because I was doing [00:51:00] research on the music industry and different new technologies and um, I think that song, um, the heart on my sleeve was first published in that.

[00:51:10] Sam: discord channel apparently and then they closed down the discord channel but they opened it again. I was like, am I being part of something illegal here? I don't know. 

[00:51:20] Maya: Well, the technology for voice synthesis is really simple. Yeah, like they it's open source right now. And anybody who like, you can train based on you know, you would need.

[00:51:34] Maya: Ideally, you do it all with permission, right? But in terms of the technological accomplishments here didn't happen. And when the song rolled out a few months ago, the technological accomplishment was done years ago by researchers, and some people are just brave enough to take open source technology and use it in really blatantly unethical ways without the artist's 

[00:51:57] Sam: permission.

[00:51:57] Sam: Yeah, yeah. [00:52:00] Well, uh, hopefully, it will be figured out, the laws and everything soon enough, um, so we'll see what happens. And please take permission if you want to use anyone's, artistic style or voice. Please don't use my voice, but, so. , you and your companies, we talked about it a lot, uh, you were one of the earlier companies that started in AI industry, and that's why you have so much more, experience and that companies that just started after AI became a buzzword, nothing against them.

[00:52:38] Sam: And then. Recently now they're catching up and this was opportunity for you to shift from a stand alone company to, a background role, as you mentioned, um, in B2B partnership, which is a significant transition. And could you share some insight into managing such a pivot and adapting your business [00:53:00] strategy accordingly?

[00:53:01] Sam: Well, it's sort 


[00:53:02] Waveai B2B Partnerships and Expanding Creativity
---

[00:53:02] Maya: of adding another layer more so than. Um, so it's been surreal to watch what happened since November 2022 to see this entire ecosystem of companies getting funded in generative AI, but also an ecosystem of developers who may or may not even, seek funding, um, explore what's possible in the generative AI space.

[00:53:28] Maya: And, a lot of them are not very technical or at least not technical enough to build their own AI models. So we, uh, pondered this opportunity for a while. Do we want to support other companies, other product creators? And what sort of impacted my thinking the most was that as, as a startup, there's only so much that we can do.

[00:53:54] Maya: You know, we have two products out right now. We're supporting them. We're improving them. But there can [00:54:00] be hundreds. There can be thousands of products powered with our AI that really focuses, focus on different on enhancing existing products, you know, as part of another suite of products, or that can just really dive into different use cases, different things that can be done with songwriting AI.

[00:54:21] Maya: And it's really amazing what a big space that is, of companies that can benefit from our technology, either as part of their core offering or part of enhancing their existing offering. And in reality, by working with our partners, we reach a lot more end users. And with our mission to elevate human creativity, to make it so that more people can express themselves better through songwriting, which I think is one of the most beautiful artistic forms of expression, we can just do it so much better by also partnering with other founders.

[00:54:57] Maya: So it's It's really cool. It's an [00:55:00] opportunity that just opened up this year, really, because of this awakening of generative AI. 


[00:55:06] Addressing Copyright Issues in AI-Generated Music
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[00:55:06] Sam: That's really awesome. And, I will have like some questions for founders and early entrepreneurs. But before we dive into that, I have a copyright question. So how do you foresee copyright laws evolving as AI continues to play a more bigger role in music creation and, what potential changes or adjustments might be necessary, do you think, in the future?

[00:55:36] Maya: Yeah, copyright law. Copyright law is really not designed very well for this use case. You know, they, initially there was a statement about if the AI is used in a, something like negligible or peripheral way, basically if the contribution of the AI is minimal, then it's okay. But like, how can you tell? How can you quantify that?/[00:56:00] 

[00:56:00] Maya: That's not serious. You can't, you can't stop there. And in reality, when, if you and me collaborate on something, if you and me cook together, right, if we make dinner, We are actually very likely to think, like each one of us is pretty likely to think that we did more than we actually did. It's like human researchers were able to show this.

