Online AI platforms for creating music from text prompts (AI music), such as Suno and Udio, are now being used by hundreds of thousands of users. Some AI music is appearing in advertising, and even charting, in multiple countries. How are these platforms being used? What subjects are inspiring their users? This article answers these questions for Suno and Udio using a large collection of songs generated by users of these platforms from May to October 2024. Using a combination of state-of-the-art text embedding models, dimensionality reduction and clustering methods, we analyze the prompts, tags and lyrics, and automatically annotate and display the processed data in interactive plots. Our results reveal prominent themes in lyrics, language preference, prompting strategies, as well as peculiar attempts at steering models through the use of metatags. To promote the musicological study of the developing cultural practice of AI-generated music we share our code and resources.

Recent advances in text-to-music (TTM) generation have enabled controllable and expressive music creation using natural language prompts. However, the emotional fidelity of TTM systems remains largely underexplored compared to human preference or text alignment. In this study, we introduce AImoclips, a benchmark for evaluating how well TTM systems convey intended emotions to human listeners, covering both open-source and commercial models. We selected 12 emotion intents spanning four quadrants of the valence-arousal space, and used six state-of-the-art TTM systems to generate over 1,000 music clips. A total of 111 participants rated the perceived valence and arousal of each clip on a 9-point Likert scale. Our results show that commercial systems tend to produce music perceived as more pleasant than intended, while open-source systems tend to perform the opposite. Emotions are more accurately conveyed under high-arousal conditions across all models. Additionally, all systems exhibit a bias toward emotional neutrality, highlighting a key limitation in affective controllability. This benchmark offers valuable insights into model-specific emotion rendering characteristics and supports future development of emotionally aligned TTM systems.

I reflect on my experience creating two music albums centered on state-of-the-art prompt-based AI music generation platforms. The first album explicitly poses the question: What happens when I collide my junk mail with these platforms? The second album is a direct response to the first, and toys with the inability of state-of-the-art prompt-based AI music generation platforms to generate music that is not ``practiced'', ``polished'', and ``produced''. I seed a large language model (LLM) with information about these albums and have it interview me, which results in the exploration of several deeper questions: To what extent am I the author? Where am I in the resulting music? How is my musical identity changing as I am faced with machines that are in some ways far more talented than I? What new musical spaces does my work open, for me or anyone/thing else? I conclude by reflecting on my reflections, as well as LLM-mediated self-reflection as method.

The lawsuits allege Udio produced output with "striking resemblances" to songs including Dancing Queen by ABBA and All I Want For Christmas Is You by Mariah Carey, while Suno allegedly turned out songs similar to I Got You (I Feel Good) by James Brown and Johnny B. Goode by Chuck Berry, among others. Record labels were able to basically recreate versions of very famous songs with highly specific prompts, then linked to them in the lawsuits. I made a short compilation here:https://t.co/9Nu7rW7eqD These lawsuits are not the first to trouble the booming generative AI industry. Visual artists have sued makers of image generating systems, while various newspapers are suing OpenAI, the owner of ChatGPT, for similar allegations.

The first concert I bought tickets to after the pandemic subsided was a performance of the British singer-songwriter Birdy, held last April in Belgium. I've listened to Birdy more than to any other artist; her voice has pulled me through the hardest and happiest stretches of my life. I know every lyric to nearly every song in her discography, but that night Birdy's voice had the same effect as the first time I'd listened to her, through beat-up headphones connected to an iPod over a decade ago--a physical shudder, as if a hand had reached across time and grazed me, somehow, just beneath the skin. Countless people around the world have their own version of this ineffable connection, with Taylor Swift, perhaps, or the Beatles, Bob Marley, or Metallica. My feelings about Birdy's music were powerful enough to propel me across the Atlantic, just as tens of thousands of people flocked to the Sphere to see Phish earlier this year, or some 400,000 went to Woodstock in 1969.

The world's biggest record labels are suing two artificial intelligence startups, taking an aggressive stance to protect their intellectual property against technology that makes it easy for people to generate music based on existing songs. The Recording Industry Association of America said it filed twin lawsuits Monday against Suno AI and Uncharted Labs Inc., the developer of Udio AI, on behalf of Universal Music Group NV, Warner Music Group Corp. and Sony Music Entertainment. The RIAA, a trade group for record labels, is seeking damages of as much as 150,000 "per work infringed." That could amount to potentially billions of dollars. "The music community has embraced AI, and we are already partnering and collaborating with responsible developers to build sustainable AI tools centered on human creativity that put artists and songwriters in charge," Mitch Glazier, chief executive officer of the RIAA, said in a statement.

Major music labels are taking on AI startups that they believe trained on their songs without paying. The filings against the AI companies reportedly demand injunctions against future use and damages of up to 150,000 per infringed work. The suits appear aimed at establishing licensed training as the only acceptable industry framework for AI moving forward -- while instilling fear in companies that train their models without consent. Suno AI and Udio AI (Uncharted Labs run the latter) are startups with software that generates music based on text inputs. The former is a partner of Microsoft for its CoPilot music generation tool.

The music industry has officially declared war on Suno and Udio, two of the most prominent AI music generators. The plaintiffs seek damages up to 150,000 per work infringed. The lawsuit against Suno is filed in Massachusetts, while the case against Udio's parent company Uncharted Inc. was filed in New York. Suno and Udio did not immediately respond to a request to comment. "Unlicensed services like Suno and Udio that claim it's'fair' to copy an artist's life's work and exploit it for their own profit without consent or pay set back the promise of genuinely innovative AI for us all," Recording Industry Association of America chairman and CEO Mitch Glazier said in a press release.

In March, we saw the launch of a "ChatGPT for music" called Suno, which uses generative AI to produce realistic songs on demand from short text prompts. A few weeks later, a similar competitor – Udio – arrived on the scene. I've been working with various creative computational tools for the past 15 years, both as a researcher and a producer, and the recent pace of change has floored me. As I've argued elsewhere, the view that AI systems will never make "real" music like humans do should be understood more as a claim about social context than technical capability. The argument "sure, it can make expressive, complex-structured, natural-sounding, virtuosic, original music which can stir human emotions, but AI can't make proper music" can easily begin to sound like something from a Monty Python sketch.