# Inside the Rise of AI Music: How Imogen Heap Is Shaping the Future | Billboard On The Record

https://www.youtube.com/watch?v=d9BnKZnh65k
Translation: zh-CN

[00:00] When AI becomes the next pop-star, who gets the spotlight?
  当AI成为下一个流行明星时，谁会成为焦点？

[00:02] The artist or the algorithm?
  是艺术家还是算法？

[00:04] You might have caught recent headlines about so-called AI artists or artists that heavily rely on AI tools like image, voice, or music models to make their songs.
  你可能已经看到了最近的新闻头条，关于所谓的AI艺术家或严重依赖AI工具（如图像、语音或音乐模型）来制作歌曲的艺术家。

[00:14] There's one artist, Zania Monet for example, who recently signed a record deal and is climbing the gospel charts and is playing on radio stations across the country.
  有一位艺术家，例如Zania Monet，最近签下了一份唱片合约，正在福音音乐排行榜上攀升，并在全国各地的广播电台播放。

[00:21] Meanwhile, last week a bunch of songs in the top 10 on the country sales chart were also songs that stem from this kind of AI artist.
  与此同时，上周乡村音乐销售排行榜前十名中的许多歌曲也源自这种AI艺术家。

[00:27] At a time when AI generated songs seem to be exploding, cropping up everywhere from TikTok trends to Billboard charts, it felt like the perfect time to dive into how this will impact artists and what can be done to protect human creativity in the process.
  在AI生成的歌曲似乎正在爆发、从TikTok趋势到公告牌排行榜无处不在的时候，这似乎是深入探讨这将如何影响艺术家以及在此过程中如何保护人类创造力的最佳时机。

[00:45] And I couldn't dream of a better guest to join me here today to discuss this topic than Imogen Heap.
  我想不出比Imogen Heap更适合今天和我一起讨论这个话题的嘉宾了。

[00:51] [music]
  [音乐]

[00:55] Welcome back to On the Record, a music business podcast from Billboard and Sixpoint Productions.
  欢迎回到《On the Record》，这是来自公告牌和Sixpoint Productions的音乐商业播客。

[00:59] As always, I'm
  一如既往，我是

[01:01] Your host Kristen Robinson and I'm thrilled to have Imogen Heap on the show today to talk about the rise of generative AI and how it will impact artists.
  我是主持人克里斯汀·罗宾逊，今天非常激动地邀请到伊莫金·希普来到节目，讨论生成式人工智能的兴起及其对艺术家的影响。

[01:10] Imogen is a multi-Grammy winning singer, songwriter, producer, engineer, and technologist who has been making music for over two decades now and it's clear that she still is somehow a few steps ahead of the rest of us.
  伊莫金是一位多次获得格莱美奖的歌手、词曲作者、制作人、工程师和技术专家，从事音乐创作已超过二十年，显然她仍然在某种程度上领先于我们其他人。

[01:21] We will unpack this growing AI phenomenon and what these tools mean for the future of creativity.
  我们将剖析这一日益增长的人工智能现象，以及这些工具对创造力未来的意义。

[01:27] As Imogen herself recently put it, the genie can't go back in the bottle.
  正如伊莫金本人最近所说，精灵无法再回到瓶子里。

[01:31] And after years of research and development, she's finding ways to use AI ethically within her own artistic practice.
  经过多年的研发，她正在寻找在自己的艺术实践中合乎道德地使用人工智能的方法。

[01:39] There are really few artists that understand the intersection of music and technology quite like Imogen.
  很少有艺术家能像伊莫金那样深刻理解音乐与技术的交汇点。

[01:42] Her latest singles, I Am and Afterlife for example, both use her regular singing voice and this AI voice model which is trained on hundreds of hours of her own singing which she calls AI-mogen.
  例如，她的最新单曲《I Am》和《Afterlife》都使用了她的常规歌声和这个人工智能语音模型，该模型基于她数百小时的演唱训练而成，她称之为AI-mogen。

[01:55] She's also been hard at work developing Oracles, a system designed to help artists manage their IP in an age of AI where deepfakes and training
  她还一直致力于开发Oracles系统，该系统旨在帮助艺术家在人工智能时代管理他们的知识产权，在这个时代，深度伪造和训练

[02:02] Models on music without permission is very commonplace.
  未经许可在音乐上使用模型是非常普遍的现象。

[02:05] We'll also touch on the 20th anniversary of Imogen's influential album Speak for Yourself, which she released at another time of great change in the music biz.
  我们还将提及Imogen具有影响力的专辑《Speak for Yourself》发行20周年，这张专辑是在音乐行业另一个巨变时期发布的。

[02:14] Back then, CD sales were down, MP3s were taking over, and almost no one was having an easy go of it.
  那时，CD销量下滑，MP3正在占据主导地位，几乎没有人能轻松应对。

[02:21] But still, Imogen managed to release the project independently and to great success.
  尽管如此，Imogen还是设法独立发布了这个项目，并取得了巨大成功。

[02:25] Today, the album is considered a modern pop classic and ever since she's gone on to serve as an inspiration for music's biggest stars, including Taylor Swift, Ariana Grande, Olivia Rodrigo, PinkPantheress, and yes, even Jason Derulo, in the years since Speak for Yourself's release.
  如今，这张专辑被视为现代流行经典，自《Speak for Yourself》发行以来，她一直激励着音乐界最耀眼的明星，包括Taylor Swift、Ariana Grande、Olivia Rodrigo、PinkPantheress，是的，甚至还有Jason Derulo。

[02:43] All this to say, I am very, very excited for our conversation today.
  总而言之，我对今天的对话感到非常非常兴奋。

[02:48] So, let's go ahead and bring her in.
  那么，让我们把她请进来吧。

[02:50] Imogen Heap, thank you so much for coming to On the Record.
  Imogen Heap，非常感谢你来到《On the Record》。

[02:52] I'm so happy that you're here virtually from London.
  我很高兴你从伦敦远程来到这里。

[02:54] Thank you.
  谢谢。

[02:56] Very happy to be here.
  很高兴来到这里。

[02:56] Where did you just fly in from?
  你刚从哪儿飞过来？

[02:58] You were just on a plane like 2 hours ago.
  你大约两小时前还在飞机上。

[02:59] I was uh coming from Lisbon, a lovely
  我呃从里斯本过来，一个可爱的

[03:02] It was actually torrential rain.
  实际上那是倾盆大雨。

[03:04] I didn't know if I was going to get back here cuz the thunder and lightning last night was so incredible.
  我不知道我能不能回到这里，因为昨晚的雷电太惊人了。

[03:08] I thought that there was somebody like going over my hotel room with a massive car or a big train or something, but it just turned out to be thunder.
  我以为有人像开着大车或大火车经过我的酒店房间，但结果只是雷声。

[03:16] Um so yeah, we might have but we were stuck on the runway forever which is why I'm late.
  嗯，所以是的，我们可能本来可以，但我们在跑道上被困了很久，这就是我迟到的原因。

[03:19] There's nothing worse than trying to get back quickly from the airport, so I really appreciate you still being able to make it.
  没有什么比试图从机场快速赶回来更糟糕的了，所以我真的很感激你还能赶来。

[03:28] Um I'm really excited to chat because I think that you are one of the artists that really just has been keeping your finger on the pulse of what's going on in the world of like cutting-edge technology, generative AI, all that stuff.
  嗯，我真的很兴奋能聊天，因为我认为你是那些一直紧跟前沿技术、生成式AI等世界动态的艺术家之一。

[03:41] And so that's one of the things that I report on at Billboard.
  所以这是我在Billboard报道的事情之一。

[03:42] It's become a huge focus for me over time.
  随着时间的推移，这成了我的一大关注点。

[03:47] So, but before we get into that kind of a chat, um I wanted to kind of throw it back to the beginning of your career when you're getting started.
  所以，但在我们开始那种聊天之前，嗯，我想把话题拉回到你职业生涯的起点，当你刚开始的时候。

[03:54] What were some of the technological tools in your studio back in the day that really inspired you?
  当年你工作室里有哪些技术工具真正激励了你？

[04:00] Well, I didn't have a studio in the beginning cuz it was very expensive to have a studio.
  嗯，我一开始没有工作室，因为拥有一个工作室非常昂贵。

[04:06] I did have a keyboard.
  我确实有一个键盘。

[04:07] I had an Ensoniq TS-12 which I still love.
  我有一个Ensoniq TS-12，我至今仍然喜爱它。

[04:10] Um, and I did have access to computers.
  嗯，而且我确实能接触到电脑。

[04:14] So, when I was 12, I started learning on an old Atari and they had some software on there at school that nobody knew how to use and it was in like this cupboard.
  所以，当我12岁时，我开始在一台旧的Atari上学习，学校那台电脑上有一些没人知道怎么用的软件，它就在一个类似橱柜的地方。

[04:26] It was like it's basically like the naughty cupboard.
  那基本上就像是个“淘气柜”。

[04:28] Um, but I realized later in life that my head the music teacher was just kind of being nice to me.
  嗯，但后来我意识到，我的音乐老师主管其实只是对我好。

[04:34] He was going, "Just get in that cupboard."
  他说：“就进那个柜子里去。”

[04:35] But he knew that I just wanted to like make music on the computer.
  但他知道我只是想在电脑上做音乐。

[04:39] So, that's when I started realizing that, "Oh wow, there's something in this computer thing that's like helping me be more than I can with just writing it down on a bit of paper and hoping that an orchestra might play it one day which they never would."
  所以，那时我开始意识到：“哦哇，这个电脑玩意儿里有些东西，能帮助我超越仅仅写在纸上、希望有一天会有管弦乐队演奏——而它们永远不会演奏——的局限。”

[04:50] Um, well, they did eventually.
  嗯，好吧，它们最终确实演奏了。

[04:53] Haha.
  哈哈。

[04:53] Um, so yeah, it was like computers and then when I was 15, I went to the Brit School.
  嗯，所以是的，就是电脑，然后当我15岁时，我去了英国学校。

[04:58] I was a second year in it's like this school in the UK which lots of musicians go to because it's the only one of the only schools like it.
  我那时是二年级，这所学校在英国，很多音乐家都去那里，因为它是唯一一所这样的学校。

[05:04] Um, and that's when I learned to use Cubase.
  嗯，那是我学会使用Cubase的时候。

[05:06] Um so I did know my way around studio, but I didn't have that much equipment.
  嗯，所以我确实对录音室很熟悉，但我没有那么多设备。

[05:09] I had a QY70 uh but that was a bit later.
  我有一台QY70，嗯，但那是稍晚一些的时候。

[05:12] That was like when I was 21.
  那大概是我21岁的时候。

[05:13] So, I could make little beats on that.
  所以，我可以用它做点小节奏。

[05:15] Do you think that like technology has always inspired you to start writing or what do you think usually kickstarts the songwriting process for you?
  你觉得技术是否一直激励你开始创作，或者你认为通常是什么启动了你的歌曲创作过程？