[00:56:18] Maya: Human beings always think that they contribute more than they actually do. Because it's really, really hard to tell, right? Sometimes you know that your teammate did nothing, but most of the time, if both people are contributing, it's so, so, so hard to quantify how much was done by each. And so when I write a song with Lyric Studio or Melody Studio, when any of our users use it, You know, they have some feeling on how much they did, right?

[00:56:42] Maya: But it's very, very hard to be precise about it. And even if they used a whole bunch of lines generated by Lyric Studio, but they are telling their story through it. They did all the curation of the lines. They edited them. And then they went ahead and did all the music for the lyrics, let's say.[00:57:00] 

[00:57:00] Maya: They put a lot of creativity into it. They put a lot of creativity, arguably more, in some cases. I'm not saying in all cases, but in some cases. More so than had they collaborated with another person. So it's, it's just so complicated and it can look, there are so many ways that this collaboration can happen.

[00:57:18] Maya: The machine can do almost everything. I can do almost everything. We can do exactly half half. It can do the lyrics and I can do the music. It's almost like when you're working with another person, there are so many ways it can look. When you're working with a machine, there are so many ways it can look.

[00:57:30] Maya: And my solution is Just give the person the copyright. Just let them have it. Let them have the copyright. We don't keep any copyright from when people use our tools. Really, none of it. I think we shouldn't. We charge for our products a really small amount, so it's accessible to everybody. But then we let the artist run with the content.

[00:57:53] Maya: And I think that's a simple solution. But of course, they're kind of Broader questions here than specifically [00:58:00] our products, sort of in general should, how, how should that be allowed? How should we handle, um, copyright when it comes to images generated with tools like Midjourney, which I love by the way. And a simple solution that I guess that I'm proposing it just let the people have the copyright.

[00:58:13] Maya: But there are complexities within it, depending on the use case. 


[00:58:19] Could AI music win Grammys and Awards?
---

[00:58:19] Sam: so, um, do you think one day like the awards, like the Grammys, would consider AI generated tracks if the proper permissions and copyrights, procedures are followed? 

[00:58:34] Maya: Well, you know, the truth is that we know that, um, a lot of signed artists are using our stuff, already.

[00:58:41] Maya: And we're never going to tell anybody. And the artists, for the most part, don't tell anybody. The great majority of our users don't inform anyone that they use our tools. Um, and I'm sure that's happening to other companies as well. And, you know, it sounds kind of naughty, you know? But it's really not, because in the end of the [00:59:00] day, it's just a tool.

[00:59:01] Maya: And I don't have to tell anybody that I'm using Logic Pro rather than Ableton. Right? Or even if I use Gorizon, I don't owe anybody that, that, um, information. And those companies are not forcing me to reveal it. So why should we, with AI suddenly, we're like, oh no, you must disclose if you're not hurting anybody, if you're not imitating anyone's style, if you're not doing anything illegal, why do you need to share what tools you use?

[00:59:27] Maya: And I think it implies that we're focusing on autonomous tools, tools that do all the work instead of you. But the tools that artists use, I mean, you mentioned the statistic about artists using AI, kind of more than half of artists already use AI. A lot of it isn't mastering, right? A lot of it is sort of the previous generation of AI, not generative AI.

[00:59:46] Maya: And nobody really had a, well, people had a problem with it, but not to the same extent as with generative AI. But it's all tools, and if we position the tools in a way that leaves the person in the driver's seat, if we do that, and I realize that's an if, and there [01:00:00] are companies that don't focus on that direction, but for those tools that do leave the user in the driver's seat, it just doesn't make sense to be so pedantic about, like, limiting what they can do with it, or eliminating them from competitions.

[01:00:14] Maya: Um, And I think in general, we just need to move past this whole click of a button. The AI is just going to do everything instead of you. Because at the end of the day, even if you look at what happened with MidJourney, which, again, love the product, I think. It's so cool. Um, but even they started adding more and more tools that let you then go in, highlight a section, kind of regenerate a portion of the image. So, uh, Adobe Firefly was really an innovator in making these text to image models more interactive.

