Click Headlines to read more of the latest news!

 

Tech startup RTM Audio launches AI music detector UAI, which issues a signed certificate with every verdict
A new music-technology company called RTM Audio has launched an AI music detector that it says produces an independently verifiable certificate for every track it analyzes.  The Los Angeles-founded company says its system, UAI, runs two separate measurements on each track, one on the production and one on the vocal, and flags a recording as AI only when both agree. RTM Audio says four patent applications are in preparation.  When the system is not fully confident, RTM Audio says, it routes the track to a human reviewer rather than forcing a verdict. RTM Audio was founded by mixing and mastering engineers Ohad Nissim, Teezio, and Calin Enache, alongside music attorney Matt Buser.  Nissim, the company’s Chief Technology Officer, is a Grammy-nominated mastering engineer, while Teezio, the company’s CEO, is a two-time Grammy winner. “The whole point was to build something where a human artist is never accused unless two independent systems both flag the same track, and then you get a certificate, not a confidence score.”Deezer said in April that it was receiving nearly 75,000 fully AI-generated tracks a day, more than 44% of all new music uploaded to the platform.

 

NO FAKES: Senate panel backs bill that could cost platforms $750k per AI deepfake
The US Senate Judiciary Committee has advanced the NO FAKES Act, the bipartisan bill that would create a federal right protecting Americans’ voice and visual likeness from AI-generated deepfakes.  The committee passed the bill unanimously by voice vote on Thursday (June 18), according to Deadline, which noted that “three Republican senators — Mike Lee, Ted Cruz, and Eric Schmitt — raised First Amendment concerns”.  Clearing the committee sends the bill toward a vote by the full Senate, after which it would still need to pass the House of Representatives and be signed by the President before becoming law. Penalties under the bill are tiered: $5,000 per work for an individual, $25,000 per work for a company that creates or distributes a replica, and up to $750,000 per work for an online service that fails to comply. 

 

Majors and BMG ask US Supreme Court to overturn copyright termination ruling they say will cause ‘chaos’
The major music companies and BMG have asked the US Supreme Court to overturn a ruling that lets songwriters reclaim the worldwide rights to their songs under American law.  In a petition filed on June 11, the rightsholders warned that the decision would unleash “chaos” on the industry if left to stand, and asked the justices to reverse a January ruling by the US Court of Appeals for the Fifth Circuit. The ruling held that a songwriter exercising their termination right recaptures the worldwide rights once signed away, not just the US copyright.  Termination, written into the 1976 Copyright Act, lets creators undo an old transfer and reclaim their rights, 35 years after the grant, or 56 years for pre-1978 works.  Until that decision, the long-standing industry view was that termination reached only US rights, with overseas rights staying with the publisher.  Once briefing wraps, the court will decide whether to grant review, a long shot regardless, since the justices take only a sliver of the cases put before them each term.

 

AI Could Use as Much Water as 1.3 Billion People by 2030, U.N. Report Warns
he water used by artificial intelligence is expected to equal the needs of 1.3 billion people by 2030—threatening natural resources for billions around the world. That’s according to a new report from the United Nations University Institute for Water, Environment and Health (UNU-INWEH) which quantifies the carbon, water, and land footprints of AI's electricity use around the globe. The report finds that AI’s environmental cost is often mismeasured—focusing solely on carbon emissions. However, cooling and generating power for data centers comes with a “water footprint,” while the energy infrastructure and supply chains to build the data centers have a “land footprint.” These are important factors to consider, the report says, when analyzing the stressors a region might be facing due to data centers. By 2030, the report finds, global data centers powering artificial intelligence are projected to consume 945 terawatt-hours of electricity. This is nearly triple the combined annual electricity use of Pakistan, Bangladesh, and Nigeria—countries that together are home to more than 650 million people. The water footprint of data centers is projected to equal the basic domestic water needs of all 1.3 billion people in Sub-Saharan Africa for a year, while their land footprint could exceed 5,590 square miles.But switching to cleaner sources of energy isn’t as simple as it sounds. Minimizing one footprint could come at the expense of magnifying another, researchers say. For example, switching from coal to bioenergy cuts electricity’s carbon footprint by 70%—but increases its water footprint more than 30-fold and its land footprint 100-fold. For a number of communities around the globe, AI is already using up significant energy resources. In 2025 alone, data centers consumed an estimated 448 terawatt-hours of electricity, the report found—more than the country of Saudi Arabia. In many cases, this excessive energy use comes at a cost to those who reside near them. 

