Bobby Owsinski: That's what we're waiting for in AI, we're waiting for someone that takes this stuff and does it way outside the box and takes us all to a new level. It's helping us learn. It's helping us get good at what we do. Now, do you have what it takes to take it to that other level?

Michael Walker: It's easy to get lost in today's music industry with constantly changing technology and where anyone with a computer can release their own music. I'm going to share with you why this is the best time to be an independent musician and it's only getting better. If you have high-quality music, but you just don't know the best way to promote yourself so that you can reach the right people and generate a sustainable income with your music, we're going to show you the best strategies that we're using right now to reach millions of new listeners every month without spending 10 hours a day on social media. We're creating a revolution in today's music industry and this is your invitation to join me. I'm your host, Michael Walker.

Michael Walker: All right, so I'm excited to be here today with Bobby Owsinski. So Bobby is a bestselling author in the music industry, has 24 books ranging from the Mixing Engineer's Handbook, social media promotion for musicians, and the music business advice book. He's appeared on CNN and ABC News as a music branding audio expert.

Recently he produced and mixed an album that hit number two on Billboard Blues Chart and he also has a podcast that's in its ninth year with over 400 episodes focused on the music industry. And we were talking a little bit backstage. We're really excited, geekin' out a little bit because we're gonna talk a little bit more about AI and specifically as it relates to music production, which is a thing that bobby knows a thing or two about. Bobby, thanks so much for taking the time to come on here today. 

Bobby Owsinski: Thanks for having me, Michael. Glad to be here. 

Michael Walker: Awesome. Maybe to start things out, we could talk a little bit about your background in the industry and how you found your yourself to this point and discovered what we're gonna talk about during this conversation with the AI production tools.

Bobby Owsinski: Briefly, I started out like most people in the industry as a player, I was guitar player for a long time on the road, in the studio, then transitioned to just the studio as a producer, mixer, engineer, and then fell into writing about it. And first it was for magazines, dozen or so, and then it started with books.

Mixing Engineer's Handbook being the first one, and then it went on from there. Now, today I'm also producing online courses and started first with linda.com, LinkedIn Learning, and then branched out to do them on my own. With that being said, you have to, at least I have to stay on top of whatever is the latest new development, especially technological in business.

Part of this is because my books are used in colleges all over the world. It's demanded that I revise them every two, three years or so. Which means that I really have to look and see what is the latest in the industry, what are people doing? And I try to keep up anyway cuz I'm really interested.

But that goes in my books and that kind of leads us to ai. One of the reasons why I get into it was, yes, it's brand new. How do you use it for music production? And then I found that I was very attracted to the technology for some reason. I just found it really interesting and got deeper and deeper into it from a tech standpoint and also from a user standpoint.

So that's what brings us to today. Now I'm developing a course and a book on AI for music production. 

Michael Walker: Cool. Yeah, I can't wait to read that book. And certainly. Gosh, like the keeping up with all of the new developments that keep happening and especially as it relates to ai, it seems where the exponential curve is starting to really ramp up.

But I would love to hear from your perspective, cuz I have so much respect for how long you've been doing this for and for how many shifts you've seen the music industry go through, and so you've seen big, revolutions that happen with the internet and, with different things related to music production with, daws and digital workstations.

And so I'm curious when it comes to AI and music production what's your mindset around it as an opportunity for musicians and what do you see as being the thing right now that might hold people back from really going all in and learning the tools? 

Bobby Owsinski: What holds people back is the perception that they won't be able to be creative with it.

And everybody thinks, oh, this is going to do everything for me, and it can, but it gives you a mediocre result. It really needs the human touch. It was just described by Jeff Walker our friend, our mutual friend. Recently in a seminar he gave that it will take you from a blank page if you're in a college course from an F to a C, and it needs you to go from a C to an A.

And I think that's the thing that you, that has to be impressed upon everybody, that this is only a tool. It only gets you so far, and then it's up to you to go to the rest of the way. 

