AI for Music – Napster redux?
Music has always been a cut-throat business across the globe. The author decodes the key to success in the music industry, which will be captured by new-age technology such as AI
Music has always been a funny business.
In the late 19th and early 20th Century, Sheet music (music transcribed on paper) was the primary means of disseminating new music to the public. Amateur musicians would buy Sheet music at music stores (or mail-order catalogs) to play popular songs at home. At the height of its popularity (1910s), 30 million copies of sheet music were sold annually in the US, accounting for majority of the music sales. If you wanted to listen to music at home you had to first raise an amateur musician.
1920s welcomed the phonograph and vinyl records into the living room … and killed the Sheet music business overnight. In case you are wondering, the number of amateur/home musicians actually went up! Music inspired people at scale. A delightful contradiction that we will come back to in a bit.
This wasn’t the first time an industry associated with music got wiped out - and it certainly wasn’t the last.
US Recorded Music revenues went from about USD 14 billion in 2000 to about USD 7 billion in 2010 because a couple of 19 year olds decided to start a peer-to-peer file sharing network. At its peak Napster had 80 million users. The revenue went back up to USD 14 billion only ten years later in 2021 - and the industry looked substantially different. Just to put things in perspective, CD sales which accounted for 92 per cent of USD 14 billion in 2000 accounted for a mere 3 per cent in 2021 - a company out of Sweden decided digital streaming was the future. Spotify (USD 12.6 billion revenue and yet not profitable) is now 30 per cent of the streaming market representing over 80 per cent of the US Music industry.
Image source: RIAA - https://www.riaa.com/u-s-sales-database/
‘I’ve heard there was a secret chord’… but who wrote the song?
It’s not just the dissemination of music that is funny, it’s the creation as well. “Hound Dog” and several other top Elvis hits were originally recorded by African-American artists. Before you (rightfully?) scream cultural appropriation, Elvis also helped fuse R&B, pop and country music to give us Rock’n’Roll. Freddy Mercury knew what’s up - ‘The show must go on’.
‘Bittersweet Symphony’, The Verve’s biggest hit didn’t earn the band a single penny for 22yrs (till 2019). All of the royalties went to Rolling Stones on account of 4 measly bars The Verve had sampled from the Stones’ hit ‘The Last Time’. This innocent choice costed the band an estimated 5M$… and a Grammy nomination! The ironic part? ‘The Last Time’ itself was a loose cover of a gospel song performed by Staple Singers.
Once again, lets zoom to the present. ‘Heart on My Sleeve’ an AI generated song with >8M views on TikTok was pulled off the platform by Universal Music Group. The reason? The song was generated based on Drake and The Weeknd’s catalog.
Grimes chose to take a more libertarian stand - encouraging fans to generate AI songs using her catalog and samples for a 50 per cent royalty share. #delegationgoals.
Which brings us to… AI and music. The answer is (already) blowing in the wind.
‘The Man comes around’… Record Labels and copyrights
Before we get to AI, let’s back up a bit and follow the money. Record Labels can make between 70-90% of the revenues off a song - read that again. What they can’t make in streaming revenues, they try to make off copyright claims. There is an entire ecosystem in place for them to quickly issue a notice for everything from a cover performed in a noisy bar to background music for your cat’s TikTok. Some contracts allow them to claim against the very artist who wrote the song - Hello Taylor Swift.
This is an expensive affair for your average Creator/Influencer who needs background (and foreground) music to keep your ADHD mind from scrolling to the next fix. This is also a large cost for Brands who overlay music on their ads (that you conveniently skip on YouTube). Very few things can rattle a Social Media CEO like a copyright lawsuit (and an occasional Senate hearing).
Epidemic (another Swedish company!) helped democratise ‘Music-As-A-Service’ for these use-cases by getting tons of artists to create music for outright purchase by the platform. Creators can now buy music at a fraction of the cost they would’ve paid the Label.
But AI music is cheaper than human music.
AI for Music - or is it Music for AI?
AI is magical - but it doesn’t generate magic from thin air. It needs data. A lot of it. Fortunately the music catalog is infinite. Unfortunately its behind a copyright, rendering the catalog useless!
Enter entrepreneurs and innovation.
While MuseNet (OpenAI) and Magenta (Google) are trained on very large sets of musical compositions (and hence have a dubious legal stand) several companies are taking alternate, novel approaches.
One approach to build AI for Music involves buying samples from Artists in bulk to train AI models. Some even give credit to the artists whose samples were used to generate a specific track. The AI model and architecture used vary significantly - and so does the production quality. Relying on underlying patterns in music (scale, tempo etc) they are able to create coherent pieces of music with data sets that are orders of magnitude smaller than ‘Big-Tech’ versions.
And the music is surprisingly good (already!). Some of them are so good they have replaced my “ambient lo-fi music for work” playlist on Spotify.
The jury is out on what model will win. MusicLM (ChatGPT for music) from Google seems to have made significant improvements in quality - and large models have a tendency to breakaway on quality obliterating small-scale efforts. The product is still in trial phase but I urge the music enthusiast to get on the waitlist.
So… genius musicophiles and big-tech are hell bent on creating a composer to end all composers - but who’s going to make the moolah?
‘Money for nothin’’… but the very best
Clearly, at Matrix, we like the intersection of AI and content/media. We’ve already made two investments. One of them, Murf.ai, is a versatile AI voice generator - AI enabled real people voices. It’s literally as simple as typing text into a box.
For music I believe true value will be created by a company that not just masters the quality of music, but also caters to the right workflow depth. The workflow that wins will build deep capability for its intended customer - ensuring the tools they use for creation and distribution are seamlessly integrated. This cannot be an “also-use” tool - it has to be core to their productivity and work. Outlining some potential case below.
- Musicians/producers - The only production tool/suite you’ll ever need
- Creators - Seamless, fully integrated music programming for your videos
- Social Media - An endless, free library for your creators in a click
- Gaming - Music/audio designed specifically to maximise the game experience
- Users - A full stack Spotify replacement (plus Garageband like features?)
- While it’s too early to take a call on what AI models will succeed, specific use-cases and integrated workflows can capturing real value imho.
‘This is the end beautiful friend’… Not really
Before we start quoting Jim Morrison and call it the end for musicians, I’d like to point back to what happened when the phonograph became mainstay. More music = more artists.
Musicians will have infinite sounds and production capabilities to translate their vision into reality. Noobs like you and me will be able to create songs in 7/8 time with complex song structures with a few prompts. Record labels permitting, I’d love to prompt “A Bob Dylan album sung by Eddie Vedder”.
Let me leave you with one of my favourite quotes.
“Art is how we decorate space, music is how we decorate time.” – Jean-Michel Basquiat
Its time to start decorating.
Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house
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