[01:00:42] Maya: Uh, and then you saw MidJourney sort of built in. Again, so, so, so they are noticing that even for text to image people don't want click of a button. So the tools are gradually, I believe, they're going to become more and more interactive and this question of do you qualify for an award if you use them will become mute.

[01:00:59] Maya: Mm hmm, mm 


[01:00:59] The Role of Voice to Voice Technology in Music
---

[01:00:59] Sam: [01:01:00] hmm. Well, what about the voice to voice technology? Like, what if the song is so good and the artist allows you to use it and You are not the artist, but like, do you think, like, maybe these awards will let you one day participate? I think 

[01:01:20] Maya: you should. Of course. I mean, people go on stage singing someone else's words 

[01:01:24] Sam: all the time.

[01:01:25] Sam: Yeah. Yeah. So, 

[01:01:27] Maya: yeah, they don't write the lyrics and yet they get the award. So why can't I write the lyrics and do everything 

[01:01:32] Sam: and. No, I mean, with the voice to voice, like, 

[01:01:36] Maya: as long as it's with permission, right? Yeah. Let's say somebody makes a grime song. And they sang it, and they did all the lyrics, and they did all the music, and they produced it and mastered it.

[01:01:45] Maya: And they made an amazing song that was a hit, right? And it wasn't, but Grimes allowed it. 

[01:01:52] Sam: Why not? Why not? Grimes will also, like, get royalty from it, yeah. 

[01:01:58] Maya: I see no reason why, [01:02:00] like, we, you can get an award for a song where it wasn't your words, or it wasn't your music, but it was your voice. So you get an award for that.

[01:02:09] Maya: Why not the flip? You did everything except the voice. Why not? Maybe it could be a different category to start, right? To make people feel more at ease. But it's art. And as long as it doesn't hurt other artists, doesn't violate their copyright, it's not unethical, I think it's just art like any other 

[01:02:31] Sam: art.


[01:02:32] Building a User Base and Marketing Strategies
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[01:02:32] Sam: Yes, that's very insightful. And moving on to some advices if you can give on early founders. Um, so I. Would love to know, um, now you have 10, 000 users per day and you have millions of user overall. How did you amass, um, this user base? 

[01:02:56] Maya: Oh, sweat and blood. 

[01:02:57] Maya: Um, yeah, it was very, very difficult. So we [01:03:00] started, as I mentioned, with, uh, 10, 000 that we kind of initial, initially Facebook ads. This was before it was called meta. We used Facebook ads to begin with and then we added. Sort of other advertising platforms and early on some influencers actually made some content for us for free. They were so excited about the product.

[01:03:18] Maya: Um, we've worked incredibly hard. Uh, everything, everything we've accomplished was through hard work. There was no shortcuts, no

[01:03:32] Maya: Yeah, I don't know if I'm really giving a profound answer here. But it's, it was just, and also like we did another thing that I can share that we did with the product. Um A lot of very extensive iteration, especially with Lyric Studio in the beginning. So, we would pay attention to user behavior really, really closely, of course, in a kind of ethical, anonymized, aggregated way.

[01:03:52] Maya: And, um, we would be like, okay. We're seeing that the users maybe don't like this. Let's try this variation. And [01:04:00] very, very quickly introduce new features and see how people react to them. So with the goal of increasing conversion, increasing the amount of time people spend on the platform, as we sort of fine tune the product based on how users behave on the product.

[01:04:14] Maya: Mm hmm. 

[01:04:14] Sam: Mm hmm. What did you pay attention to, to know that, for example, user don't like this part of your platform? Oh, it can be like, 

[01:04:24] Maya: it can be anything. It can be like the sign up flow. Mm hmm. Or like something, some kind of wording makes people uncomfortable that we didn't realize. Um, And then we also do a lot of A B testing on the A I itself to kind of change something up, see if they respond better to it.