Michael Walker: Absolutely. Yeah. It's seeing it as a way to amplify your creativity or buy back your time. And, if you, it's like if you're gonna, if you have a goal to do something, and let's say we're using an analogy of cutting down a tree, then you could cut down the tree with a hacksaw or with a hand saw.

Or, if you had a chainsaw that was like, you could do it in significantly less time. It doesn't necessarily mean the chainsaw, is gonna do it itself. In fact, it's really important that it has like an operator or someone that kind of knows what they're doing with it. But that, that's really helpful to, to hear and kinda reiterate that point that you're bringing up is that this doesn't necessarily replace you, it's actually, it amplifies your ability to do what you do best. 

Bobby Owsinski: The other thing it does, it makes you more efficient and makes everything go faster. And frankly, as someone who teaches people how to mix and get better at mixing, I'm always for anything that will make that process go faster because it can be boring.

Back in the day, it was not uncommon to spend days and days on a mix. And it would be really expensive cuz you're doing it in a big studio and now still that can happen, but it's less expensive cuz you're doing it in your home studio. But you don't want to spend that much time. Really it, the more time you spend, the more chance you have of going down a rabbit hole and not really progressing.

Just making things different instead of better. So I'm for anything that could cut to the chase and make things good as soon as possible. And then just some tweaks and we're done. And AI, I think is getting us in that ballpark, it's not quite there yet, but it's getting us there. 

Michael Walker: Very cool.

So as it relates to AI with music production, I'm curious to hear about some of the tools that are available right now from like a landscape point of view. What are some of the big movements or some of the big opportunities that are happening right now with AI and music production? 

Bobby Owsinski: There's more happening on the production and the composition area than there is on in the mixing area.

There's some very good tools that have actually been around for a while, and that's most of the things by isotope, ozone and Neutron, for instance. Neo Verb is another one, and they've been out for a while. The thing about it is most people don't use the AI feature in it. I think it's because they're, they don't really understand what it is, but that's what makes everything go and go fast and make that those particular plugins really work well.

But that being said they've been around for a while now. There's a whole list and we're just talking about, let's say mixing, mastering. There's a whole list of other ai tools, AI plugins and whatever, and you look at 'em and you go, okay, where's the ai? You say It's there. It doesn't allow me to interact in a way that AI usually does.

It has me scratching my head on a lot of these, but there are some, Sonible makes some really good stuff. It's again, it EQ, compressor a reverb. They work incredibly well. Now, if we switch over to the production side, there's a number of tools that can help you. Now that being said, sometimes the results are pitiful.

It's a type of thing that if you're not a musician, you go, wow, this is great. If you're a musician, you go, why? So I look at most of those tools as - this is a good way for me to get some ideas. I'm stuck. I need some ideas. Hit me and that's the level that we're seeing now.

When you talk about copying, okay, make me a song. It sounds like Drake. It's really good. It's good to a point. You listen to it and you go. That sounds a lot like Drake or Paul McCartney. There was just some good Beatles ones that came out and it's it sounds good, but you know what?

The fidelity is not that great. So that kind of defeats the purpose. And there's some glitches and so people are wowed with the technology, but when you really dig into it, you go, it's not what people are hyping it to be in a lot of ways. And yes, that, and don't get me wrong, I'm sounding negative about AI and I'm not at all.

I'm just saying you have to understand where it sits in the grand scheme of things. 

Michael Walker: That totally makes sense. So it sounds like what you're saying is that The way to be successful using AI right now and using it for music production isn't looking for a magic pill or magic button. You just press the button and it's it's all done.

But instead using it as a way to as a tool, to amplify what you're already doing. And right now the people who are gonna be the most successful with it, or the people who are bringing their expertise and bringing their wisdom and bringing the human element of it and not just letting it do everything.

