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- Chipmunks to Gorillaz: Why AI will enable a new wave of virtual artists
Chipmunks to Gorillaz: Why AI will enable a new wave of virtual artists
Virtual bands had already “been a thing” for nearly half a century by the time Gorillaz released Clint Eastwood in 2001. AI tools will enable a new wave of virtual artists.
“...in 1969, year of Abbey Road and "Everyday People," the Archies' "Sugar, Sugar" was the top song in both the U.S. and U.K. Written by 16-year-old Andy Kim and Brill Building mainstay Jeff Barry, the song was originally sent to live-action TV band the Monkees. They passed, and so it went to an animated TV band: the Archies, a group composed of the kids from the Archie comics.”
Alvin and the Chipmunks were probably the first, but it was when the Archies strapped on their animated guitars about a decade later that the world embraced this new idea: the virtual band, or in those days, cartoon bands. So, when Gorillaz released Clint Eastwood in 2001, the virtual artist had already “been a thing” for nearly half a century.
Since 2001, many other music artists have ventured into the virtual waters.
Here are a few notable examples:
Hatsune Miku, a Japanese virtual artist and mascot for vocal synthesizer software, has 1.5 million monthly listeners on Spotify. (Link)
K/DA a virtual K-pop group has over 3 million monthly listeners on Spotify. (Fun Fact: two of the voices behind this four-piece K-pop girl group are American singers — Madison Beer and Jaira Burns). (Link)
Polar, a virtual artist who rose to fame on TikTok, has built an audience of over 1.7 million followers on the platform. (Link)
Miquela, originally a virtual Instagram influencer, has over 175,000 monthly listeners and has collaborated with big brands like Pac-Sun, Channel, Calvin Klein, and Prada. (Link)
FN Meka, a virtual rap artist, was signed to Capitol Records in 2022 but was quickly dropped after controversy around racial stereotyping and its use of the n-word in songs. (FN Meka is a black virtual artist that was created by white and Asian cofounders). (Link)
Mave, a new K-pop girl group who just dropped their debut single on January 25th and already has over 200,000 monthly listeners on Spotify. (Link)
If you are interested in checking out more virtual artists, Last.fm maintains a long list of them but to be honest, a few of the descriptions sound more like studio music artists with stage names.
Generative AI enters the scene.
The recent developments in generative AI tools for text, images, and increasingly for audio and music indicate we’re going to see more virtual artists — probably a lot more.
People hold on to a romanticized idea of what a rock star is, what a pop star is, and the feelings around being absolutely enamored with a band.
I do too! Just yesterday I teared up watching a video of this girl getting pulled on stage to play “Monkey Wrench” with the Foo Fighters. She’ll remember that day forever. I don’t even really like the Foo Fighters, but I can imagine how she felt.
Some people are afraid we will lose that magic if AI becomes mainstream in music and the human element is diminished.
But I think AI tools will release new and imaginative ideas from people's brains. Ideas that were locked away because it was too hard for the average creator to assemble a skilled team of people to do all the things that need doing when creating something as complex as a virtual artist and the world in which they live. Today, the creation of a multi-media music artist with a backstory, graphics, video, ad copy, and of course, music can be accomplished by one imaginative individual with a few AI tools and a laptop … hell, it can be done on a phone!
I think people will fall in love with those creations too. I was smitten over Gorillaz, and that was before I knew anything about the people behind the band, which turned out to be the guy from the “woohoo song” and one of the guys that made Tank Girl.
Lately, I’ve noticed more people talking about growing a Social Media following while maintaining their anonymity.
“Make Millions on Youtube without showing your face”
“Grow a huge audience on Twitter with an anonymous “Small Business Advice” account”
People seem to be catching on to the fact that fame, even internet fame (or especially internet fame) comes with a lot of downsides.
They’re looking for ways to get the benefits without the drawbacks. High-profile cases like that of Britney Spears and Kanye West (Ye) show lives that seem to have been ripped apart by fame (or in Ye’s case, his mouth, but let’s be honest, fame supported his mountain of an ego).
We also see the rejection of fame by celebrities or at least a tumultuous relationship with it. Dave Chappelle famously quit his successful TV show in the middle of production. Shia Lebeouf wore a paper bag over his head at a red carpet event that said, “I am not famous anymore”
With the zeitgeist at play, a generation suddenly equipped with AI superpowers, and the metaverse lurking about, the emergence of Virtual Artists as commonplace in music seems obvious.
This returns us to a recurring theme in this newsletter: AI will force us to redefine art and what it means to be creative.
I am taking submissions for the new definitions.
📍 Random Curated Links
How Much Humanity Will AI-Generated Songs Need to Be Copyrightable? Billboard Guest Column (Link)
10 controversial predictions for the music business in 2023. (Link)
Mave: AI-Generated K-pop girl group (mentioned in the op-ed above) debut on January 25 and already has 200,000 monthly listeners on Spotify (Link)
MusicLM: Generating Music From Text. This is Google’s most recent and impressive contribution to AI-Generated Music:
Noise2Music: a series of diffusion models is trained to generate high-quality 30-second music clips from text prompts (Link)
SingSong: ”a system which generates instrumental music to accompany input vocals.”
AudioLDM: a Text-to-Audio (TTA) system that can generate sound, speech, and music from text descriptions.
📍 Tweets to dive into
woo everybody cheer on lucidrains let's gooooo
👏👏👏👏
MuLan is the key to MusicLM, it was trained on 44million songs— dadabots (@dadabots)
1:48 PM • Jan 28, 2023
Models such as Stable Diffusion are trained on copyrighted, trademarked, private, and sensitive images.
Yet, our new paper shows that diffusion models memorize images from their training data and emit them at generation time.
Paper: arxiv.org/abs/2301.13188
👇[1/9]
— Eric Wallace (@Eric_Wallace_)
3:52 PM • Jan 31, 2023
Copyright lawsuits against AI companies are going to get interesting. 🍿🍿
Outcomes could shape how new tools function. Fascinating.
Here's a great breakdown by @LegalEagle of the current landscape and things to come.
— Chris Egan (@TheChrisEgan)
9:25 PM • Jan 26, 2023
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