[01:04:54] Maya: So that was done very, very aggressively for the first few months until we started hitting the kind of conversion rates that we wanted to see. [01:05:00] So we have basically we have a hypothesis that. Fundamentally, these generators, melody generators, lyrics generators, can be very, very helpful in, uh, songwriters or a beginner's journey of learning songwriting.

[01:05:14] Maya: But exactly how to do it, the minute details of it that make an enormous difference, is something that we're flexible about. And so we kind of navigated that space of possibilities until we got the kind of results that we thought were quite good. Mm hmm. Mm 


[01:05:29] Communicating Technical Concepts to a Non-Tech Audience
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[01:05:29] Sam: hmm. And, um, In the early stages, um, you mentioned you couldn't really use AI in your promotional material because like people didn't even know what AI is.

[01:05:41] Sam: And, um, so how did you communicate effectively your company's offering to the market that is unfamiliar with your technology? And, um, what strategies do you recommend other founders of technical companies in conveying their values to a broader audience? 

[01:05:59] Maya: That's a great [01:06:00] question. So, um, Users don't care about AI.

[01:06:04] Maya: If anything, it's intimidating, it's scary, it feels replacive. And that's been the case before and to some degree, there remains some resistance right now. I think it's a little bit better. If there is no way to communicate the value of the product without using the word AI, then there is no value in the product.

[01:06:24] Maya: so, We have a lyric generator, something that helps you write lyrics, right? So you need to communicate the value to the end user. We have something that's going to help you write songs, help you write lyrics. You show it, you have to show it, if it's new, if they don't understand what it is. Get a video, show it to them.

[01:06:42] Maya: , and then people try it, and then they tell their friends. And that's where the quality of the product really, Um, really starts to shine. You can have the biggest, I mean, we see this, this with movies all the time, you can have the biggest marketing budget, but in the end of the day, people do have decision power.

[01:06:58] Maya: So, [01:07:00] um, yeah, you can, you can describe everything we do without using the word AI once. And I think, you know, sometimes founders are really, especially if you build the AI yourself, you're just so proud of it. You're so proud of what you created. But nobody cares. Nobody cares what you're proud of. It's not about, it's not about you.

[01:07:20] Maya: It's not about the founder. It's not about how brilliant they are and what an amazing AI they made. Nobody cares. Maybe nobody should care. What value are you giving to the end user? Why should they spend their valuable time and money on whatever it is you build? Explain it from their perspective. That's a 


[01:07:36] Navigating Challenges and Rejections as an Entrepreneur
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[01:07:36] Sam: good focus.

[01:07:38] Sam: That's, that's great. That's great. So Before I move on to our next subject, what are some of your experience that you think are going to be valuable for early founders to navigate their challenges and their within their entrepreneurial journey? [01:08:00] It's gonna 

[01:08:01] Maya: be hard. 

[01:08:02] Maya: Unless you're like, I don't know, exceedingly well connected so you can just keep failing up.

[01:08:09] Maya: Um, you know, there are companies that fail and somehow raise twice their previous round. That happens to the most well connected founders, pretty much. Um, but that doesn't apply to most people, and those people don't need my advice. Um,

[01:08:25] Maya: look, I mean, you're trying to change the world. You're trying to get somebody to care about what you and, you know, two, three, four, five other people came up with. Most likely you and two of your friends. Um. It's going to be hard. A lot of people are not going to believe in you. Um, a lot of stuff is going to go wrong all the time.

[01:08:48] Maya: All the time! You can predict what's going to happen in eight years with perfect accuracy and still have everything go wrong all the time. So, um, if [01:09:00] you are not ready for that level of pain and suffering and rejection, don't do it. There are other ways to live life. There are other ways to be happy. If for some reason you want to change the world, it's going to be hard.

[01:09:13] Maya: Uh, and if it was easy, everybody would be doing it and the world would be changing way too quickly all the time. 

[01:09:18] Sam: Exactly. Um, that reminds me of, um, something that Barbara, I think her last name is Korokon from Shark Tank, mentioned that If you're not going to be okay with rejection, do not be an entrepreneur.