Cuz right now, It isn't at a point where it's good enough to just do everything on its own. It's like you, you mentioned it brings it up to, from an F to a C, for example, on its own. Really interesting. 

Bobby Owsinski: It goes beyond that because there's some ethical considerations here. And already we're finding, for instance, the platforms like TuneCore will not accept a 100% AI generated song.

You've already decided that. And we're seeing that AI generated songs that don't contain any element of a human, they're being pulled down off of Spotify and off of all the streaming services. Recently, there was also a ruling by the US Copyright Office. Now it's guidance cuz it's not a law yet, but it's basically saying, unless a human is involved, it's not copyrightable.

So if it's not copyrightable, you can't make money from it. So you look at and you go, okay, I wanna make money for my music and I better do something with this in order to facilitate that. 

Michael Walker: Wow, that's so interesting. So basically there needs to be a human touch, and I feel like it's kind of shades of grays. It was like I I put I touched it. Like I put my pinky on it. It was like, okay, now it's copyrightable. But it sounds based on what you just said, that someone, a programmer couldn't just say, I'm gonna integrate with AI and I'm gonna have it generate these songs for me.

But they couldn't legally copyright that even though they had written the code to create those songs right now, unless they actually Do something with it human wise. 

Bobby Owsinski: There's the gray area that hasn't been figured out. Who owns the copyright? Is it the programmer? Is it the platform that it was done on?

Is it the training material that was used? And already we're seeing some movement that way. Is it the user who, who prompted it? Or any combination of those. And that hasn't been worked out yet. It, we're starting to see court cases that are going to set precedents on it, and they're happening now.

There's a bunch of really big ones. But that being said, it's still, big gray area. 

Michael Walker: Yeah. It's a, it's so fascinating. When you break down how we as humans, write music and how we learn, obviously we have influences and we have little pieces of characteristics and DNA that come from things and it'd be really interesting if there, there was a way to analyze myself and be like, Michael Walker and Modern Musician is 0.79% Jeff Walker product launch Formula. And be able to kinda see our influences cuz it's very true that there, there's a lot, we stand on the shoulder of giants and we have our mentors. And our mentors like, There's a certain like DNA of sorts that kind of propagates from our influences, but it's not quite as clear cut cuz we don't fully understand how our brains work. In some ways I think that that drive those, whereas with computers it's like very realistic you say. Yeah. This was training data of this thing. So yeah, I wonder if there's a, and then there's also this like emergent property that's happening where in some cases it seems like the AI tool is actually linking the dots in ways that transcend just pulling directly from this training data in a similar way that our brains have this emergent property and we can create a new property from underlying data.

So it's a super interesting one. 

Bobby Owsinski: Yeah, that's the neural network actually. And the hierarchy is we have AI and a subdivision of that is machine learning. And then a subdivision of that is neural networks. And then a subdivision of that is deep learning. And deep learning is basically how many layers in the neural network do you have.

But the neural network, what it does and most AI now has a neural network involved. What it does, if it's a word for instance, it predicts what the next one should be. So for lyrics, for instance, it's already looked at, maybe a million or a couple million songs in the lyrics of songs.

So it thinks that, okay, you just wrote these two words, so then the next one should be this one, and then after that there should be another one. Now that being said, you can always say I don't like that. Do it again and we'll come up with a different. Version the next time and the next time. After that, and the next time but it will all be logical because it's predicting it. 

Michael Walker: So interesting. Yeah. As it relates to that topic with the predictive nature of like Chat GPT and how it comes up. One thing that I think is interesting cause how do our brains function? There're essentially like, Predictive models to a certain extent, like this conversation that we're having the exact words that I'm saying, I'm not like reading from a script or like I know the entire sentence before I say it.

In fact, it's like very much so one word at a time, it's these thoughts are being strung together in a way that's coherent and it's coherent because you, afterwards you can look back like, yeah, he spoke a sentence, but in the middle of it, there is a lot of predictive intelligence that's just predicting the next word in my sentence.