[05:24] It really is more about time.
  这其实更多是关于时间。

[05:27] Like what am I doing?
  比如我在做什么？

[05:27] Any musical instrument anywhere or if there's any time where it's like, "Oh actually, I could be doing music now." then it really doesn't matter where I am.
  任何地方的任何乐器，或者如果有任何时刻像这样，‘哦，其实我现在可以做音乐了。’那么我在哪里真的不重要。

[05:35] I can make music out of anything.
  我可以用任何东西做音乐。

[05:38] Um I think it is really about just feeling calm and excited and like there's not a lot on your back right now and that the sense that you actually might have time to finish something or even just manage to do a verse or even if you did capture something.
  嗯，我认为这真的只是关于感到平静和兴奋，就像现在没什么压力，以及那种你实际上可能有时间完成某件事，甚至只是设法做一段歌词，或者即使你确实捕捉到了什么的感觉。

[05:51] I also bought this this fun little It's called the drone machine and it's made by Stylophone.
  我还买了这个有趣的小东西，它叫无人机机，是Stylophone制造的。

[05:56] Um and I love it and I spent 4 hours uh just like noodling around on it on the plane the other day, but I didn't have a way to record it into my iPhone.
  嗯，我很喜欢它，前几天我在飞机上花了4个小时，嗯，就像在上面随意摆弄，但我没办法把它录到我的iPhone里。

[06:04] Um so and I didn't bring my laptop.
  嗯，所以我也没带我的笔记本电脑。

[06:04] So, yeah.
  所以，是的。

[06:06] There's just it is right now it involves lots of steps to just kind of clear the area to make me enable me to just actually put something down.
  目前的情况就是它涉及很多步骤，只是为了清理区域，让我能够真正放下一些东西。

[06:16] But most of the time it's a notepad.
  但大多数时候它是一个记事本。

[06:18] I just write all the time in my little notepad or in my notes.
  我一直都在我的小记事本或笔记里写东西。

[06:23] It's when I was younger, it was a piano.
  我年轻的时候，那是一架钢琴。

[06:26] It was a piano or it was a cassette player.
  那是一架钢琴或一台卡带播放器。

[06:28] I would just come up with something.
  我总会想出点什么。

[06:30] But now life is different, very hectic.
  但现在生活不同了，非常忙碌。

[06:32] There's so much stuff going on, there's little peace.
  有太多事情发生，几乎没有平静。

[06:36] So, it's just little scraps of things really here and there.
  所以，真的只是这里那里的一些零碎东西。

[06:38] And like this little Stylophone thing is really cool.
  而且像这个小Stylophone的东西真的很酷。

[06:41] Interesting.
  有趣。

[06:43] So, I want to get to AI-mogen, Oracles, and the MiMu gloves.
  所以，我想谈谈AI-mogen、Oracles和MiMu手套。

[06:51] But before I get there, I am very curious like when was the first time that you realized that generative AI was going to be very impactful in music?
  但在那之前，我很好奇，你第一次意识到生成式AI将对音乐产生巨大影响是什么时候？

[07:01] I don't know.
  我不知道。

[07:03] I think it like weirdly crept up on me.
  我觉得它奇怪地悄悄接近了我。

[07:05] The first time I did any generative anything was with a human.
  我第一次做任何生成性的事情是和一个人一起。

[07:06] Uh, called Rob Thomas and this was about 15, 17 years ago and he wrote code for apps.
  呃，我联系了罗伯·托马斯，这大约是15、17年前的事了，他编写了应用程序的代码。

[07:14] And he had, there was this brilliant app.
  他有一个非常出色的应用程序。

[07:16] Basically, it would take the world around you and it would synthesize it in harmony.
  基本上，它会捕捉你周围的世界，并以和谐的方式合成它。

[07:20] So, if you're on the train, it would kind of have resonant frequencies of everything and then it would just sound all in time and in tune.
  所以，如果你在火车上，它会捕捉所有东西的共振频率，然后听起来完全合拍且音调准确。

[07:26] Um, RJDJ, that's what it was called.
  嗯，它叫RJDJ。

[07:31] And there was all these different scenes and they were really great.
  而且有各种不同的场景，它们都非常棒。

[07:33] Anyway, I loved it so much I reached out to him.
  总之，我非常喜欢它，于是联系了他。

[07:35] I was like, "Can I speak to somebody there?"
  我说：“我能和那里的人谈谈吗？”

[07:37] And then he came round and we did this experiment where he would, he would personally analyze the way that I improvised.
  然后他过来了，我们做了这个实验，他会亲自分析我即兴演奏的方式。

[07:42] And then he created a little program so that could generate music, um, in the style of the way that I played piano.
  然后他创建了一个小程序，可以生成音乐，嗯，以我弹钢琴的风格。

[07:49] So, he was just like, you know, mentally, um, creating a little algorithm as a human, as kind of apportioning, kind of appropriating what he thought was me.
  所以，他就像，你知道，在脑海中，嗯，作为一个人创建了一个小算法，有点像是分配、挪用他认为属于我的东西。

[08:00] Um, and it just kind of occurred to me, "Wow, that'd be so useful to be able to just like start improvising and then the piano continues."
  嗯，我突然想到：“哇，能够开始即兴演奏然后钢琴继续下去，那真是太有用了。”

[08:07] on without me and then I can kind of jam kind of with myself but like a one step removed, but it's still kind of me.
  没有我继续下去，然后我可以在某种程度上与自己即兴演奏，但就像隔了一步，不过那仍然是我。

[08:13] And so I always was I was really inspired by that and that started a song called Runtime because we were going to make a running app out of it that would like work to the rhythm of your of your running and everything.
  所以我一直深受启发，这开始了一首名为《Runtime》的歌，因为我们打算用它做一个跑步应用，可以配合你跑步的节奏等等。

[08:25] Um I think that that's a total thing now.
  嗯，我觉得现在这已经很普遍了。

[08:27] Um but we wanted to we wanted to explore that.
  嗯，但我们想要探索这一点。

[08:30] So, it was yeah, about 17 years ago.
  所以，是的，大约17年前。

[08:32] But I suppose the way that I feel now it's impacting is just everybody's terrified.
  但我想，我现在感受到的影响就是每个人都吓坏了。

[08:37] That's not true.
  那不是真的。

[08:38] Not everyone's terrified.
  不是每个人都害怕。

[08:40] I'm not terrified.
  我并不害怕。

[08:40] I'm just aware that even not just even music, everything everything uh is is being turned upside down and it's not all a loss.
  我只是意识到，甚至不仅仅是音乐，一切都在被颠覆，但这并非全是损失。

[08:49] Uh there are many things that we can do to mitigate it and to set the standard to to make things better for us in the future by getting things right now.
  呃，我们可以做很多事情来缓解它，并通过现在把事情做好来设定标准，让未来对我们更有利。

[08:59] Um and I'm excited about the question of DC as a a kind of an evolution of us as people.
  嗯，我对DC作为我们人类的一种进化这个问题感到兴奋。

[09:05] Um and I'm excited to with all the possibilities.
  嗯，我对所有的可能性感到兴奋。

[09:07] That can happen.
  那是可能发生的。

[09:08] But I've been doing like AI judging of AI music, um, competitions for about, I don't know.
  但我一直在做类似AI评判AI音乐，嗯，比赛，大概，我不知道。

[09:08] I think I want to talk about that for about 4 hours.
  我想我想谈论那个大约四个小时。

[09:13] Um, but I felt like only really everywhere else, uh, I felt the big change in the last 2 years really.
  嗯，但我感觉真的只在其他地方，呃，我确实感觉到了过去两年里的巨大变化。

[09:26] I've been asked to do that like three or four times over the last 10 years.
  在过去十年里，我被要求做那件事大概三四次。

[09:30] And there was a sudden like jerk basically of like, "Oh wow, this sounds completely amazing compared to what it did then."
  然后突然有一个像急转一样的变化，基本上就是，“哦哇，这听起来和它当时做的相比完全令人惊叹。”

[09:37] Um, and you know, that is incredible, you know, the shift that really happened over, you know, the year basically.
  嗯，而且你知道，那太不可思议了，你知道，基本上在一年里真正发生的转变。

[09:43] [clears throat]
  [清嗓子]

[09:43] I feel like for me when I noticed a huge shift was I, I started reporting on AI music and it was just like they could generate kind of a shitty but passable instrumental, but then when Suno came out and you could really generate everything at the click of a button and it sounded pretty convincing and increasingly it's gotten even more and more convincing.
  我觉得对我来说，当我注意到一个巨大转变时，是我开始报道AI音乐，那时他们只能生成一种糟糕但还过得去的器乐，但后来当Suno出现时，你真的可以一键生成一切，而且听起来相当令人信服，并且越来越令人信服。

[10:04] That's when I really felt, felt like, oh wow, it's suddenly here.
  那是我真正感觉，感觉像，哦哇，它突然来了。

[10:08] It just a a moment when things really did shift.
  那只是一个事情真正发生转变的时刻。

[10:15] And it's interesting that we're talking this week because um it feels like right now a lot of these so-called like AI artists, which I don't know how I feel about that term.
  而且有趣的是我们这周在讨论这个，因为嗯，感觉现在很多所谓的AI艺术家——我不确定我对这个词有什么感觉。

[10:23] Um but there's a lot of people who are using AI tools very heavily in their creative process that are now actually seeing some level of success from it.
  嗯，但有很多人在创作过程中大量使用AI工具，现在确实从中获得了一定程度的成功。

[10:33] Cuz I think at first it was maybe a creative experimentation, but they weren't rising up the charts or they weren't trending on TikTok or getting a lot of streams, but now we're starting to see that with like uh Zenia Monet.
  因为我觉得一开始这可能只是创意实验，但他们没有登上排行榜，没有在TikTok上走红，也没有获得大量播放量，但现在我们开始看到像嗯Zenia Monet这样的情况。

[10:48] I I'm wondering for you as these kind of heavily AI generated projects start entering the marketplace alongside human-made works, do you think that these things should be treated similarly in terms of what royalties they make, um what opportunities they have, or do you think there needs to be some distinction between AI works and human-made works?
  我很好奇，对于你来说，随着这些大量由AI生成的项目开始与人类创作的作品一起进入市场，你认为这些东西在版税收入、机会等方面应该被同等对待，还是你认为AI作品和人类作品之间需要有所区分？

