In just less than a year, Suno, a startup specializing in AI-generated music, now boasts of up to 12 million users as the company claims. After securing $125 million in a Series B funding round, the company is now valued at $500 million. The AI tool allows users to create full-length songs from text prompts, and is touted as a game-changer in the music industry.
It gained more popularity when Microsoft included the app as a plugin in Microsoft Copilot in December 2023. And just last March, it released its v3 version for both free and paying users.
AI-Powered Music Revolution? It Depends
Suno's core product combines its proprietary music model with OpenAI’s ChatGPT to generate music and lyrics to produce tracks that the company claims to sound human-generated.
To foster a community of music creators, Suno launched the “Summer of Suno” program in June, offering $1 million in payouts to the most popular tracks created on its platform. This encourages users to produce and share their music, promoting Suno's capabilities.
Despite its technology, the company faces scrutiny over its training data. Ed Newton-Rex, a former VP of Audio at Stability AI, analyzed Suno's AI and suggested it may have been trained on copyrighted materials without permission. Newton-Rex believes that the works of Eminem, Ed Sheeran, and ABBA are used to develop the songs.
In an article by RollingStone, Antonio Rodriguez of Matrix Partners, an early investor, acknowledged the risk of lawsuits but emphasized the importance of developing the product without initial constraints from music labels.
British-born American guitarist and songwriter Vernon Reid, who founded the rock band Living Colour, worries about the ethical implications of AI producing music genres rooted in human experience, such as the blues. Suno’s founders, on the other hand, argue that their technology will benefit artists by increasing overall engagement with music.
AI Music Generators
Generating music from AI may look like new technology, but such isn’t so if we delve into computer music history. Between September 1955 and November 1956, experiments were conducted to explore if digital computers like the Illiac at the University of Illinois could generate music based on logical compositional instructions. The resulting Illiac Suite, divided into four movements, aimed to address various musical problems, using random sampling to ensure a representative output rather than selectively chosen superior results.
In 1965, Raymond Kurzweil, considered a pioneer in artificial intelligence and a prolific inventor, developed the Kurzweil 250, a synthesizer capable of emulating acoustic instruments, which has been widely adopted by musicians. In addition to his technological contributions, Kurzweil has authored several books, including "The Age of Intelligent Machines" and "The Singularity Is Near," where he discusses the future of AI and human-machine convergence.
By 1983, the Kansei Music System, developed by Yamaha Corporation, utilized advanced music information processing and artificial intelligence techniques to tackle the transcription problem, particularly for simpler melodies. Its development was formally documented in a 1989 paper by demonstrating the feasibility of applying AI to music, a concept that was relatively novel at the time.
Experiments in Musical Intelligence, commonly known as EMI, is another groundbreaking project that was initiated by David Cope in the early 1980s. EMI can generate compositions that closely resemble those of well-known composers like Bach, Mozart, and Chopin. Critics and enthusiasts alike were astonished by the system's capacity to produce convincing musical works, raising questions about creativity, originality, and the role of AI in the arts.
Fast forward to 2010, Iamus, an artificial intelligence developed by the University of Málaga in Spain, made a significant breakthrough in the realm of AI-driven music composition by producing the first fragment of original contemporary classical music.
Today, aside from Suno, the AI music generation space includes Udio, OpenAI's MuseNet, Amper Music, AIVA (Artificial Intelligence Virtual Artist), Jukedeck, Google's Magenta, Endlesss, Humtap, and Hexachords Orb Composer.
But Is It ethical?
One of the primary ethical concerns with AI music generators like Suno is the potential infringement of copyrighted materials. Suno and similar AI systems are often trained on vast datasets that may include copyrighted music without proper authorization. Record labels have filed lawsuits against Suno with damages amounting to damages up to $150,000 per work. They claim that the app uses materials from artists without consent, and can lead to more legal challenges and raise questions about the ethical use of copyrighted works in training AI models.
Another major ethical issue is the misuse of AI music generators to create and disseminate harmful or offensive content. Reports have highlighted that Suno has been used to generate music with racist and antisemitic messages. The Anti-Defamation League (ADL) found a "vast library of disturbing songs'' created with Suno, including tracks that glorify Hitler and promote white supremacist ideologies.
Transparency in the data and processes used by AI music generators is crucial for ethical practice. The lack of clarity on what data Suno is trained on exacerbates concerns about copyright infringement and ethical use. Public details about the training data are scant, and the opaque nature of these systems fuels suspicion and mistrust among artists and industry stakeholders.
Finally, investors in music royalties rely on predictable income streams from licensing and streaming of human-created music. The proliferation of AI-generated music could disrupt these streams, especially if AI music becomes widely accepted and integrated into commercial uses, such as advertising, background scores, and entertainment.
However, investors might need to adapt their strategies in response to the growing presence of AI in music. This could involve diversifying investments to include AI-driven music companies or technologies that enhance music distribution and monetization provided that no copyright infringement is committed by developers.
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