Even though I didn't, I wasn't thinking that far ahead. Like you have to think what the sentence, how is the sentence gonna end? So that's also interesting to play into account. 

Bobby Owsinski: But see there's more to it than that because you're just focusing on the one sense, but there's all the other senses that are going on.

You're hearing yourself. And that's influencing everything you're seeing maybe something on paper, you're seeing me you're seeing influences around the room, you're touching something, you're feeling that, and all those are all different pathways that are influencing you.

Now, that's the whole thing that people don't understand about ai. AI is really good at getting a lot of that, but it's not good at all at getting all of it. So when people get scared about AI taking over the world and becoming cognizant and everything it has to get to that point where it's predicting all of our senses and it's not there yet, not even close.

So it can get to one sense and even that is multiple layers. 

Michael Walker: Yeah. It's so interesting. It's interesting I've seen from a from the perspective of robotics, how there's certain things that we can do as humans that you wouldn't think are that hard or complex to do. Like a baby can, reach out and grab a cheerio and eat a cheerio, but, There's certain things like that, that are incredibly complex or require an intense amount of intelligence for computers to be able to do, and for a robot to reach out and grab a cheerio and and grab it it's possible now if they have a very fine tuned model, but it's way more complicated than you would think to do things. So I, to your point I think it's there, there's so much wisdom in that, that There's so much that we do in this intelligence that comprises our bodies and our minds and our brains and on at the same time, there's certain aspects of digital intelligence that for obviously like ways surpass our human intelligence for certain things like doing math. There's no way I'm gonna beat a computer at doing an intense calculation. So it is gonna be like where do those things converge? Where can we bring in those human elements that are so intelligent but the computers can't do, and then vice versa and merging them into maybe one tool.

Bobby Owsinski: I just read something the other day about that and basically it was computers like to fail. AI likes to fail because it learns from it. Where for us, we get frustrated. We do something. Let's say it's a math problem and it doesn't work. We do it a second time, third time, and then we go, ah, I don't think I'm gonna get this.

A computer will do it a hundred times until it gets it and it will learn all the way, and then it won't, I shouldn't say computer ai, a neural network will figure it out eventually. And it doesn't like it dislike it, it just does it. For us, we have the, the element of, oh, I'm bored, or, I have self-doubt about this.

I'm not good enough. Or, those things, AI doesn't have it. 

Michael Walker: That's really true. Yeah. Yes. Coming back to this topic of music production and ai. I'm curious what you found are some of the other like tools or interesting movements that are happening right now. You mentioned that right now some of the mixing and the mastering, like there's plugins and what would be really helpful too.

Yeah, I think that maybe you've comprised like a list of some of these tools and kind of resources as it relates to different plugins that use AI and whatnot. So we can talk a little bit more about that later, because its super valuable. But I'd be curious right now what you've seen happening in terms of some of the tools that if someone right now is, listening to this or watching this and they're producer and they're like, You know what?

I've been sitting on the fence for long enough. I wanna dive into this AI thing. I wanna kinda learn how I can use it as a musician and as a creator a producer of my music, how would you recommend that they get started with that? 

Bobby Owsinski: Easiest way and you can prompt yourself from, and I'm just gonna stay in, in the area that I know really well and that's mixing and mastering whatever.

Mastering is fairly easy because there are great AI tools available that have been around for a while. Lander, for instance cloud Bounce is another one. Emastered. They're all AI based. And Lander was the first one. Lander, for instance, when it first started, it got a really bad rap. Oh, it's not good as whatever.

But after millions of tracks, it's learned and it's really good now. So that's a really good place to start. I want to get my song mastered. Let's do it. And you can do it yourself, but the real problem is you probably can't. Everybody thinks they can. I have this tool, but when I get mastering engineers on my podcast, I ask every single one of them, how long did it take you before you got good?

