Rise of the robot music industry

Rise of the robot music industry

AI is transforming music streaming, talent spotting, promotion and even composition

December 2, 2016 by: Nic Fildes, Telecoms Correspondent

Robotic is not an adjective that many musicians would want applied to their songs but the industry has been fast to embrace data analytics and artificial intelligence to help tailor its services to the increasingly fickle listener.

Algorithms are seeping into the music business to help with talent spotting, promotion and even composition in an industry that has been historically resistant to change and was one of the first to feel the effects of “disruption” through piracy and music sharing.

Streaming services have already ushered in an era of “hyper personalisation” for music lovers. Spotify’s Discover Weekly playlist, launched in July 2015, had racked up 40m listeners around the world and 5bn track streams by May this year, according to a report from the BPI prepared by Music Ally. These playlists monitor what a person is listening to, and cross-references that data with other users with similar tastes to recommend new songs and artists.

Apple Music has opted to use human curators such as Zane Lowe, the radio DJ, for its playlists, but Spotify has doubled down on its robotic recommenders with new services such as Release Radar and the Daily Mix to tempt its subscribers down different paths.

Yet discovery is only the equivalent of a debut album for streaming services, and can be a blunt tool. Users of Spotify Discover complain that it is hit and miss — often suggesting the same artists and songs repeatedly, and failing to adapt to the often random whims of the listener.

The industry is now hoping that the use of artificial intelligence will bring better analytics, and even predictive technology.

A listener’s location, mood and even the weather conditions are now being built into some recommendation engines. Google Play is, for example, working on such adaptive functions.

“A bot will be able to recognise guilty pleasures . . . see that I’ve been to the pub and serve me a Little Mix record when I’m on the way home,” says Luke Ferrar, head of digital at Polydor, pointing to the use of algorithms to understand how people listen to music.

When combined with the sort of intelligence provided by a smartphone — location, time, activity and movement — it means that music services can find the right track for the right moment. In effect, AI can determine whether a person is bored in an airport, studying in a library or sunning themselves on a beach, to tailor a playlist.

AI has already started to be used to improve streaming services. Quantone, a London-based music AI start-up, is using the IBM Watson engine to further improve recommendations by crunching music reviews, blogs and Twitter comments into how music is analysed.

Evan Stein, chief executive of Quantone, said AI allows for a more precise data set than “you like Iron Maiden, you’ll probably like Metallica” to one where someone who appears to like a certain bass player can be pointed to other records featuring the same musician.

The rise of smart assistants such as Apple’s Siri and Amazon’s Alexa in the home also points to a future where AI acts as a “musical concierge” in the living room or car according to Geoff Taylor, chief executive of the BPI.

AI’s role in the music industry is also expanding into the business. Record labels have started to use “chat bots” — computer programs that interact with consumers — to promote new albums and tours. The pop singers Robbie Williams and Olly Murs have launched bots to answer questions from fans and push them to buy more from online stores. Bastille, the British band, created a bot that masqueraded as an evil company called WW Comms that sent fans Gifs and video clips.

There is a lot of hyperbole about robots taking over but its more about getting a better hammer to hit more nails
Evan Stein, chief executive of Quantone

There is also the opportunity to use AI to find new artists. Instrumental, a British label, scrapes YouTube for people uploading their songs and then sifts through data on thousands of unknown artists to define which have started to attract attention. The label, which is backed by Warner Music, has signed three of the most promising to development deals.

Some remain unconvinced that old-fashioned talent spotting is set to be replaced, however. Simon Wheeler, head of digital at independent label Beggars Group, told the Midem conference in June: “We have a role of finding things that people don’t know they’re going to like . . . and data are not very good at doing that stuff.”

The biggest question is whether the robots will start making the music too. Google’s Deepmind has been used to create a piece of classical piano music, while the technology company’s Magenta research project is using machine learning to create “compelling art and music”. That leads to the question of whether sophisticated machines will end up creating music for their own enjoyment, according to the BPI. In other words, will androids dream of electric guitars?

British start-up Jukedeck, which operates out of TechHub, has already used AI to created half a million pieces of original music aimed at companies and video creators looking to create fresh pieces rather than paying royalties. This is hitting the stock audio industry and has the potential to reduce royalties if retailers, for example, use Jukedeck to create muzak rather than playing hits in store.

Mr Taylor said: “Some may fear this will mean the sheet music is on the wall for human composers and that we will all be consigned to a dystopian future surrounded by soulless muzak.”

But Ed Rex, co-founder of Jukedeck, does not think AI will kill off the human composer, but instead expects more musicians to use algorithms to improve their own work.

Mr Stein also remains unconvinced. “There is a lot of hyperbole about robots taking over but its more about getting a better hammer to hit more nails. A terrible composer will still make terrible music, just at a faster speed.”

Copyright The Financial Times Limited 2016. All rights reserved.


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