Writing and playing a song once required some level of musical training, and recording was a technically complex process involving expensive equipment. Today, thanks to the advancement of artificial intelligence, a growing number of companies allow anyone in the world to skip this process and create a new song with the click of a button.
This is an exciting prospect in Silicon Valley. “It's very easy to invest in these kinds of things right now,” Lifescore co-founder and CTO Tom Gruber he says dryly, “because everyone thinks genAI is going to change the whole world and there won't be any human creators left.” (Lifescore offers “artificial intelligence-powered music creation in the service of artists and rights holders.”)
Recently, however, some executives in the AI music space have been asking: How much do average users actually do I want create their own songs?
“For whatever reason, you just don't see an extreme level of adoption of these products among everyday consumers yet,” notes one founder of an AI music company who spoke on condition of anonymity. “Where are the 80 to 100 million users on this stuff?”
“My belief is that the text-to-music platform won't have decent retention rates yet,” he says Ed Newton-Rex, who founded the AI music production company Jukedeck and then worked at Stability AI. “It's a magical moment when you first try a music production platform that works well. Then most people don't really use it.” So far, the most popular use for song creation tools seems to be creating meme songs.
While there are hundreds of companies working on genAI music technology, the two that have generated the most headlines this year are Suno and Udio. The first recently was announced that 10 million users have tried it in eight months, while the latter he said Bloomberg that 600,000 people tried the song generation product in the first two weeks. Neither company said how many of those testers became regular users. Compare this to ChatGPT, which was is appreciated to gain 100 million weekly users within two months. (Although there is chatter that growth is leveling off there too.)
It's early days for many of these AI songwriting companies, of course. That said, executives working at the intersection of music and artificial intelligence continue to wonder: How can tools that churn out new tracks on command help users?
“You can end up with a very good technology that doesn't really solve a real problem,” Gruber notes. “If I want something that sounds like a folk song and has a clever lyric, I already have all I can eat on Spotify, right? There is no shortage there.”
Part of the reason for the explosion of ChatGPT, according to Antony Demekhin, co-founder of Tuney, is that it “clearly solves a bunch of problems — it can edit text for you, help you code.” (Tuney is developing “ethical AI music for creative media.”) Still, a recent multi-country survey from the Reuters Institute noted that for ChatGPT, “frequent use is rare… Many of those who say they've used genetic AI have only used it once or twice.”
In the subset of survey respondents who said they have used genetic AI to “create media,” “audio creation” was the ninth most popular task, with 3% of people doing it. Reuters Institute research shows that AI generation tools are most often used for email writing, creative writing and coding.
“How many 'non-musicians' really wanted to create music before?” he asks Michael “MJ” Jacob, founder of Lemonaide, a company that develops “creative artificial intelligence for musicians” (about 10,000 users). “I don't think it's true to say 'everyone,' as tempting as it is.”
Another factor that could hinder AI audio creation, according to Dia El All, founder and CEO of Soundful, is the number of competing companies and the difficulty of judging the quality of their output. (Soundful, which bills itself as “the premier AI Music Studio for creators,” has a user count “in the seven figures,” says El All.) Mike Karenfounder of the company and publishing company Artist Partner Group, believes many people will try an AI song generator “that's not that good, have a bad experience and won't come back for six months or a year.”
The uncertain regulatory climate almost certainly hinders the spread of AI songwriting tools. Currently, in the US, there are open questions about the copyrightability of AI-generated tracks, potentially limiting their commercial value.
Additionally, these programs must be trained on large musical datasets to produce reliable tracks. While many prominent tech companies believe they should be allowed to undertake this process at will, labels and publishers argue that licensing agreements are needed.
In other areas, AI companies have already been sued for training on news articles and images without permission. Until the rules around education are clarified, through court cases or regulations, “corporate brands don't want any of the risk” of opening themselves up to potential litigation, he explains. Chris WaltzCEO and co-founder of Lifescore.
Music AI leaders also believe that their song production technologies still suffer from a bad reputation. “I think the tech-lash and the stigma is really unexpected and very powerful,” says the company's founder.
CEO OpenAI Sam Altman recently was discussed this in The All-in Podcast: “Let's say we paid 10,000 musicians to create a bunch of music just to make a great training set where the music model could learn all about song structure and what makes a good catchy beat,” he said. “I was kind of putting it as a thought experiment to the musicians, and they say, 'Well, I can't object to it on any principled basis at that point. And yet, there's still something I don't like about it.” (So far, OpenAI has moved away from the music industry.)
While the average citizen's interest in AI song creation remains unproven, many producers and aspiring artists, who already make music on a daily basis, would like to try products that spark ideas or streamline their workflow. That's still a large user base — “the total global addressable market for digital music producers alone is approximately 66 million,” according to Splice's CEO Kakul Srivastava“and that continues to grow at a fairly rapid rate” — though not the entire population of the planet.
“We were all talking about how artists get ripped off, because this is a dramatic story,” says Demekin. “For me, what's more likely is these tools just integrate into the existing ecosystem and people start using it as a source for stuff like Splice,” which provides artists and producers with sample packs full of musical building blocks.
Caren believes that music AI tools will be used first by musicians, then by creators looking for sound in their videos, and then by fans and “music lovers” who want to express their appreciation for their favorite artists by making something.
“The question of how much can it penetrate people who aren't serious music fans?” he asks. “I do not know.”
from our partners at https://www.billboard.com/pro/ai-song-generation-tools-slow-adoption/