If you think 100,000 songs a day hitting the market is a big number, “you have no idea what’s coming next,” says Alex Mitchellfounder/CEO of Boomy, a music creation platform that allows you to compose an instrumental in one click.
Boomy is one of many so-called “generative artificial intelligence” music companies – including Soundful, BandLab’s SongStarter and Authentic Artists – founded to democratize songwriting and production even more than the synthesizer does. did in the 1970s, the drum machine in the 80s and 90s, digital audio workstations in the 2000s, and sample and beat libraries in the 2010s.
In each of these cases, however, trained musicians had to use this technology in order to produce songs. The selling point of generative AI is that no musical knowledge or training is required. Anyone can potentially create a hit song using computers that evolve with every artificially produced guitar hit or drumbeat.
Unsurprisingly, the technological breakthrough has also generated anxiety among professional musicians, producers, engineers and others in the recorded music industry who fear that their livelihoods are potentially at risk.
“In our search for the next best technology, we don’t think enough about the impact [generative AI] could have on real people,” says Abe Batshon, CEO of BeatStars, a subscription-based platform that licenses beats. “Are we really helping musicians create, or are we just cutting jobs for producers?”
Not so, say entrepreneurs working in the start-up business. From their perspective, generative AI tools are just the next step in the long legacy of technology shaping how music is created and recorded.
“When the drum machine came out, the drummers were afraid it would take away their jobs,” says El All DayFounder/CEO of Soundful, another AI-powered music-generating app that’s been tested by hit makers like Caroline Pennell, Madison Love and Matthew But at a recent songwriting camp in Los Angeles. “But then they saw what Prince and others were able to create with it.”
El All says the music Soundful can generate instantly, based on user-defined parameters like beats per minute or genre, is simply meant to be a “starting point” for songwriters to create songs. “The human element,” he says, “will never be replaced.”
BandLab CEO Meng Ru Kuok says having tools to boost song creation makes a huge difference for young music creators, who so far seem to be the biggest adopters of this technology. Meng says his AI-powered SongStarter tool, which generates a simple music loop that creators can create a song on, makes new BandLab users “80% more likely to share their music rather than write from zero”. (Billboard and BandLab collaborated on Bringing BandLab to Billboard, a portal that spotlights emerging artists.)
Other applications for generative AI include creating “entirely new listening formats”, as the co-founder/CEO of Endel Oleg Stavitsky said. This includes custom music for games, wellness, and soundtracks. Lifescore modulates human-created scores in real time, which can reflect how well a player is doing in a video game, for example; Endel generates soundscapes, based on user biometrics, to aid sleep, concentration, or other states (Lifescore also has a similar wellness app); and Tuney targets creators who need dynamic, personalized background music for videos or podcasts, but don’t have a licensing budget.
These entrepreneurs claim that generative AI will help grow the “creator economy,” which is already worth more than $100 billion, according to Influencer Marketing Hub. “We’re seeing the lines between creator and consumer, audience and performer blurring,” says Mitchell. “It’s a new creative class.”
In the future, both Mitchell and El All seem to envision that everyone can have the ability to create songs, much like the average iPhone user already has the ability to capture high-quality photos or videos at home. stolen. That doesn’t mean everyone will be a professional, but it could become an equally common hobby.
The public’s fascination and fear of generative AI has taken a new step this year with the introduction of DALL-E 2, a generator that instantly creates images based on text input and with a startling level of precision.
Musician Holly Herndon, who has used AI tools in his songwriting and creative direction for years, says that over the next decade, generating a great song will be as easy as generating an image. “The entertainment industries that we know are going to change dramatically when media is so easy and abundant,” she says. “The impact is going to be dramatic and very foreign to what we are used to.”
McBoucher, a creative technologist and co-creator of the non-fungible token project WarNymph with his sister Grimes, agrees. “We will all become creators and be able to create anything.”
If these predictions come true, the music industry, which is already struggling with oversaturation, will have to recalibrate. Instead of focusing on consumption and intellectual property, more companies could turn to artist services and the development of tools that make it easier to create songs – similar to Downtown Music Holdings’ decision to sell its catalog of 145,000 songs over the past two years and focus on meeting the needs of indie talent.
Big music companies are also investing and building relationships with AI startups. Hipgnosis, Reservoir, Concord and Primary Wave are among those that have worked with stem-splitting company AI Audioshake, while Warner Music Group has invested in Boomy, Authentic Artists and Lifescore.
The advancement of AI-generated music has naturally sparked a debate about its ethical and legal use. Currently, the US Copyright Office will not register a work created solely by AI, but it will register works created with human input. However, what constitutes this contribution has not yet been clearly defined.
The answers to these questions are being worked out in court. In 2019, industry leader Open AI posted a comment to the U.S. Patent and Trademark Office, claiming that using copyrighted material for training an AI program should be considered fair use, although many copyright holders and some other AI companies disagree.
Now, one of Open AI’s projects, which was done in conjunction with Microsoft and Github, is fighting a class action lawsuit over a similar issue. Copilot, which is an AI designed to generate computer code, has been accused of often reproducing copyrighted code because it was trained on billions of lines of copyrighted material created by human developers.
Executives interviewed for this story say they hire musicians to create training materials for their programs and don’t touch copyrighted songs.
“I don’t think songwriters and producers talk about [AI] enough,” says the music advocate Karl Fowlkes. “This kind of thing looks like a dark, imminent thing coming our way, and we have to sort out the legal issues.”
Fowlkes says the biggest challenge for AI-generated music will come when these tools start creating songs that mimic specific musicians, just as DALL-E 2 can generate images clearly inspired by copyrighted works. author of talents like Andy Warhol or Jean-Michel Basquiat.
Mitchell says Boomy could cross that threshold next year. “I don’t think it would be crazy to say that if we can line up the right framework to pay the rights [to copyrighted music], to see something of us earlier than people think on that front,” he says. “We’re looking at what it will take to produce at the level of DALL-E 2 for music.”
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