[11:11] And all the gray in between.
  以及介于两者之间的所有灰色地带。

[11:12] Yeah.
  是的。

[11:12] Yeah, and then all the gray in between.
  是的，然后还有介于两者之间的所有灰色地带。

[11:14] Yes, for sure.
  是的，当然。

[11:14] No, I do think we need to have a way to identify in some form, however little or granulated that can be right now.
  不，我确实认为我们需要一种方式，以某种形式进行识别，无论现在这种识别可以多么微小或细化。

[11:25] Um but we definitely need to build the layer that allows the humans to show their input and to be verified by other humans as that is that person's work and because, you know, I trust this person who trust this person and that's what we're doing, which we might talk about later with Oracles.
  嗯，但我们绝对需要构建一个层，让人类能够展示他们的输入，并由其他人类验证那是那个人的作品，因为，你知道，我相信这个人，这个人相信那个人，这就是我们正在做的，我们稍后可能会在讨论预言机时谈到。

[11:41] Um it's just a place for a human to say this is me, these are my works, um these are the people that I work with, these are all the this is all the contextual information around this piece of music and how I made it and the instruments and whatever it is that whatever people want to find out.
  嗯，这只是一个地方，让人类可以说这就是我，这些是我的作品，嗯这些是我合作的人，这些都是围绕这首音乐的所有背景信息，以及我如何制作它、使用的乐器，以及任何人们想了解的东西。

[11:56] Um and creating this wealth of information that the future and now industry can build on.
  嗯，并创造这个丰富的、未来和现在行业可以依赖的信息库。

[12:01] So, until that happens, we are still kind of floating around in midair because we don't even have the bedrock of understanding even right now as we're still in this kind of
  所以，在那发生之前，我们仍然有点悬在半空中，因为即使现在，我们甚至还没有理解的基石，因为我们仍然处于这种状态。

[12:11] Traditional music making way of identifying human work even now.
  传统音乐至今仍是识别人类作品的一种方式。

[12:16] And that's one of the main problems.
  而这是主要问题之一。

[12:18] Yeah, that's something that I've been encountering in my own reporting is people come to me and they'll say, "Hey, this song is AI-generated."
  是的，我在自己的报道中经常遇到这种情况：人们来找我，他们会说：“嘿，这首歌是AI生成的。”

[12:24] And I'm like, I don't know for sure that it is AI-generated or if it is fully human-made.
  而我会说，我不确定它到底是AI生成的还是完全由人类创作的。

[12:30] And um I think AI detection tools still have a long way to go and I'm really, really hopeful that there's some strides made in that because right now it's one of those it's almost like a guessing game and you'd hate to uh accuse someone of using AI or say an AI work is human and have that be completely wrong.
  嗯，我认为AI检测工具还有很长的路要走，我真的非常希望在这方面能取得一些进展，因为目前这几乎就像一场猜谜游戏，你肯定不想错误地指责某人使用了AI，或者把AI作品说成是人类作品而完全搞错。

[12:49] But like you were saying before, there's like such a gray area in the middle.
  但就像你之前说的，中间存在一个非常模糊的灰色地带。

[12:53] When we talk about or we see headlines about AI songs or AI artists, this can be anything from something that is fully generated just using a prompt and then the human steps back or it could be something where it's mostly human-made, but there's just an AI vocal that's incorporated.
  当我们谈论或看到关于AI歌曲或AI艺术家的头条新闻时，这可能涵盖从完全通过提示词生成、人类退居一旁的作品，到主要是人类创作但只是融入了AI人声的作品。

[13:10] Kristen, actually I just want to butt in because you said
  克里斯汀，实际上我想插句话，因为你刚才说

[13:11] Then about mistaking human music for AI music.
  然后是关于把人类音乐误认为是AI音乐。

[13:16] And actually, embarrassingly, I did that the other day and I felt really bad about it.
  实际上，尴尬的是，我前几天就这么做了，而且我感到非常内疚。

[13:20] So, I discovered this artist when I was listening to a playlist and I discovered this playlist because of my new favorite artist called Blawan, which I know I'm a bit late in the day, but I just love this record that he's done.
  所以，我在听一个播放列表时发现了这位艺术家，而我发现这个播放列表是因为我最喜欢的新艺术家叫Blawan，我知道我有点晚了，但我就是喜欢他做的这张唱片。

[13:30] So, it recommended, you know, go listen to this other stuff.
  所以，它推荐了，你知道，去听听其他东西。

[13:34] So, I found this long playlist and I listened to loads of stuff.
  所以，我找到了这个很长的播放列表，听了许多东西。

[13:36] I was like, "Oh, I quite like it."
  我当时想，“哦，我挺喜欢的。”

[13:38] I made a load of notes on this plane journey.
  我在这次飞机旅行中做了很多笔记。

[13:39] But one of them was that this artist called Dataclast and I was like, "Wow, this really sounds like Max Cooper and Jon Hopkins.
  但其中一个是这位叫Dataclast的艺术家，我当时想，“哇，这听起来真的很像Max Cooper和Jon Hopkins。

[13:48] Like it really really does.
  就像真的真的很像。

[13:50] Like I was really suspicious and I looked up on this, you know, on the biography about this person and it was it just said data made music made with errors or something like that.
  就像我真的很怀疑，我查了查，你知道，关于这个人的传记，上面只是说数据制作音乐，用错误之类的东西制作的。

[14:00] And I was like, "Mm, this is very suspicious."
  我当时想，“嗯，这非常可疑。”

[14:02] And then I looked this person up and I did actually find a person behind it.
  然后我查了这个人，我确实找到了背后的人。

[14:06] But I was like, "Ah, but that could be a ruse.
  但我当时想，“啊，但那可能是个诡计。

[14:07] Might not be real."
  可能不是真的。”

[14:09] Anyway, I found their Instagram page and then I followed them and this person was like, "Oh my..."
  总之，我找到了他们的Instagram页面，然后关注了他们，这个人说，“哦，我的……”

[14:13] God, imagine hey, uh, is this real?
  天啊，想象一下，嘿，呃，这是真的吗？

[14:16] And I was like, "Are you real?"
  然后我就想，“你是真实的吗？”

[14:17] I love your music.
  我喜欢你的音乐。

[14:19] Blah, blah, blah.
  等等，等等，等等。

[14:20] Yeah, I was going to say like both of you were
  是的，我本来想说你们两个都是

[14:22] [laughter]
  [笑声]

[14:22] Cuz I just said this this record that you've done I absolutely love it.
  因为我刚才说了，你做的这张唱片我绝对喜欢。

[14:24] Like I'm really, really enjoying it, but I can't help feeling how similar it is sometimes to Max Cooper and my friend John.
  就像我真的很享受它，但我忍不住觉得它有时和Max Cooper以及我的朋友John的作品太相似了。

[14:31] And he was like, "Oh, thanks so much.
  然后他说，“哦，非常感谢。

[14:33] Those are my biggest heroes.
  他们是我最大的偶像。

[14:34] That's like the best thing you could have ever said to me."
  这就像你能对我说过的最好的话。”

[14:36] And I was like, "No, and don't take this the wrong way, but did you create a model that kind of, you know, mashes them up together and then generates them and kind of just stuff over the top?
  然后我就想，“不，别误会，但你是不是创建了一个模型，那种，你知道的，把它们混在一起，然后生成它们，再在上面随便加点东西？”

[14:46] He was like, "Absolutely no way.
  他说，“绝对不可能。

[14:48] I can show you the stems.
  我可以给你看分轨。

[14:50] I can do this with it."
  我可以用它做这个。”

[14:50] And fair enough, he got like, you know, a bit offended.
  好吧，他有点，你知道，被冒犯了。

[14:53] Um but it it has got to that point where we can recreate things and honor people and uh and we do all the time.
  嗯，但已经到了那个地步，我们可以重现事物并致敬他人，呃，而且我们一直在这样做。

[14:58] Sometimes without knowing it.
  有时甚至没有意识到。

[15:00] We just we go, "Oh, we've I've come up with this idea."
  我们只是说，“哦，我们——我想出了这个主意。”

[15:04] And actually it was something that somebody else did, but you just forgot about it and you thought it was an original idea.
  而实际上那是别人做过的东西，但你只是忘记了，还以为是个原创想法。

[15:08] Um and that happens all the time.
  嗯，这种事经常发生。

[15:10] So, I'm quite yeah, I we definitely are at that place where it's very confusing
  所以，我相当——是的，我们确实处于那个非常令人困惑的阶段

[15:14] Right now.
  现在。

[15:16] Um, and we do need some clarity.
  嗯，我们确实需要一些清晰度。

[15:18] But it — we are, we, we can do it.
  但——我们是，我们，我们能行。

[15:21] There are tools and everybody wants it.
  有工具，而且每个人都想要它。

[15:24] So, I feel like the silver lining really of this dark cloud, as some might see it as AI music taking over, is that we are going to get the data layer of works.
  所以，我觉得这片乌云（有些人可能视其为AI音乐接管）的真正一线希望是，我们将获得作品的数据层。

[15:34] We're going to get this complete data layer of works because people will want to prove not only that they're human, but they want to go — they want to actually just say, "Do you know what? I'm human and these are all of my works that I actually contributed to, even if I'm a mixing engineer or whatever it is."
  我们将获得这个完整的数据层，因为人们不仅想证明他们是人类，而且他们想——他们实际上只想说：“你知道吗？我是人类，这些都是我实际参与的作品，即使我是一名混音工程师或其他什么。”

[15:51] So, I feel like, you know, this panic in, uh, you know, how we going to — how we going to, um, know what's what is also going to empower us to just do what we've needed to do for like 100 years.
  所以，我觉得，你知道，这种恐慌——嗯，你知道，我们如何——我们如何，嗯，分辨是非——也将赋予我们力量去做我们一百年来一直需要做的事情。

[16:01] I recently spoke to someone at Hallwood Media, which is signing AI artists.
  我最近与Hallwood Media的某人交谈过，他们正在签约AI艺术家。

[16:05] They've signed this Zenia Monet, um, artist, which, um, has gone pretty viral in recent weeks.
  他们签下了这位Zenia Monet，嗯，艺术家，嗯，最近几周相当火爆。

[16:12] Um, and one of the things that they said is because Zenia is backed by
  嗯，他们说的其中一件事是，因为Zenia得到了……的支持

[16:15] Real person who essentially writes poetry and then uses Suno to help complete that poetry into a song, they record or they have her record herself making her music so that if anyone ever has questions about it, they can actually show like, "Here's exactly what she did. Here's exactly what AI did."
  真实的人本质上写诗，然后使用Suno帮助将诗歌完成成一首歌，他们录制或让她录制自己创作音乐的过程，这样如果有人对此有疑问，他们可以实际展示，比如：“这是她做的。这是AI做的。”