[01:09:34] Sam: You have to embrace being rejected all the time. I started 

[01:09:39] Maya: doing this thing, um, in the last fundraise, you know, and I'm really, really fortunate at, you know, some of the stuff that's been happening to us right now. But the first few rejections that I got, I decided on purpose to be happy about it. I was like Yay!

[01:09:54] Maya: A rejection! Woohoo! Another rejection. Fantastic! That means I'm getting out [01:10:00] there. And I'm doing the work. Right? If I'm not getting enough rejections, that means that I'm Maybe I'm afraid. Maybe I'm hiding from the work. Maybe I'm not asking enough people for meetings. So celebrate those rejections to whatever capacity you can.

[01:10:17] Sam: Yeah, absolutely. I don't know. I think I read it somewhere today or yesterday. Done is better than perfect. Oh, 

[01:10:25] Maya: you're never going to have perfect. Oh my goodness, with entrepreneurship, you have to be good at so many things. You're not going to come in being good at all of them. Just forget about it. If you think you're great at like, Like, I came in as an AI expert, literally a professor in AI, and I thought that I knew what I needed to know.

[01:10:44] Maya: No, that's just not true. It's just not true. You have to, there was just so much to learn about the way the funding works, the way the business world works. And if you're sitting there waiting for you to be perfect, I mean, your company is going to be, it's going to fail [01:11:00] before you have a chance to do 

[01:11:02] Sam: anything.


[01:11:03] Gender Bias in Venture Capital Funding
---

[01:11:03] Sam: Absolutely. , moving on to our next topic. You conducted extensive research in gender bias in venture capital. And the results was shocking because it showcased that investors that claim that the number of exits and education are the most important in entrepreneurs.

[01:11:26] Sam: But according to your research, you found out that gender is more important. Sadly, if you can. Expand on that. 

[01:11:35] Maya: It's hard. It's hard. It hurts to talk about biases directed towards you. I think that it's a very, but it's half of humanity, right? Women are half of humanity. So if we can't talk about that bias, what bias can we talk about?

[01:11:48] Maya: Um, so, you know, I had my own experiences. I honestly thought it was gonna be really easy. I'm an AI professor. I see was perfect clarity where the field is going. I see what needs to be done. I could probably raise [01:12:00] a few million. I was so sure about it. I thought it would take a few months to raise money.

[01:12:05] Maya: And maybe it should have, but, uh, but it didn't. I had experiences, more than I'd like to admit, that were really disorienting. Um, where I just couldn't understand why these investors were not taking me seriously. In a way that I was really sort of not used to already at that phase in my life. And then, kind of by accident, with a couple of my students, three of my students, we ended up, they wanted to build some systems to help investors, and I'm like, oh, let's have a glance at whether we see any quick differences in investment patterns towards minorities or women compared to other groups.

[01:12:45] Maya: And the bias started oozing out of the data in a way I've never expected. So you know, common narrative is pipeline problem, not enough women are trying to get money. The total amount of women, percent of funding going to women is like 2 [01:13:00] percent versus 98 percent to men. Okay, maybe not enough women want to be founders.

[01:13:05] Maya: It's possible. It's a logical explanation for these, this kind of data. Well, you can ask another incredibly simple question and I don't understand how it's possible that no one asked it before me because it's really straightforward. What's the expected value? What do you, if I go to fundraise and a guy exactly like me goes to fundraise, how much are we going to raise?

[01:13:27] Maya: Right? And it's a massive gap. It's a massive gap, and it's pretty simple data analysis. And to be on the safe side, we also asked, okay, how does, like you pointed out, how does, uh, gender compare to the importance of business acumen measured by previous exits and level of education, and gender turned out, turned out to be a lot more important in that analysis.

[01:13:50] Maya: So that's the problem. The problem is that when a woman goes to raise, she either doesn't raise anything or raises much less than her male counterpart. And the problem It's not [01:14:00] diversity. Diverse teams don't have any problems raising money if they're led by a male CEO. The bias is against the female CEO, whether she has male co founders or not.