And the average is about five years of doing it every single day. So if you think you're gonna sit down and master something in your room, You just learn this tool, it's probably not going to be better. Chances are it's gonna be worse. So the easiest way is just go to one of those services and use it and you can tweak them.

So it's ai, but it gives you a lot of tweak ability. Another possibility is there's some really good tools out there. Isotope tools are fantastic. Sonible makes really good ones and they actually have a line, the pure line, it's pure limit, pure comp, and those are fairly inexpensive and very easy to use.

That will give you great results really fast. So those are a couple of places that you can jump right in and it can get you going. But remember that the real secret here is it's just like all ai, it's only as good as what you ask it to do. So if you give it an incomplete prompt and Chat GPT, for instance or bing ai, you give it an incomplete prompt or something that doesn't have enough detail, then you're not going to get the answer back that you want you have to give it enough detail of if exactly what you want.

So with these audio AI tools, it's much the same thing. It has to learn what it has first, here's your song, learn this, and it takes eight seconds and then it figures it out, and then it gives you all the suggestions of what should happen. But that's where people go wrong. They don't use that tool and, or they just use a universal tool.

Oh, this is a rock song. This is an e d m song. And they use that general tool so they get something that doesn't exactly fit for them. So again, it's always good as the information that you're giving it. 

Michael Walker: Really great point. Yeah. So it sounds like what you're saying is that. Like anything in life really, like the art of asking the right question is a superpower, particularly when it comes to prompt based, AI tools, because if you give, if you ask a general question, you're probably gonna get a general answer.

But if you ask a very specific question, you ask a good question, then you're going to get an actual response. It is interesting how that also relates to just non-AI world and just like our human intelligence and, learning how to ask the right question is such a superpower.

Bobby Owsinski: There's something that you can do, if you're using it for marketing, for instance and the end of a prompt you can either put, do you understand? Just to make sure that it does and you're not getting a hallucination. Hallucination is a kind of a off the wall response, or you can say, be very concrete and tangible with your answer.

And sometimes just that alone will take a lot of the fluff out of the answer and give you just that. 

Michael Walker: Super smart. Yeah. So add that little tip. Yeah. And this is such an important, I think point that we're talking about right now around prompt engineering, but basically like the idea of those little tips and tricks, like learning how to interact with it.

So it sounds like one of those little shortcuts is saying specifically make this as concrete and tangible as possible. And a lot of times that's going to, make something more concrete and tangible, which can be very helpful for using it. 

Bobby Owsinski: Another way to do it is to start off and say, imagine I'm a six year old.

How would you explain this to me? It will clarify the answer in such a way that even if you find the subject to be very opaque, it will clarify it for you. It does work. The other thing is if you use Bing ai, the Bing AI is very good, and the reason why it's connected to the internet, so it's getting all the latest information, Chat GPT is not, so the training material is only up to the last year.

So you're not getting really up to date info. It might be plenty for what you need, but it might not either. But with Bing ai, what you're able to do is you can go in and you can say, give me a professional response. Give me a funny response. Give me a casual response, and it will write it out like that or write it very professionally, it will write it very casually, will more will do it in a funny way. So those are all variations as well, that are very interesting and very unique and usable. 

Michael Walker: Super cool. Yeah. This is also a good segue or good reminder for anyone who's here right now in street team, under the tab artist ai, you can come in and you can play around with this tool that's included for free in street team.

And it essentially is like a version of Chat GPT and being ai, and it's built on open ai. So it's built on the same foundation as those AI tools, but it's fine tuned for you as a musician. So you can be a little bit more tailored to what you're looking for.

So maybe this will be a fun kind of demo or something to play around with, like with the two of us. So like we were talking about prompt engineering, one thing that I found really helpful is if I don't know what the right prompt should be. Then sometimes I'll ask it to help me come up with a good prompt.

Bobby Owsinski: Yeah. 