[16:32] I could kind of see that being something that uh becomes a thing in the coming years um of just trying to create a log of here's what I did, here's what AI did as that increasingly becomes part of the creative process.
  我有点觉得这可能会在未来成为一种趋势，嗯，就是试图创建一个日志，记录我做了什么，AI做了什么，因为这越来越成为创作过程的一部分。

[16:46] But I do want to go back to that point about Hallwood signing AI artists.
  但我确实想回到关于Hallwood签约AI艺术家这一点。

[16:49] Um they're the first label that has been pretty public about doing this.
  嗯，他们是第一个相当公开地这样做的唱片公司。

[16:51] Um I'm wondering in the coming few years, do you anticipate that this will become a thing where major record labels are signing AI talent um or um talent that heavily uses AI?
  嗯，我想知道在未来几年，你是否预计这将成为一种趋势，即主要唱片公司签约AI人才，嗯，或者大量使用AI的人才？

[17:07] And how do you feel about that?
  你对此有何感受？

[17:09] Do you think that that's right?
  你认为这是对的吗？

[17:13] Um I think lots of things when you said that.
  嗯，当你这么说时，我想到了很多事情。

[17:15] I feel like
  我觉得

[17:17] A lot of major labels are signing music that sounds AI-generated to me anyway.
  很多大厂牌都在签约音乐，这些音乐对我来说听起来像是AI生成的。

[17:21] It's just like, "Oh, that just sounds like that last thing or that last thing."
  就像，“哦，那听起来就像上一个东西或者再上一个东西。”

[17:24] And nothing's changed.
  而且什么都没变。

[17:26] Um so, it doesn't surprise me at all that that would happen.
  嗯，所以，那会发生我一点也不惊讶。

[17:29] Um and wherever there's money, obviously they'll go if they think they can make money out of this artist.
  嗯，而且哪里有金钱，显然他们就会去哪里，如果他们觉得能从这个艺术家身上赚钱的话。

[17:35] Um I think right now it's exciting.
  嗯，我觉得现在这很令人兴奋。

[17:37] It's like it's a it's such a nascent space, exciting kind of beginnings where it still sounds a bit AI and it's like you're not quite sure and it's that will soon disappear where you absolutely can't tell.
  这就像它是一个如此初生的领域，令人兴奋的开端，听起来还有点AI，就像你不太确定，而且那种情况很快就会消失，变成你完全分辨不出来。

[17:48] I actually love these early beginnings where the voices just sound like they're they're kind of jumping around or they're the formats of the voice isn't quite right and they they're the diction, the way they say things and their accents is all funny.
  我其实很喜欢这些早期阶段，声音听起来就像它们在跳来跳去，或者声音的格式不太对，而且它们的措辞、说话方式以及口音都很有趣。

[18:01] I I really like that.
  我真的很喜欢那样。

[18:02] I'm kind of going to miss that when AI and humans create music that we never could have expected, you know, that just like really we just wouldn't have gone there because you couldn't really imagine mashing that thing with that thing cuz it would have taken so long to do it with a band, with
  我有点会怀念那个，当AI和人类创造出我们从未预料到的音乐时，你知道，就像我们真的不会去那里，因为你无法真正想象把那个东西和那个东西混在一起，因为用乐队来做会花太长时间，用

[18:17] A thing.
  一件事。

[18:17] I don't know.
  我不知道。

[18:19] Um, that we'll just be able to iterate and hear things differently, and it will just, it will, it will really just like make us hyper-creative.
  嗯，这样我们就能不断迭代，以不同的方式听到东西，而这会让我们变得超级有创造力。

[18:25] So, I'm excited for the music that's going to come and the people that are going to mash and hack these systems together to create like weird, kind of weird sculptures with small heads and but music.
  所以，我对即将到来的音乐以及那些将把各种系统混搭和破解在一起、创造出像奇怪的小头雕塑但又是音乐的东西的人们感到兴奋。

[18:41] Um, because why not?
  嗯，为什么不呢？

[18:41] Like, we're not really, we're not really pushing the boat out a lot.
  就像，我们并没有真正地大胆创新。

[18:45] Um, and I, I really think we need to.
  嗯，而且我真的认为我们需要这样做。

[18:47] And I think we'll go through this boring phase of people just mimicking what we do.
  而且我认为我们会经历一个无聊的阶段，人们只是模仿我们所做的事情。

[18:50] And then once we've got over that, um, we will, we'll create music that's like really astounding and exciting, but it will be, it will be a complete cross between us.
  然后一旦我们克服了那个阶段，嗯，我们就会创造出真正令人震惊和兴奋的音乐，但它会是，它会是我们之间完全的融合。

[19:01] What you just said earlier, um, really reminded me of a quote from Brian Eno, who I'm, I'm going to butcher it.
  你刚才说的，嗯，真的让我想起了布莱恩·伊诺的一句话，我可能会引用得很糟糕。

[19:06] I don't know it off the top of my head, but he talked about how, um, after a technology gets really good, people start to have a fondness for like whatever the quality of it that everyone criticized when it first came out.
  我一时想不起来原话，但他谈到，嗯，当一项技术变得非常好之后，人们开始喜欢上它最初问世时被所有人批评的那些特质。

[19:18] Mean early photography and film did not look good.
  早期的摄影和电影看起来并不好。

[19:20] There was a grain on it.
  上面有颗粒感。

[19:23] It didn't look totally real to life, but after a while now we're adding film grain onto things to make it look kind of emulate that style.
  它看起来并不完全真实，但过了一段时间，现在我们给东西添加胶片颗粒，让它看起来有点模仿那种风格。

[19:30] I think it'll be interesting to see what people think of like looking back on I guess like 2021 AI-generated images where like the hands are all messed up and they have different fingers uh that are not right.
  我觉得看看人们怎么看待回顾2021年AI生成的图像会很有趣，那些图像里手都乱七八糟，手指数量不对。

[19:41] But yeah, it'll be fascinating.
  但没错，这会很迷人。

[19:44] But I wanted to go back to something that you've referenced before.
  但我想回到你之前提到过的一件事。

[19:48] You said um that even like, you know, 15 years ago you were working with AI to try to create an algorithm that mimicked the way that your creative process worked.
  你说，嗯，甚至像，你知道，15年前你就在用AI尝试创建一个模仿你创作过程运作方式的算法。

[19:59] I was using a human.
  我当时用的是人类。

[20:01] I was using a human to do it.
  我用人类来做这件事。

[20:03] Okay, yeah, yeah, yeah.
  好的，是的，是的，是的。

[20:05] Yeah, but it was the beginnings of this generative idea that you can extend yourself beyond just your human capacity.
  是的，但这是这种生成性想法的开端，即你可以超越自己的人类能力。

[20:08] That you can create a code that will emulate you then beyond.
  你可以创建一个代码，它会模仿你，然后超越。

[20:13] Yes, and so now like you've recently released a 13-minute song called I Am.
  是的，所以现在，比如你最近发布了一首13分钟的歌曲，叫《I Am》。

[20:19] which also has a beautiful visual that

[20:21] goes along with it. And in that song,

[20:23] it's not just you singing, it's also AI

[20:26] Mogen, which is your essentially digital

[20:28] self or your AI self. So, can you tell

[20:31] me about what AI Mogen is and why you

[20:35] think that that is an interesting

[20:36] creative interplay to essentially

[20:38] collaborate with yourself? Well, I don't

[20:40] think the way that I've used AI Mogen in

[20:42] this song is particularly creative. Um,

[20:45] it's kind of a very long-winded kind of

[20:46] silly way around of doing things, but I

[20:48] did it as a statement. Um, and I did it

[20:51] to

[20:52] rile people up, I suppose, and just have

[20:54] a be able to have this conversation.

[20:56] Because the song in the beginning, it

[20:58] takes you through this journey really of

[21:00] what I've experienced over the last four

[21:02] years. I recognized I was starting to

[21:04] think about who am I, um, what am I,

[21:07] what, you know, this ego, what is it?

[21:10] What what's stressing me out? Like, what

[21:12] is it when you get rid of all of that in

[21:14] just in breath or in silence or in the

[21:17] noise, what's there?

[21:19] And then I started to think about AI

[21:22] because, um,

[21:24] what is what is that that that AI isn't?

[21:26] Um, what can what can I feel

[21:29] that is something that an AI can't feel?

[21:31] And I kind of got down to these like

[21:34] bits, these tiny bits. Um, and so the

[21:38] noise section in that song is like the

[21:39] annihilation of my ego. Well, I'm I'm

[21:42] not saying I'm going to get it. Um, so

[21:44] then I needed I needed aftercare after

[21:46] that. I love this idea that AIs are

[21:49] child.

[21:50] AI is something that we are raising

[21:52] together uh, as the as the mother and

[21:56] father, as the

[21:57] you know, as the uh, the adults, um,

[22:00] raising up this child. And what I messed

[22:03] with it is

[22:04] of that. Um, and and right at the end

[22:07] there's this there's the AI voice of

[22:09] Mogen. I wanted it to be an AI voice

[22:11] even though I had to sing everything.

[22:13] And so I sang all the parts and then I

[22:15] put it through my AI model so that it's

[22:18] the model of my voice that's then

[22:19] singing the words rather than my actual

[22:21] words that I'm saying. But the melody of

[22:23] it and all the

[22:24] you know, inflections and the all of

[22:26] that is me.

[22:27] But the sound of it is like changing the

[22:29] sound on a on a keyboard.

[22:31] Yeah, so it's like putting a filter on

[22:33] top of it in a way. So, you still had to

[22:35] do the act of singing.

[22:36] Yeah, I had to do the singing, but it's

[22:37] like changing output sound for another

[22:40] sound. So, it could have been a trumpet.

[22:42] And I wanted to trick people, you know,

[22:43] into going after all of this music,

[22:45] after all of this like quite traumatic

[22:48] noise section, that they would

[22:50] they would feel something and that voice

[22:53] would not be my voice, it'd be AI

[22:55] Mogen's voice. I wanted to create a

[22:56] discussion. I wanted to, you know, show

[22:59] people that we already don't know. But

[23:01] does it matter, you know?

[23:03] Um, I mean, I say in the in the title

[23:05] it's AI Mogen. Um, but it was all

[23:07] ethically sourced. It's all done in the

[23:09] the best way possible and it's my own

[23:11] voice and I didn't use any I didn't

[23:12] generate any music. Of course, everybody

[23:15] has already uh, some people have already

[23:17] canceled me for, you know, even talking

[23:20] or saying that AI is in my music. Some

[23:22] many of them were like, "I can't believe

[23:23] Mogen, I'll never listen to your music

[23:24] again.

[23:25] You used AI to generate the self." I was

[23:27] like, "No, I did not. Uh, I wish that I

[23:30] could have done it cuz it took me four

[23:32] years to do it with 100,000s of hours."