[01:14:11] Maya: It's worse if she doesn't, but still the strongest signals is just the gender of the CEO. So that's what we found. Um, and it was a really hard pill to swallow.

[01:14:21] Maya: Easier to live in an imaginary world where I was just having weird experiences than to recognize just how deep the bias runs. 

[01:14:32] Sam: That is, uh, very heartbreaking, but, you are successful. You've Um, overcome so many challenges and, for other female entrepreneurs that are listening right now. Um, these are like really saddening and, , how can we shift our focus and what can we do to persevere knowing these facts [01:15:00] and what can investors do to, Basically fight their bias. 

[01:15:06] Maya: Yeah, yeah, these are great questions, and I have some kind of responses there, but first, did I overcome the biases? I think I'm doing okay, despite being a woman, but this was before I joined the business world that I would do this exercise, and I'd be like, what if instead of Maya Ackerman, I would be Mark Ackerman?

[01:15:26] Maya: Identical in every other way. And I know in my heart that things would have been a lot easier. They would have been easier in academia, and they would have been much easier in business. Attributing intellectual brilliance to men comes, just comes more naturally to us. With a woman, we have to do extra cognitive work for some reason, to accept her accomplishments, to not diminish them, um, to recognize her potential in a way that we so easily grant to men.

[01:15:52] Maya: So, I think, um, it did not deter me, but I don't think that the outcome is identical, [01:16:00] you know. Um, what can investors do? The investors have the power here, right? So the investors are really the ones who can change it, and there's a lot of VCs that are, you know, really trying to make a difference.

[01:16:13] Maya: We need to become aware of our implicit biases. So, Carl Jung said that, if, uh, we don't acknowledge our shadow, it controls us. But also, you know, researchers out of universities, like Berkeley. Also showed that really, the less we're aware of our bias, the more biased we are, like by trying to claim that we have no bias, that's when we are the most biased.

[01:16:38] Maya: So there needs to be a lot of effort in the venture world for investors to learn about gender bias and to maybe put aside the guilt for a moment. It's not about blame. It's really about. Our world is sexist, right? And it manifests in a very specific way in the business world and to really learn about it, to, to recognize the [01:17:00] biases within themselves so that they, so they can overcome those biases and really fund the best founders to make better decisions.

[01:17:07] Maya: This is not a charity. Female founders are not a charity. I hate it when this kind of framing gets put on. In fact, there's a lot of research showing how they fail less often, they succeed more often. There's a lot of, A lot of really strong results showing how incredibly well female entrepreneurs perform.

[01:17:25] Maya: So this work needs to happen on the investor side. We're actually doing some work with Santa Clara University and Chevron on training programs for investors. And so much of it is just about reducing that resistance, that fear of being called bias, kind of the negativity that comes with the fear that maybe you're doing something wrong and just recognize that everyone has implicit bias.

[01:17:47] Maya: We all carry it. And. We should learn to recognize it within ourselves so we can do better. On the entrepreneur side, that's when all I can share is kind of my own thoughts of what I've been doing, rather than [01:18:00] research founded solutions. What helps me is to realize that while I was not ideally positioned from this perspective, had I been Mark Ackerman, I'm certain things would have been easier, but somehow, despite being born in Soviet U.

[01:18:17] Maya: S. S. R., you know, in communist times. Um, as a girl whose parents couldn't afford to buy her an instrument, that I still somehow managed to be in a position to meet with investors and, you know, have the incredible fortune of how to recognize opportunities around generative AI eight years before everyone else became aware of them.

[01:18:42] Maya: Good things came my way as well that offer an advantage. So it's not just one big disadvantage. It's a complicated array of factors and I have so much to be grateful for. Um, and there's a lot of people in this world who don't have the opportunity to, to [01:19:00] pitch to Silicon Valley investors. So that helps me, sort of, helps me keep doing what I'm doing.

[01:19:06] Maya: Yeah, 

[01:19:07] Sam: thank you so much for opening up about this and Sharing, , your story, um, as you said, like, it's Like, we should never think of like funding woman as let's pity woman and just to , say, , I'm not biased, I'm gonna like, just fund this woman, , but I don't really believe in her.