Michael Walker: And then it'll it'll actually give you like some tips or it'll help you. I'll be like, ask me questions to help you write like I want you to write a bio for me, for my artist career. Can you ask me a list of questions so that you can create a bio and then I'll ask good questions and be like, okay, great.

What would be a good example that we could potentially use for. As it relates to music production, music mixing, or composition? 

Bobby Owsinski: I'll give you one that's more relatable to maybe your audience. Let's say that you're an artist that has some success and you want to come out with a line of merch.

What you're not sure exactly what to do, but what you could say is, I want to come out with this line of merch, but I'm not sure what it should comprise or what, how it should be comprised. Can you write a survey that I can send out to my customers, to my audience, to my followers that would ask them exactly what they're looking for when it comes to merch, and especially from me.

There we go. 

Michael Walker: Wow.

Bobby Owsinski: Now if you don't like those at the end I'm not sure if your implementation allows you to ask again. 

Michael Walker: Yep. It has contexts on it. So we can go back and forth, 

Bobby Owsinski: but I actually just did this. I used it yesterday. I asked it to come up with a survey for me for this particular course that's coming up, this AI course, just to find out what people know about ai, what they don't.

These are my followers. These are on my list and what they're looking for, and just a little bit of demographic information. Now, I had to tweak it, but it was still pretty good and it was very usable. It was like, okay, I can use this. I won't use that. I can use this. And I got an excellent response, so it would've taken me hours to come up with these survey questions.

And anybody that's ever done a survey knows that there's a lot that goes into it. This is just an easy way of getting past it and again, getting information that you can use right away. 

Michael Walker: Super cool. That's a great example. I've never seen seen it used in this way to generate the survey questions to ask, but yeah.

This is super smart and asking people what they want is almost always the right first step to creating something that can provide them what they actually want. Awesome. And I wonder if we wanted to like, iterate on this. Let's say that we. I want my merchandise to involve ai themes.

Can you give me some ideas? This will be interesting. I'm not really not getting a whole lot.

Bobby Owsinski: Okay.

I think there's gonna be a copyright problem, some of these, but, 

yeah. 

Michael Walker: It is funny. One of the limitations it seems of this AI you mentioned it earlier, is around fabrication or hallucination. Yeah. It's really funny. So one of the applications that, that we've built with the AI is in the form of an AI chatbot service that can have like really well articulated conversations with new fans.

And we had to build in a mechanism to fix this because it kept doing this thing where it would, every once in a while it would it would come up with a totally fictitious name for a song. You'll probably like my song like running in Iceland.

But it it wouldn't be running, it would be something that actually sounded like legit. It would be like, oh like that sounds like a song. And it sometimes even provide a link. It's here's the link. And people would click on it and be like, this link doesn't work. Also, I don't think that's a real song.

Yeah. But for me, I was like, man, like maybe I should write a song about that. That's, it was pretty, that's, but it's funny 

Bobby Owsinski: hallucination, as they would call it. 

Michael Walker: So interesting. 

Bobby Owsinski: Yeah. Yeah. This is cool stuff. It's, again, it's tool and you just have to learn how to use the tool. Just pro Tools or Logic or, any of those are tools.

You have to learn them.

Michael Walker: Absolutely. And I think the approach that you're recommending is so spot on in terms of there's always this tendency. At least it seems like there's this tendency whenever there's a new technology or something big that's pretty disruptive where there's a hype and excitement around it, and sometimes there's a bubble that can kinda like pop, but then there's also a lot of resistance generally to it and a lot of wanting to downplay it or saying it's not like that, it's not that smart because X, Y, Z. And then, like it, like you mentioned Lander is like, when it first came out, it's oh yeah, like it's cool, but it's, it can't really do anything.

And then it's wow, it got better. It got smart. But it definitely seems approaching it and acknowledging that there is a bit of a bias towards not wanting to use something new, being willing to kinda like swim along with the wave that's coming so you can catch the wave and get that momentum as it cress I think is really important.