[23:35] Um, anyway, so my point is that

[23:37] it everybody is fearful of it. Um, but

[23:40] we can still feel, you know? And

[23:43] what

[23:44] what is art

[23:46] you know, art is something to someone or

[23:47] not to somebody else, but if it

[23:49] essentially it speaks to you and it

[23:51] makes you feel something,

[23:53] does it matter?

[23:54] If it makes you recognize something in

[23:57] yourself. I mean, essentially all AI is

[23:59] generated from human work. So,

[24:02] um,

[24:03] and I think that what we'll end up with

[24:05] over time

[24:06] is the AI models that we do rely and

[24:09] live with

[24:11] will teach us that we don't need

[24:12] anything else. We don't need this

[24:14] capitalist horrible world that we

[24:16] have got to the extreme of. We just need

[24:20] each other to be kind to each other for

[24:22] communities, to care about, you know, we

[24:23] don't need happiness out there. It's not

[24:25] something we can buy a Porsche or

[24:26] something that makes us happy. Um, you

[24:28] know, so the the voice right at the end

[24:31] of the song is actually my daughter's

[24:33] voice.

[24:33] And she's the she has the last word. Um,

[24:37] and that is to say that, you know, AI

[24:39] Mogen Scout

[24:42] AI um, they're our children and we need

[24:46] to take care of them and we need to do a

[24:47] good job of showing them how to do

[24:49] things the way that we would like them

[24:51] to be done, not how we're currently

[24:52] doing a lot of things.

[24:54] That's so fascinating. I mean, I I love

[24:56] that you've been able to make this model

[24:59] with AI Mogen that is totally within

[25:01] your control. So, you can do with it

[25:03] what you like. I think the the thing

[25:06] that gets scary is when, you know,

[25:08] anyone can manipulate or find anyone's

[25:10] voice model online or or train a voice

[25:13] model based on interviews that people

[25:14] have done in the past and just run with

[25:16] it. Um, I'm wondering in an age of AI,

[25:20] um, I wonder how artists will continue

[25:22] to self-curate. Uh, I think such a

[25:25] important part of being an artist is

[25:26] having the taste and the curation to

[25:28] know what you want to say, um, what

[25:31] songs you want to put out, what songs

[25:32] you want to keep for yourself, what

[25:34] interviews you want to do, what things

[25:35] you don't want to do. In an age of AI,

[25:37] it feels like you're losing a lot of

[25:39] control over yourself. Um, do you have

[25:42] fears around that? I mean, we already

[25:44] have lost control. Uh, people misquote

[25:46] us constantly, you know, say that we've

[25:49] written something when we haven't, don't

[25:51] credit us when we have been a part of

[25:52] it. That that's still very much there.

[25:54] So, I do actually think this is going to

[25:55] really

[25:56] it's just going to

[25:57] it's going to force us into creating

[25:59] something that will make sense of what

[26:01] we have already for and for the future

[26:02] so that we can put a flag in the sand as

[26:05] humans and go, "Okay, up to this point

[26:08] um, it was human generated and then

[26:10] there was like this blurry space and

[26:12] then we figured it out and now you can

[26:14] really discover what is what." Um,

[26:17] I I'm excited cuz I like I have you

[26:20] other people have also used my voice.

[26:22] Um, there's an artist called Beretta

[26:23] who's created a great dance track with

[26:25] it. And there is um, an artist called

[26:27] Lucy Hayes has done a really amazing

[26:29] song with it, too. And you can go to uh,

[26:31] I have a profile on the DSPs as AI.Mogen

[26:35] and you can see the songs that she her

[26:36] voice has sung including my voice. Uh,

[26:38] including my song. Um, but the nice

[26:41] thing about that is as I say, you have

[26:42] control. Uh, again, I think it just

[26:44] comes down to this like core missing uh,

[26:47] piece that we don't have, which is an ID

[26:50] layer, like identifying a home for each

[26:52] individual. That I think we'll just have

[26:55] in time anyway just as much as there's

[26:56] one physical version of you in the world

[26:58] even though we'd like there to be more

[26:59] of us. Um, and there's one of me, but

[27:01] there's no digital one version of me

[27:04] somewhere that I own, that I can, that

[27:07] anyone in the world can go to to find de

[27:09] facto information about me, you know, up

[27:12] to the minute if they need to. So that I

[27:14] can express whatever I want to express

[27:17] in like a kind of umbilical cord to

[27:19] anything that I might be connected to in

[27:21] one instant from one place. Um, I want

[27:24] to be able to do that. I'm wondering,

[27:26] how are you seeing some of your peers

[27:28] use AI in their musical process that

[27:31] inspire you? Is there anything

[27:32] interesting you've seen recently? I'm

[27:34] not seeing any of my peers doing any

[27:36] music with a with AI. Maybe I've got the

[27:38] I don't know. I just feel like all my

[27:41] friends, they're just like, "We just

[27:42] make music the way we always made

[27:43] music." Um,

[27:45] I'm really interested in developing

[27:47] Mogen to the point where I can jam on

[27:49] stage with her, where she can train off

[27:52] my music and she can continue, like say

[27:55] if I if I really do want to do this.

[27:57] Like I don't want to slave away in front

[27:58] of the computer and make

[28:00] tracks like I Am for the rest of my

[28:02] life. I don't want to do that. Like I

[28:03] really don't want to do that. I would

[28:04] love to find ways to speed up the

[28:07] process but not take away any of the

[28:08] creativity. And there are many things

[28:10] you do in the studio or to prepare

[28:13] plugins or, you know, that you can clean

[28:15] up and you can help AI could help you do

[28:17] some of that admin or help you identify

[28:21] things that could be similar sounding

[28:23] that you could pull in without having to

[28:24] go through all the presets. I mean,

[28:26] there are already things that do that. I

[28:27] mean, Splice, I'm pretty sure, has

[28:29] started to do that. I would say that

[28:30] very few artists, I mean, I know that

[28:33] um, is it Timbaland that's like a lot on

[28:35] Suno? Yes. And he's like very

[28:39] Yeah. advocating. Um, and I understand

[28:41] it. It's fun. It's like it's super fun.

[28:44] And it had it is hard not to go not to

[28:47] go there. I had to play, you know, I

[28:48] have had a play and I was like, "Whoa."

[28:51] Hold on a minute. That's actually

[28:53] That's actually really cool. Like I

[28:54] would I actually might use that. But I

[28:56] you have to stop yourself because I do

[28:58] have I do want to create standards that

[29:01] that allow for musicians to be

[29:03] recognized for the work that they've

[29:05] done that these these streaming service

[29:07] that these um,

[29:08] uh, AI models have learned from and

[29:10] Hoover that but are not in any way

[29:13] caring at the moment seemingly about how

[29:15] to solve that problem. And I really want

[29:17] to spend my time helping to solve that

[29:19] problem, helping to contribute to,

[29:22] you know, attribution for musicians of

[29:25] the past and the now. Um, so that they

[29:27] see themselves in these future models if

[29:29] they want to. And if they don't, fine.

[29:32] One of the things that I've heard from

[29:33] AI companies before is that they foresee

[29:35] a time when pretty much everyone makes

[29:38] music. Um, one person even said to me

[29:40] once, um,

[29:42] that, you know, back in the day we could

[29:44] have never foreseen that people would go

[29:46] from, you know, uh, if you wanted to get

[29:48] your family photographed, you'd have to

[29:50] go to a photographer who was a

[29:51] professional and had the camera, sit

[29:53] down with them at a special place, but

[29:55] now we just take photos on our iPhone.

[29:58] And this person was saying that they

[30:00] foresee a time when everyone just gets

[30:02] to make music. It's not something

[30:04] reserved

[30:05] for musicians anymore, I guess.

[30:07] Great. What's wrong with that? Yeah,

[30:09] yeah, I'm wondering what your thoughts

[30:10] are on like the the barrier to entry

[30:12] lowering so that everyone could feasibly

[30:16] do it.

[30:17] I really Why not? So they have spent

[30:19] many lots of thousands of hours,

[30:20] whatever, uh, perfecting your craft. You

[30:22] always have an edge.

[30:23] Um, you know, whether you're If you

[30:25] generate anything off these, you know,

[30:28] services right now, you're just going to

[30:29] sound like

[30:30] 99.9999% of other things that do that,

[30:33] too. But if you have an edge, if you

[30:35] have a real

[30:36] something there that connects with

[30:38] people and you use it differently and

[30:39] you go a little bit further out of your

[30:41] way and you create something that's

[30:42] genuinely outstandingly good,

[30:44] then that's great. That's really good.

[30:45] That helps everyone move forward. I

[30:47] don't have problem with that at all.

[30:49] Like you said, everyone takes

[30:50] photographs, everyone's talking for we

[30:51] can all put filters on it and clean it

[30:53] up. Um, the other thing is like, why

[30:56] should music just be reserved for those

[30:58] who, you know, have have access to like

[31:01] computers and programming and lessons if

[31:03] you need it and you know, all the time

[31:05] and whatever money, I don't know, but I

[31:07] mean,

[31:09] because initially, um, we all used to

[31:11] sing. Like we sang before we spoke. Um,

[31:15] we we had songs that we would sing and

[31:17] we would dance and

[31:19] we could move our bodies and we felt

[31:21] that was just the way we expressed

[31:22] ourselves and now we're just scared to

[31:24] sing. Um, and so I think this is great,

[31:28] you know, if it helps us connect with

[31:29] our creative inner selves um, and allows

[31:33] us to feel more at peace with ourselves

[31:35] because there's something that's

[31:38] you know, really connecting. If it just

[31:40] feels great to make music, um, then I am

[31:43] definitely for it, 100%. I've got no

[31:45] issues with it. Uh, if anything is just

[31:48] going to

[31:49] what needs to happen, which will happen

[31:51] in tandem with it, is much better

[31:53] discovery tools to help people see

[31:56] through and hear through the noise

[31:58] because it is ever so much harder to

[32:01] find the good stuff out there as there

[32:03] are many, many, many, uh,

[32:06] issues. Well, there's that there you

[32:08] don't really know if you're listening to

[32:09] AI generated music at the moment on on

[32:11] these platforms. I have come across

[32:14] hundreds of

[32:16] uh, generative versions of Headlock um,

[32:19] and other songs that I've done that are

[32:21] definitely not human or largely not

[32:24] human created because they come up

[32:25] quickly. Um, and you look at the

[32:27] profiles and you try and find out and

[32:29] there's there's it all kind of

[32:30] disappears and it's all like one label

[32:32] and nobody really knows. And then they

[32:34] disappear and you know, it's just like,

[32:35] oh, was it there at all? Um, so there's

[32:38] definitely like weird stuff going on

[32:39] already and who knows who's benefiting

[32:42] from that. You know, the top level, who

[32:44] knows. Um, so it is just a mess and I

[32:48] think it's good because it has been a

[32:51] mess forever and now it's just really

[32:52] showing the problem. One of the

[32:54] interesting things that I've been

[32:55] thinking about in terms of AI music is

[32:57] it certainly speeds up the process. So

[32:59] we're going to get more music.

