As we have seen in previous parts of this blog series, AI applications are quickly reaching the limits of copyright law. This starts with training the AI with huge amounts of music data, continues with processing that data in the hidden layers of the AI, and ends with AI output such as voice clones. Copyright issues can therefore arise throughout the entire process of AI-generated music, which we will explore in this part of the “AI in the Music Industry” series. AI in the Music Industry – Part 14: AI and Copyright Infringement Let’s remember how music AI works. Whatever AI systems are used, w ..read more

Text-to-music generators are an important development for user-friendly music creation, using simple commands (prompts) to tell the AIs what music to make, as we know from ChatGPT. Not only are new pieces of music created en masse by AIs, but also voice clones of superstars that are indistinguishable from the original. The most popular tools, such as Music LM, Stable Audio, Riffusion and MusicGen, will be discussed in more detail in this part of the blog series. AI in the Music Industry – Part 13: Text-to-Music-Generators: Music LM, Stable Audio, Riffusion and MusicGen Google has already taken ..read more

Another company at the forefront of AI research and driving the transition from Artificial Narrow Intelligence (ANI) to Artificial General Intelligence (AGI) is Google and its parent company Alphabet. In particular, in the area of AI-generated music creation, Google created early AI applications with Magenta Studios, which ultimately opened the door to Artificial General Intelligence in music creation with WaveNet, developed by DeepMind. Both developments will be explored in this part of the blog series. AI in the Music Industry – Part 12: Google’s Magenta Studio and the WaveNet The following ..read more

Volume 13, no 1, April 2024 Editorial by Peter Tschmuck, p. 1 Alex Timewell: Music Business Education in the Global Creative Industries: Curriculum design, inclusive practice and measures of success, pp. 3-16 Xuejie Huang & Mei Foong Ang: Factors Predicting Singers’ Work Efficiency and Singers’ Singing Peak, pp. 17-26 Book review by Guy Morrow: ‘Chokepoint Capitalism: How Big Tech and Big Content Captured Creative Labour Markets and How We Will Win Them Back’ by Cory Doctorow and Rebecca Giblin, pp. 27-28. Book review by Guy Morrow: ‘Artificial Intelligence and Music Ecosystem’ by Martin C ..read more

An important pioneer in AI music creation was François Pachet, who originally worked at the Université Pierre et Marie Curie in Paris before moving to the SONY Computer Science Laboratory to experiment with AI in music improvisation. Among other things, he created the first AI that could interact with jazz musicians on stage in real time, as well as the first AI-generated pop song, “Daddy’s Car”. François Pachet’s role as a pioneer in AI music creation is highlighted in this part of the series “AI in the Music Industry”. AI in the Music Industry – Part 10: François Pachet: The Continuator, Flo ..read more

It has always been a dream of mankind that music would not only be produced by instruments played by musicians, but that machines would be able to create music on their own. As early as the 18th century, music boxes that could play well-known melodies were very popular, and composers in the rank of Mozart and Beethoven were not above composing pieces for so-called musical clocks.  However, the theoretical foundations for a machine that could compose music as well as perform complex arithmetic tasks were laid in 1840 by Charles Babbage with his “Analytical Engine”. Based on this early visi ..read more

15th International Music Business Research Days (2024) Music Ecosystem Research: Challenges and Opportunities June 5 – 7, Hanover University of Music, Drama and Media, Department of Journalism and Communication Research in collaboration with HYPE&FRIENDS, GMM e. V. and Austrian Music Business Research Association (AMBRA) CALL FOR PAPERS Music business research is an interdisciplinary field that puts different analytical approaches into mutual dialogue. It is located at the intersection of economic, artistic, musical, cultural, social, legal, and technological understandings of the cre ..read more

The Young Scholars’ Workshop is part of the 15th International Music Business Research Days. Young researchers are invited to submit abstracts from all disciplinesexploring questions that help understand economic and managerial problems as well as processes in the music sector and in the field of music management. The Young Scholars’ Workshop will be co-organized by the IJK and the GMM e.V., the German branch of the IMBRA: A society for music business and music culture research. We encourage early-stage researchers, either in the beginning of their doctorate projects, or in the beginning of th ..read more

Spotify was one of the first streaming services to use AI technology to successfully persuade users to use its service. However, Spotify has also been accused of misusing AI to create fake artists in order to get a bigger slice of the streaming pie. The misuse of AI to manipulate music streams is the dark side of the AI revolution in music streaming, and even led to a prosecutor’s investigation into music streaming service Tidal in Norway. Although the case was eventually dropped, it draws attention to the growing influence of AI-generated content being played on a loop via illegal streaming f ..read more

One of the most important applications of artificial intelligence in the music industry is music recommendation in music streaming services such as Spotify. The history of music recommendation goes back to the early 2000s, when LastFM’s Audioscobbler and Pandora’s Music Genome Project transformed internet radio into music streaming. AI in the Music Industry – Part 5: Music Recommendation in Music Streaming In 1999, when the P2P file-sharing network Napster was hitting the headlines, Austrian Martin Stiksel and German Felix Miller met at a concert. The two computer nerds agreed that Napster was ..read more