[01:19:24] Sam: No, actually, when there is like, two people, and there is a more qualified woman, and then there is a less qualified man, and you're just , funding funding. the man because of , the gender, you're hurting the society, you're hurting the economy, you're, so that's why that that makes me really upset as well.


[01:19:47] Maya's Advice for Aspiring Entrepreneurs
---

[01:19:47] Sam: Um, but Maya, thank you so much. I have, , last two questions and, , it's, it's been really a pleasure. So, uh, my last two question is, um, [01:20:00] What advice would you give to early and aspiring entrepreneurs that you would think is, would have the most benefit in their entrepreneurial journey? 

[01:20:14] Maya: Humility and persistence, I think, are the most important things. So humility to recognize that no, you don't know everything. And yes, you have a lot to learn. You need to be discerning about what advice you take, because you'll get a lot of conflicting advice. And nobody knows your business as well as you do.

[01:20:31] Maya: But you almost certainly You need to learn a lot, and you need to bring on team members who are experts at things that you're not very strong at. Um, yeah, arrogance blinds us to our own weaknesses and hinders our own success. So definitely, humility is really, really important. And the other one, mostly reinforcing what I've already said many times today, is determination.

[01:20:53] Maya: Uh, Building that muscle of being okay with rejection, being actually gracious about it, [01:21:00] and maintaining those relationships with people who have rejected you. You have a choice, like very often, uh, people who have rejected you in the past will invest in you in the future. So, respect their right to say no, be gracious about it, but don't, you know, don't stay on the ground.

[01:21:17] Maya: Get up, again. Um, it's okay to feel bad, you know, if you're trying to change the world, it's not gonna all feel good. Some moments are going to feel really, really terrible, and it's the people who are willing to suffer, who are willing to take the bad with the good, who, you know, are left standing when the real opportunities arise.


[01:21:38] WaveAI and its full Potential
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[01:21:38] Sam: Yeah, absolutely. Thanks for all the great advices. And the last question is, I'd like to ask you to envision a future where wave AI has realized its full potential. What positive changes do you see happening in the world as a result of your work?[01:22:00] If it, 

[01:22:02] Maya: if it goes the way I want it to go, it'll really be about profoundly elevating human creativity across a wide array of domains, starting with music and about, um, With much more creative people, if you could make everybody ten times, a hundred times more creative than they are now.

[01:22:25] Maya: Not only do we have a lot more incredible art and music, but we also become capable of tackling Some of the most difficult challenges facing humanity, because creativity is at the root of problem solving. So I think I really view this as a phase in human evolution. Generative AI applied right, applied to where the ripest opportunity is, and not superimposing old ideals of the servant machine, onto AI.

[01:22:50] Maya: Um, but instead leaning into its incredible creative potential in a way that interacts with a human and doesn't replace the human, [01:23:00] we can really have a whole new phase in humanity's timeline. 

[01:23:07] Sam: Yes. Yes. And I love that. I hope there are more leaders like you that's, take this technology, in a way that will benefit all humanity.

[01:23:20] Sam: So thank you so much, Maya. This was such an insightful conversation. Really just amazing stories and background. And I feel like I just became smarter just having this conversation with 

[01:23:32] Maya: you. so much for having me. It was such a joy. 

[01:23:35] Sam: Thank you, Maya. Thank you.


[01:23:38] Concluding Remarks and Final Thoughts
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[01:23:38] If you'd like to turn your personal trials into your strength. Perhaps into a thriving business, just like Maya did. Make sure to subscribe because at the entrepreneurs road, there is a village of successful founders, investors and experts all here. Eager to [01:24:00] share their secrets and support you on your journey, into becoming who you're meant to be. Don't forget to follow us on Instagram, TikTok LinkedIn, for more insights updates, and behind the scenes even. Join our Vibrant community across these platforms and be part of the conversation that is shaping the future of entrepreneurship.