[33:02] Especially I think we're going to see

[33:03] more music ending up on streaming

[33:05] services. Right now we already have

[33:06] 100,000 songs being added every day. You

[33:09] know, if we put AI aside and we look at

[33:10] a few years ago when it was still a

[33:11] similar number of just a mass amount of

[33:14] music coming into the services every

[33:16] day. A lot of that music is from totally

[33:20] DIY artists. I think the the revolution

[33:23] of DIY brought forth a ton of music.

[33:26] But, you know, for the most part most

[33:28] people aren't listening to most of it.

[33:30] Some of it's not very well done and

[33:31] that's okay. You know, they they've

[33:33] released it as a passion project,

[33:35] whatever.

[33:37] But, you know,

[33:38] algorithms allow us to navigate through

[33:40] the 100,000 songs that are there on

[33:43] Spotify every day. And so as AI comes

[33:46] in, I think it'll just accelerate that

[33:48] process. We'll definitely have even more

[33:51] songs,

[33:52] but this is not a new problem. We

[33:53] already have a lot of songs to sort

[33:54] through. So it just has to get smarter

[33:56] and better. I think what we're going to

[33:58] be able to wrap into it,

[33:59] uh, is the story of the song. So right

[34:03] now the algorithms are like pitch and

[34:05] tempo and timbre and like maybe lyrics

[34:08] or dynamic range or that kind of stuff

[34:10] that it's creating algorithms for us to

[34:13] go, oh, you might like this.

[34:15] Um, but you might want different ways to

[34:18] search. You might discover that you

[34:20] like,

[34:21] you know, a particular producer, you

[34:23] know, and if you're lucky you might I

[34:24] don't think you can search by producer

[34:26] at the moment on streaming services, but

[34:28] you can search obviously to artist, but

[34:30] you can't you've just about started to

[34:32] be able to search through composer. Um,

[34:34] but you still have to be registered in a

[34:36] certain way and not everyone's allowed

[34:37] to be a songwriter composer. I've only

[34:38] I've just allowed to be one even after

[34:40] how many 30 years I've been doing it.

[34:42] Um, so there's it's not even at the

[34:46] basic stuff isn't isn't sorted. You

[34:47] can't search through drummer or, um, you

[34:51] know, mixing engineer, um, but you might

[34:53] discover if you could that uh, you

[34:56] actually actually the reason why you

[34:58] love these songs is because of the

[35:00] arranger or it's because of the

[35:01] particular way somebody plays a a

[35:03] stringed instrument that in that um,

[35:05] kind of

[35:06] inspires the mystery of the song for

[35:08] someone. Yeah, yeah. And to kind of

[35:11] pivot the conversation a little bit, you

[35:13] just recently celebrated the 20th

[35:14] anniversary of Speak for Yourself, which

[35:16] is very exciting. [clears throat]

[35:18] And I mean it's it's really crazy how

[35:21] many times these songs keep coming back

[35:23] up.

[35:24] I really enjoyed Normal People

[35:27] and the sync placement that a Hide and

[35:29] Seek had in there a couple years ago.

[35:32] I've been on TikTok and I keep finding

[35:33] your work there as well. I'm wondering,

[35:36] why do you think this has continued to

[35:38] find new audiences organically over

[35:40] time? I don't know. Maybe there's the

[35:42] nostalgia. Um, maybe there's something

[35:45] comforting in it. Um,

[35:48] I don't know. I ask myself the same

[35:49] question. I feel very lucky.

[35:52] Um, I think I I don't know. Maybe it's

[35:55] just a generation of people that 20

[35:57] years ago, you know, were

[36:00] just starting out. They were students or

[36:02] whatever and at that point for them it

[36:04] meant something because they heard it in

[36:05] The OC or whatever, however they

[36:07] discovered it. Um, and people like

[36:10] Ariana Grande, they discovered it then

[36:11] and Taylor that they all kind of

[36:13] discovered it then. And now 20 years

[36:15] later, you know, they're massively

[36:16] famous pop stars and they're just

[36:18] killing it all around the world.

[36:20] And they're introducing people as well.

[36:23] Um,

[36:24] and the people that were watching those

[36:25] programs back then, they're in cool jobs

[36:28] and doing different things and, you

[36:30] know, so they they chuck it in because

[36:32] it means something to them.

[36:34] And I'm finding that not just in the

[36:36] music space, in the like in the fan

[36:39] space, but in a much smaller way also

[36:41] see it in the industry side. I see the

[36:43] people that were my peers when I was

[36:45] younger in the industry, we're also

[36:48] coming together going, "Do you know

[36:49] what?

[36:50] We're going to we're doing things

[36:52] differently now." And I'm finding

[36:54] I'm finding it much easier to navigate

[36:56] and to help shape the future of this

[36:57] industry because it's a different year

[37:00] groups coming through. Basically, the

[37:02] old guard are going out and we are able

[37:06] to come together. I'm like nearly 50

[37:08] now.

[37:09] I've already said it. Um, and it just it

[37:12] just feels like it's easier and then

[37:13] it'll feel easier again for the next

[37:15] generation hopefully as they learn from

[37:17] our mistakes and see that there's no

[37:19] point to be rigid and there's no point

[37:21] to be possessive over things. Nothing

[37:23] fun comes from that, just more pain.

[37:26] Yeah, yeah, earlier you were touching

[37:28] on,

[37:29] um, like the music industry and things

[37:30] turning over.

[37:32] And one of the things I find really

[37:33] interesting about Speak for Yourself is

[37:36] that it was first released I I didn't

[37:38] realize this until very recently that it

[37:39] was released independently,

[37:41] um, which was probably not a very easy

[37:44] thing to do back then. It's now become

[37:45] so much more popular to be an

[37:47] independent artist and to find success

[37:49] that way. I'm wondering, looking back on

[37:52] it, how do you think it compares being

[37:54] an independent artist now versus when

[37:56] you released that album 20 years ago?

[38:00] Um, I feel like I was in a sweet spot

[38:01] because it was just as the industry was

[38:03] going, um, digital and streaming and

[38:06] there was

[38:07] iTunes had come out just literally a

[38:10] month or two before Speak for Yourself

[38:12] happened.

[38:13] And there was only one front window.

[38:14] There was like now there's like 50

[38:16] revolving windows and God bless. And

[38:18] I've got lucky and I got chosen. My

[38:21] album got chosen to be the album of the

[38:24] week on iTunes. Wow. And I was like, how

[38:26] did this happen? You know, I'm a nobody.

[38:29] I'm like I I just couldn't believe it.

[38:32] They you I thought you'd have to pay for

[38:33] that spot, but I did release the record

[38:35] myself. So it was independent and I

[38:37] ingested it myself. I still have an

[38:39] account for that Apple even though I

[38:40] shouldn't. Um, um, because I was one of

[38:43] the first and so I sent a message to the

[38:46] to iTunes uh, like info@itunes or

[38:48] whatever and I was like, "Hello.

[38:51] Uh, just a message to say thank you to

[38:53] whoever put my song my album on the

[38:56] front page." I think it was maybe the UK

[38:58] iTunes. And I was like, "Thank you so

[39:00] much. You don't know how much this means

[39:01] to me." And I got a message back from

[39:02] this guy, um,

[39:04] called Denzil Feigelson,

[39:06] um, and he's he was the boss at the

[39:08] time. Uh, and he was like, "Do you know

[39:09] what? No one's ever thanked us.

[39:12] Would you like to come into the

[39:12] offices?" And I was like, "Yes, I will."

[39:15] Uh, so I went into the went into the

[39:16] offices. I met the Pete Downton who was

[39:18] like one of the first uh, digital

[39:20] streaming, um,

[39:22] gave the music to to streaming companies

[39:24] like Spotify before they had their own

[39:25] way to do that. And I went to their I

[39:27] was the first artist in the office. So I

[39:30] have this like I was at a lucky point

[39:32] where there wasn't that much going on.

[39:34] Um, you were either with a label or you

[39:36] weren't. Um, and I and I reached this

[39:38] point where people were like, "Wow, an

[39:39] actual artist is coming in to the

[39:42] office. This is weird. It's not a music

[39:44] executive. And it it really worked in my

[39:46] favor. Um and it was much less scary to

[39:49] do independent than to go again with a

[39:51] major label. It was just it just tore me

[39:54] apart every time. They just made a

[39:56] terrible job of

[39:58] of not promoting it or promoting it a

[40:00] good job of not promoting it. Yeah, cuz

[40:02] Frou Frou was on a major label, right?

[40:04] And that's

[40:05] then you were dropped after that and you

[40:06] went independent.

[40:07] My first album was called I Megaphone.

[40:09] My second album was Frou Frou with Guy.

[40:12] And then um

[40:14] Frou Frou they decided they didn't want

[40:16] to make another Frou Frou record.

[40:17] And I was like, "Fine." Um then I was

[40:20] like, "Well, we'd like to make an Imogen

[40:21] Heap record." And I was like, "No, thank

[40:23] you." Um you literally you couldn't have

[40:26] made a bigger mess of such a great

[40:28] record. Like we absolutely thought The

[40:29] Details is one of the best things ever.

[40:31] It was so good. Um and now there's so

[40:33] many other people think that. But at the

[40:35] time they were like, "No, no, it didn't

[40:36] get onto Radio 1. It's not not going to

[40:38] be as big as Sugababes." Um and they

[40:40] didn't like give us any airtime at all

[40:42] or any any support. Um they've they made

[40:45] us try and come up with some hits and

[40:46] put on the record. It was just so awful.

[40:49] Um

[40:50] So in the end I was like, "Can you

[40:51] please just let me go? Cuz I just can't

[40:53] I just don't want to do this. I don't

[40:55] want to do it." And I think they

[40:56] thought, "Fine.

[40:58] Um off you go then." I just said, "I'll

[40:59] give you first refusal." Which I I

[41:01] didn't, but they didn't care anyway. Uh

[41:03] they would just probably have to be

[41:04] happy to get rid of me. Um and then it

[41:07] was just so much easier. I basically

[41:08] remortgaged my flat. I took a hundred

[41:11] grand out cuz it had grown in value over

[41:13] is this a small flat in Waterloo over a

[41:15] year and it was the only way I could get

[41:17] any money. I did try the banks, but they

[41:19] didn't want to give me money. So I

[41:21] remortgaged my flat and then I I bought

[41:23] all the studio equipment and I did it

[41:24] for a year. And then I could have gone

[41:27] with a major label then. But I was like,

[41:29] "I'm going to do it myself." Like I'm

[41:31] going to bring all the people that I've

[41:32] met from all the labels and all the

[41:34] times and I'm going to bring in my best

[41:35] crew. Um we're going to do it together.