Bobby Owsinski: Yeah. Again, like we said before, I think one of the big problems here is people read some of the hype and especially about taking over everybody's job as a writer and all those things, but really it's a tool. It's going to give you mediocre results and maybe even better than mediocre good results, but it's not going to give you great results.

Shelly Palmer, do you know who Shelly Palmer is? 

 He's a tech guy, is it? He's the tech guy on TV in the New York area, I think on ABC Channel seven. But he has a newsletter and he's always in the cutting edge and he's always on ai, on about AI has some good classes on it.

But he's also a musician. He made his living before he did that writing jingles. So he comes from our world. But he had a really interesting take on it, and his take was everybody steals from everybody else when you're learning, it's part of the learning process. So if you're learning how to play guitar, you're picking out 10 guitarists and you're learning their licks.

Eventually we get really good at it and the people that are just really good at it, they don't stand out above the crowd. They're just really good at copying this stuff. Every once in a while you have a genius that thinks outside the box and takes all this data and then just jumps to a different level.

And that's what we're waiting for in ai, we're waiting for someone that takes this stuff and does it out in a way outside the box and takes us all to a new level. But you can also think of, here's ai, it's helping us. It's helping us learn. It's helping us get good at what we do. Now, do you have what it takes to take it to that other level?

Michael Walker: Oh man. That's so good. Yeah. Actually you gave me goosebumps as you were talking there. What my mind went to was Steve Jobs and his famous speech around, think different. Yeah. Like the whole mantra of think different and that famous commercial, it's all about the icons and about, it's it's the square pegs and the round holes like, Those are the people who change the world because they, people think they're crazy and they think differently, they're the ones that create, disruption and change.

And certainly relevant to this conversation and what you're saying right now about, ai Yeah. It's a powerful tool and, you can use it to amplify, your message, but ultimately it's actually thinking differently, it's taking that and making it your own is really where true genius is born.

Bobby Owsinski: Yeah, that's right. You have to learn first. And how do you learn? You learn by copying your influencers. 

Michael Walker: It's true. Yeah. That's such an important lesson too to bring home, I think is because a lot of times as musicians or artists especially, we might feel like there's something wrong with being influenced or, modeling or referencing other musicians that you look up to and we feel like, no and I have to be 100% original and, there's nothing else. They can't describe, my sound in words, but yeah, just the willingness to learn from your influences and to model, but balancing that with what you just talked about with with bringing your own taste to it.

I've heard it described before, like you emulate and then you innovate. So at first you just find out what's working, what people spent tens of thousands of hours figuring out the current state, and then you take that and you innovate and you make it your own.

Bobby Owsinski: Yeah. Yeah. That's a good way to put it. 

Michael Walker: Yeah. I didn't come up with it. I'm emulating and I, now I need to innovate. What's the new way to say that AI quick. Come here. Help me say that in new ways. You know what's so funny too, if we came here, we were just like, and we asked it, can you create 10 different variations of this phrase?

Bobby Owsinski: Oh, that's good. Yeah. 

Michael Walker: Of the phrase emulate, then innovate.

Bobby Owsinski: I don't see anything there that jumps out at me, but pretty good. 

Michael Walker: Nothing on the level of emulate than innovate. That one's just so short and catchy. Yeah. Less than four words only. Copy, create, improve, adapt. I guess I didn't ask it to gimme 10 more.

I was just like, copy, create, improve, adapt. That's pretty good though. That's that's a pretty good little catchphrase. All right, cool. Totally original copy written thought I own the creation of this. 

Bobby Owsinski: You and open AI 

Michael Walker: yeah. Then back into the can of worms around ownership and royalties gotta figure that one out. Hey Bobby, dude, this is one of my favorite things to talk about, and like I mentioned I really appreciate the perspective that you bring to the conversation and thank you for taking the time to come on here live, to share, some of the insights and lessons you've learned and the current state of AI as it relates to music and production.

Bobby Owsinski: Thanks for having me, Michael.