[41:37] I'm going to pay them and I'm still

[41:39] going to earn way more than I would have

[41:40] ever done if I'd signed to a record

[41:41] label.

[41:42] Um and I only just, you know, Frou Frou

[41:46] was released 25 years ago, I think. Um

[41:49] I've only just seen royalties from that

[41:52] album. Wow.

[41:53] Only just.

[41:54] We've only just recouped. Isn't that

[41:56] crazy? That's how it is.

[41:58] Wow. That is hard to believe. I mean,

[42:00] also that Frou Frou record is incredible

[42:02] and to think that it wasn't enough at

[42:06] the time for this label is is is hard to

[42:08] believe.

[42:09] Um it's one that I really enjoy

[42:11] listening to to this day. And I know a

[42:13] lot of other people keep, you know,

[42:15] finding it again. I mean, the streaming

[42:16] numbers are crazy. I think it's always

[42:18] interesting to look at a streaming

[42:20] service and an album that was released

[42:21] before streaming and see how it does.

[42:24] Cuz some of them just don't fare that

[42:25] well and that's okay.

[42:27] Um but to have an album that is still

[42:29] being streamed that much

[42:31] um from what 25 years ago or so is is

[42:34] really remarkable. Um but it's it's it's

[42:37] amazing now

[42:38] um

[42:39] in 2025 how many artists are waiting to

[42:42] sign longer. They're getting better

[42:43] deals because they have the ability to

[42:45] be independent. I'm curious like if you

[42:47] think you were coming up now, do you

[42:48] think you would have also still chosen

[42:50] that independent path?

[42:52] Oh, 100%. Yeah, I really do not don't

[42:55] sign a major label deal.

[42:57] Like

[42:58] I basically everyone who signs a major

[43:00] label deal

[43:01] after about a year they're like, "How do

[43:03] I get out of this deal?

[43:05] How long have I got? How many more

[43:06] albums do I have to do before I can get

[43:07] out of this deal?" Every artist knows

[43:09] that it's a stepping stone to becoming

[43:11] independent. It's not it's not the place

[43:13] to end up, you know? It's just you've

[43:15] got to make the best deal that you

[43:16] possibly can.

[43:18] Um they're always going to give you the

[43:21] worst deal.

[43:22] Uh even if you think it might be good

[43:23] cuz of the way they worded it. Um

[43:26] And also you don't know what they're

[43:27] doing especially in terms of AI

[43:30] training, giving over licenses to what

[43:32] you we don't know what they're doing.

[43:35] We don't know.

[43:36] Um it's not in our it wasn't in our I

[43:38] mean, I'm not signed to any more, thank

[43:39] goodness, but

[43:40] they at the time I was I was actually

[43:42] like 2 years ago when they still had

[43:44] licenses of my stuff. I was writing

[43:46] letters. I was like, "Do not in any

[43:48] event give my music to AI companies. Do

[43:52] not. Do not. Do not do this. Otherwise

[43:53] I'll take you to court."

[43:55] Um and

[43:56] uh I think I might message that

[43:58] somewhere on a

[44:00] I open letter. I can't remember. I

[44:01] didn't really get any replies

[44:03] um at all. It was very suspiciously

[44:06] quiet. Um but I did hear that backroom

[44:08] deals were being done at major labels

[44:11] with AI companies.

[44:13] And that they were doing discussions.

[44:14] And I I I don't know what they'd done,

[44:16] but I'm glad to not be in it anymore.

[44:18] Yeah, I mean, I I do think it's very

[44:19] interesting about uh record contracts is

[44:21] you sign it and um so they usually have

[44:24] some sort of a clause that leaves the

[44:25] door open for technology in the future

[44:27] that can't be foreseen at this moment.

[44:29] Um which I understand why they do it,

[44:31] but it does leave Yeah. instances like

[44:34] this. I mean, who could have foreseen um

[44:36] generative AI in this form? And that's

[44:38] something that I think about a lot with

[44:40] um

[44:41] legacy artists or artists who are

[44:42] deceased. Um

[44:44] I've reported on some estates um

[44:47] offering the voice rights of a person

[44:50] who's been passed away for like 10, 20

[44:52] years uh to AI companies. And I always

[44:55] wonder like if they could have even

[44:57] foreseen that generative AI would be a

[44:59] thing, how would they feel about this

[45:00] use? And unfortunately, we'll never

[45:02] know. Um but yeah.

[45:04] Well, I think yeah, it's tricky, isn't

[45:05] it? Uh

[45:06] I guess they did it okay. Um but Yeah.

[45:10] If it's the family, then I they'd

[45:11] probably just be like, "Yeah, sure. Of

[45:13] course. I'm dead. Do what you like."

[45:14] Yeah. Um that that would be my that

[45:16] would be my stance. One more thing I

[45:17] wanted to ask you before we start

[45:19] wrapping it up. I I wanted to ask you

[45:21] about the gloves, the MiMU gloves. I

[45:24] absolutely love those. Um they're

[45:26] something that Ariana Grande has used on

[45:28] stage quite a lot. They're really

[45:29] wonderful to see in um

[45:32] everyone's different hands, I guess. Um

[45:34] are you still iterating on that and

[45:36] improving it or do you feel like the

[45:37] product is done as is?

[45:39] No, we're still we're still we're still

[45:41] iterating. Um we have we have a batch

[45:44] that's going to be delivered hopefully

[45:46] before the end of the year uh to like a

[45:48] few hundred people. Um

[45:50] we haven't yet managed to get them on

[45:52] the shelf. Um

[45:54] they're they're not, you know, they're

[45:55] very

[45:56] very good quality, the best in the world

[45:59] uh for creating music. Um and there's

[46:03] they're expensive. They're like two and

[46:04] a half grand a pair. So, you know, it's

[46:07] like buying a it's like buying a

[46:09] computer. But they are they're expensive

[46:11] cuz they're basically like tiny team.

[46:14] We're doing our best to make them, you

[46:16] know, as best we can as cheaply as we

[46:18] can. But we're not like a mass, you

[46:20] know, we're not making millions of these

[46:21] things. So it is still expensive. And a

[46:24] lot of people there's obviously a big

[46:25] barrier. Um

[46:27] and it's a it's a leap to go to, you

[46:29] know,

[46:30] make music gesturally even though it

[46:31] feels totally natural to do it. Um So,

[46:35] we are missing out on the people who the

[46:36] impulse buys cuz it's like, "Oh, I want

[46:38] to do that. I'm going to buy that.

[46:39] Yeah." Yeah, yeah.

[46:40] they they hit buy and then they're going

[46:41] to get it next day and then they're

[46:43] going to love it. But then it's like,

[46:44] "Oh, wait a minute. I'm not going to get

[46:45] it for 3 months or maybe 6 months." Cuz

[46:47] it takes a month. And then they don't

[46:49] buy it. Yeah, our problem really is that

[46:50] we need to have enough capital in

[46:52] advance to buy them to get them on the

[46:54] shelf. And then I think we could see a

[46:56] lot we'll see a lot more people buying

[46:57] them cuz you can't you can't get credit

[46:59] for something if it doesn't exist. Um so

[47:02] once we can create a way where they're

[47:03] on the shelf, then people can pay over

[47:06] time over a couple of years or whatever.

[47:07] It's much more it's easy to stomach. Um

[47:10] but we're just we're a tiny company. We

[47:11] haven't taken investment other than like

[47:13] friends and other musicians tiny bits.

[47:16] Um because we just want to do it our

[47:18] way, you know? Um So, we're hopeful that

[47:22] we can find a way to get it on the

[47:23] shelf. Um

[47:25] because I do think we haven't seen the

[47:27] end of it yet, really. Even though it's

[47:29] been really hard. We we'd have a big

[47:31] chat the other day. Um but there's

[47:32] nothing else like them, you know? I know

[47:34] you can do it with the computer. There

[47:36] are people you've seen videos of people

[47:37] using touch designer or whatever and

[47:38] just kind of you know, using the IR the

[47:41] camera and creating gestures in doing it

[47:43] in front of the computer. We know you

[47:44] can do that. You can do that with us,

[47:46] too, with the glove software. But

[47:48] there's nothing like being away from

[47:49] from the computer,

[47:51] being in the garden and making music

[47:54] with the trees. Uh you've got a I've got

[47:56] a wireless microphone. I've got my inner

[47:57] headset. And I'm just out in the garden

[48:00] making music with whatever I want to

[48:02] make it with. Or I can go into the

[48:03] studio or I can go into the

[48:05] by the piano or on stage. And it's just

[48:07] that freedom um of being able to change

[48:10] your music in real time

[48:12] in real whatever space and not be in

[48:14] front of a camera. Uh this has been such

[48:16] an interesting discussion. I'm going to

[48:17] end it off with some quick like

[48:19] rapid-fire questions and then we'll do

[48:22] our our playlist. I might not get

[48:24] rapid-fire answers, but I'll do my best.

[48:26] Okay, okay. Just a couple words per

[48:27] answer and we'll see we'll see how it

[48:29] goes. Okay. Um Not myself, yeah.

[48:31] Who is an artist that you view as an

[48:33] innovator? Uh Tim Exile.

[48:35] Okay.

[48:36] A song from Speak for Yourself that you

[48:38] look back on with great pride.

[48:41] Uh Hide and Seek.

[48:44] Yeah. The coolest way that someone has

[48:46] paid homage to your work. I don't know.

[48:49] I really liked hearing like kazoo

[48:51] version of Hide and Seek.

[48:53] Um

[48:54] I love that.

[48:55] I mean, no. Ariana Grande.

[48:58] When she did uh Goodnight N Go.

[49:00] Uh and she like I love it. I love that

[49:03] she did that. And I went I went on tour

[49:04] and I did my version of her version of

[49:06] my song.

[49:07] Um and no, I really like her when she

[49:10] did that. It's she's so generous. She

[49:12] really just has continuously

[49:14] shared the love

[49:16] uh and always supported me.

[49:19] Uh and she's just like enormous. And she

[49:22] just has such integrity. All the things

[49:24] she's been through. I thought I think

[49:25] she's so talented. I really I know I'm

[49:28] going to work we're all going to

[49:28] actually do something together one day.

[49:30] One day. We both said it. It's just

[49:32] we've got to find the right thing at the

[49:34] right time so So we can really enjoy it

[49:36] and it's not just something like. It's

[49:38] got to be but you know at the same time

[49:40] it's like you don't want to build it up

[49:41] so much and then

[49:42] we never do it cuz it's like it's going

[49:44] to be the perfect time.

[49:45] But then I really really want to work

[49:46] with Ariana. I think

[49:48] she's great. Yeah, she is.

[49:51] What's the best film TV use of your song

[49:53] Hide and Seek? I mean obviously The OC.

[49:56] Um that cuz that was the first one. But

[49:58] um I think the the most intriguing one

[50:01] was the Saturday Night Live skit and

[50:03] because they didn't ask permission.

[50:05] Um they just they just did it. And there

[50:08] are quite a lot of people seen The OC

[50:10] but way more people saw that skit. And

[50:13] then well didn't even know where it came

[50:15] you know did they know where it came

[50:16] from I suppose but didn't didn't know

[50:17] about the song it was like too many

[50:18] steps removed at that point. And this

[50:20] was one it was one it ended up being one

[50:21] of the first memes uh on the internet.

[50:24] Uh people just did what you say and just

[50:27] all different kind like Simpsons version

[50:30] all all different versions of it. Um and

[50:33] I don't think it was an official

[50:34] Simpsons one. But people just you know

[50:35] edit stuff up.

[50:37] Um and it was amazing. It was amazing to

[50:39] see but that was before monetization

[50:41] sadly on YouTube.

[50:42] So there were like billions and billions

[50:44] of uh bits of this song. But I think it

[50:46] like goes under the radar of

[50:48] monetization cuz it's not quite 30

[50:49] seconds but otherwise it'd be like I'd

[50:51] be like totally winning it.

[50:53] Um yes.

[50:55] Ah that really is too bad that it was

[50:57] just a little early on the YouTube thing

[50:58] but um I think that song still has a lot

[51:01] of legs online. There are still people

[51:03] using it all the time.

[51:04] Um who is an artist who counts Well

[51:08] actually you kind of answered this.

[51:09] Maybe Ariana. Um What let me ask the

[51:11] question then. Um an artist who counts

[51:13] you as an inspiration that you enjoy

[51:15] listening to yourself.

[51:18] Well yeah, Ariana. Um

[51:21] I don't know. I mean I heard I I really

[51:23] heard this person's music recently

[51:24] called Blawan. Not Blawan sorry uh

[51:26] Datacluster. Um and he was like totally

[51:29] excited. So and I really like his music.

[51:31] Well I discover lots of people that that

[51:33] I'm like wow I love this person's music

[51:35] and then I think like there's no way

[51:37] they're going to know me cuz I'm just

[51:37] not cool enough. And then like no I

[51:39] really have to like that I'm like their

[51:41] guilty pleasure. Um which I find a

[51:43] little bit like huh.

[51:44] How can I be a guilty pleasure I mean

[51:45] I'm not cool enough. Um but I'm very

[51:48] lucky. I I seem to find fans in all

[51:51] kinds of like unexpected places.

[51:54] It like you know extreme heavy metal

[51:56] rock bands or noise artists or

[51:58] hip hop or trap or rap or you know just

[52:03] Yeah just that it's just it's mad how

[52:06] cross genre um the music gets. Uh really

[52:10] love that. I feel I feel so lucky really

[52:12] to have

[52:14] Yeah, know people from all over and just

[52:17] feel like it's a possibility really

[52:19] hopefully to work with anyone. If I if I

[52:21] really wanted to maybe I couldn't I

[52:23] don't know.

[52:24] Um but there's so many people I want to

[52:25] work with. I just I don't want to sit in

[52:28] front of the computer and write music in

[52:30] the way that I have done over the last

[52:31] 30 years just like solitary mixing and

[52:34] just moving bits of audio around. I have

[52:36] to find another way and I know that

[52:37] obviously there are other ways like you

[52:38] could do modular you can you can work

[52:40] with a band. Um but I've just become a

[52:43] slave of my own technique really. And

[52:45] that's why I really want to develop the

[52:46] live system with the Mi Mu gloves with

[52:48] generative AI of of motion but under an

[52:52] acceptable level of AI generative work

[52:55] so that I can conjure lyrics in real

[52:58] time with my own brain in real time. Um

[53:01] but also maybe with the the temperature

[53:04] or how many people in the room changes

[53:06] the way that the melody moves around or

[53:09] that the how fast the chords move

[53:11] depending on how close they are to me or

[53:12] I just I want to create music in real

[53:14] time in a very different way than I ever

[53:16] have and that's really what I'll spend

[53:17] my time on. Exciting. Well um okay so

[53:20] the final thing of our interview is the

[53:23] playlist part. So we always ask everyone

[53:25] on on the record to help make me a

[53:27] playlist. What is a song you can no

[53:29] longer gatekeep? We'll just start there.

[53:31] What's the song that you're loving right

[53:32] now that you want more people to know

[53:34] about? I really do love uh this album by

[53:38] Blawan

[53:39] called Sick Elixir. Uh Sick Elixir I

[53:42] nearly had a car crash cuz I was driving

[53:44] and I've been waiting to hear it in the

[53:45] car so I could hear it not just on like

[53:47] my headphones or you know wherever. I

[53:48] wanted to hear it like loud and so I

[53:51] played it and I had I had a car journey

[53:53] enough time. And oh my I knew I just

[53:56] couldn't believe how good it was. It

[53:57] just I was like I was swearing. I was

[53:59] like I'm if somebody looked in the car

[54:01] they would be like what the hell's that

[54:02] one doing? I was like going oh my Thank

[54:05] god this is amazing. I just like

[54:07] I couldn't believe how good it was I was

[54:08] just laughing just I was like a

[54:11] kind of being possessed. Um so the whole

[54:13] album is absolutely amazing but if I I

[54:15] can't really choose one cuz I I liked

[54:17] all of them. Um but I don't know I like

[54:19] it there's one called dot dot dot Nos.

[54:22] What is a favorite throwback of yours?

[54:24] So a song over 10 years old. When I was

[54:26] like 17 in Camden when I was you know

[54:30] starting out. And there was this band

[54:32] called Acacia. Um and one half of it was

[54:35] Guy Sigsworth who obviously we turned

[54:37] into being Frou Frou. But the album that

[54:40] um that they made Acacia um is so good

[54:43] and I think the one of the tracks that I

[54:45] love the most was called Maddening

[54:47] Shroud. So

[54:49] I'd check that out. It's from the 90s so

[54:52] long ago. I'll have to check that one

[54:54] out. And last but not least what is a

[54:57] guilty pleasure for you? Um well I just

[54:59] it feels a bit weird to say it cuz it's

[55:01] not really like a guilty pleasure but it

[55:02] kind of is. And I talked about this

[55:04] person earlier this this uh artist

[55:06] called Datacluster. And I found them on

[55:09] uh you know on this random playlist. And

[55:12] I was I was I was a little bit thinking

[55:14] that they might have been AI generative

[55:16] between some artists that I love. So the

[55:18] guilty feeling is like but I love Max

[55:21] Cooper and I love Jon Hopkins and

[55:23] they're like my I like know them. Um and

[55:26] there's such echoes of their music in

[55:28] this that I feel

[55:30] slightly uncomfortable about cuz it is

[55:32] so to the T. Uh but the melodies and

[55:34] it's not it's not their music at all.

[55:36] It's just Datacluster um

[55:39] absolutely idolizes these artists and

[55:42] has studied them meticulously to the

[55:44] point where he just knows how to get

[55:45] those sounds. I just would not have the

[55:48] patience to do that. Um I'm just like oh

[55:49] it I'm just going to make it sound

[55:50] like this. Um

[55:52] so I guess my guilty pleasure in a way

[55:54] is that cuz I would like to talk to Jon

[55:56] and and Max and see how they feel. Maybe

[55:57] they're like that doesn't sound anything

[55:59] like me how how and why would you think

[56:00] my sound is like me? I'm like oh sorry

[56:02] huh. Um so the one that I found on this

[56:05] playlist I'm going to try and find the

[56:06] name of it. Circa 13. It had under a

[56:09] thousand plays on Spotify. Um

[56:12] and he's got 899 monthly listeners. But

[56:15] I was like

[56:16] this is just great.

[56:17] And I really liked it and I was

[56:19] listening to it a lot and I got in touch

[56:20] with him. I think he lives in LA. Might

[56:22] meet up with him when I go to NAMM in

[56:24] January.

[56:25] Um but yeah Datacluster and the track

[56:27] that I heard was called Circa 13 but it

[56:29] comes off his debut album

[56:32] um I believe which is called

[56:35] Coalescence.

[56:36] Awesome.

[56:37] Yeah. Okay I'll check it out. It's

[56:38] really nice.

[56:39] Well thank you so much Imogen Heap for

[56:41] coming to the show. This has been so

[56:42] much fun. I love talking AI with you and

[56:44] you'll have to come back soon. Thank

[56:46] you.

[56:47] Thank you. My pleasure.

[56:49] All right another big thank you to

[56:50] Imogen Heap for coming on the show today

[56:52] and sharing her insights with us. It's

[56:54] really good to get a pulse on how an

[56:55] artist is feeling about AI right now

[56:57] especially one who is still very hopeful

[56:59] about the future. Up next we're going to

[57:01] be diving into our charts roundup where

[57:03] we'll highlight this week's biggest

[57:05] movers and shakers. Here is the top 10

[57:07] of the Hot 100 chart for the week of

[57:09] November 22nd.

[57:11] Rising to number 10 this week is Back to

[57:13] Friends by Somber.

[57:17] Number nine is I Got Better by Morgan

[57:19] Wallen.

[57:22] Number eight is Folded by Kehlani.

[57:28] Number seven this week is Mutt by Leon

[57:30] Thomas.

[57:34] Six this week is Daisies by Justin

[57:36] Bieber.

[57:37] [music]

[57:39] Opalite by Taylor Swift comes in at

[57:42] number five.

[57:45] Man I Need by Olivia Dean rises [music]

[57:47] to number four.

[57:50] Number three again this week is Ordinary

[57:53] by Alex Warren.

[57:54] [music]

[57:57] Golden by Huntrix comes in at number two

[57:59] again this week.

[58:00] [music]

[58:02] And finally

[58:03] the number one song on the Billboard Hot

[58:05] 100 chart for the week of November 22nd

[58:07] [music] for its sixth week at number one

[58:10] is The Ballad of Ophelia by Taylor

[58:12] Swift. Thanks for tuning in to this

[58:14] week's episode of On the Record and

[58:15] another special thank you to my guest

[58:17] Imogen Heap for coming on the show. And

[58:19] [music] if you'd like today's show

[58:20] please consider hitting us with a rating

[58:22] a follow a thumbs up. All those things

[58:25] really help a show like ours to grow and

[58:27] to reach new people. Again I'm your host

[58:29] Kristin Robinson and tune in next week

[58:31] for another peek behind the curtain of

[58:32] the music business. I'll see you then.

[58:41] [music]