 

A landmark bill targeting AI deepfakes faces a US Senate Judiciary Committee vote on June 18. Five things to know about the NO FAKES Act.
In 2023, an AI-generated track called Heart on My Sleeve cloned the voices of Drake and The Weeknd, drawing hundreds of thousands of streams before it was pulled from Spotify and YouTube.  Neither artist performed on it, and cloning a voice is not clearly copyright infringement – a gap the NO FAKES Act aims to close.  The Nurture Originals, Foster Art, and Keep Entertainment Safe (NO FAKES) Act goes before the US Senate Judiciary Committee on Thursday (June 18).  It would create, for the first time in US federal This is its third attempt.  A version introduced in July 2024 ran out of time before that Congress ended, and a 2025 reintroduction stalled in the Senate Judiciary Committee as sponsors negotiated with big tech and free-speech groups warned it swept up protected speech.  A bipartisan group reintroduced the latest version on May 20.  Here are five things the music business needs to know before the vote. 1) It would create a federal right to your own voice and likeness law, an intellectual property right in a person’s voice and visual likeness, 2) Platforms could face up to $750,000 per track, 3) It builds on Tennessee’s ELVIS Act – but makes it national, 4) Its backers run from the major labels to indie artists – but not everyone is sold, 5) It lands as AI floods streaming – and detection still isn’t reliable. If the NO FAKES Act clears the committee on Thursday, it would still face the full Senate, the House, and the President‘s desk before becoming law.

 

Paying for Precision—The New Economics of Music Usage Data for Royalty Distribution
For decades, the music industry has accepted a compromise in how royalties from public performance are distributed. When music is played in cafes, restaurants, retail stores, gyms, and other licensed venues, businesses pay fees with the expectation that the rights creators will be compensated for those plays. But in practice, collective management organizations (CMOs) have relied on proxy data to allocate those royalties rather than concrete data. That proxy data is derived from radio airplay, surveys, and partial reporting from a limited pool of venues.This system was designed to balance cost, practicality, and precision. However, it comes with a major structural limitation—it does not measure what is actually played across the majority of physical locations. Instead, music usage and therefore royalty payments are estimated based on indirect signals. That creates a fundamental issue for musicians and rights holders who want to be paid when their music is utilized in this way. Without a benchmark tied to real-world playback in these environments, there is no way to quantify how accurate royalty distributions truly are. The industry is not working within known margins of error, but rather without a measurable understanding of how far distributions diverge from actual usage in public performance settings. This lack of precision in royalty distribution has financial consequences for everyone involved. When proxy-based systems are used, value is redistributed along blurred lines. Some rights holders benefit disproportionately because their music is over-represented in proxy datasets. Others are underpaid because their music, while played in venues, is not captured. This is particularly relevant for independent artists and niche genres that may perform strongly in public spaces, but lacks broader airplay data. Other sectors outside the realm of music routinely invest in better data to improve outcomes. Music royalty distribution for public performance is now approaching the same inflection point. The central issue is no longer technological feasibility, but whether the industry is willing to move beyond systems that are not capable of measuring their own accuracy. As expectations around fairness and transparency increase, reliance on proxy data becomes harder to defend.

 

Is Anyone’s Music Safe? Newly Identified ‘Giant Datasets’ Containing Millions of Songs Raise Fresh Questions About Music AI Training Processes
Are gen AI companies actively developing their music models with the same collections of copyrighted tracks? And despite ongoing discussions about free-for-all training, is this process far more systematic than we’ve been led to believe?  These and other pressing questions are taking center stage following an investigative report from The Atlantic’s Alex Reisner, who identified “four giant datasets of songs that are being shared within the AI-development community.” Unsurprisingly, even in light of the noted report, we don’t have a concrete answer. Said report pinpointed four training datasets consisting of north of 22 million recordings between them – including two collections clocking in at closer to 100,000 recordings apiece, one containing 9.7 million songs, and the last with roughly 12.3 million tracks. Google and Stability AI have reportedly utilized tracks from one of the 100,000-song datasets, the Free Music Archive. Owing to “the industry’s secrecy around training data, we don’t currently know who has used the others” – though all four are said to have been “downloaded thousands of times” in total, per the report.

 

After Spotify Eyes Concert Streaming, YouTube Launches ‘Music Nights’ Exclusive Live Concert Series
Just a week after Spotify reportedly began shopping around to secure licensing to stream live events, YouTube claps back with “Music Nights.” The new series of exclusive concerts designed “for dedicated fans” will include release parties, intimate shows, and special tour stops, with the first three to feature Isaiah Rashad, Kacey Musgraves, and Bleachers.  “This year, we’re hosting Music Nights in music hubs across the globe, from Los Angeles, New York, Paris, London, and Tokyo to unique destinations with a special meaning to artists, like New Braunfels, Texas, and Asbury Park, New Jersey,” reads YouTube’s blog post. “You can dive into the full performances, relive standout tracks on repeat, and explore exclusive behind-the-scenes moments on Shorts, directly on each artist’s Official Artist Channel.” YouTube’s Music Nights is just the latest move in the ongoing rivalry between YouTube Music and Spotify. The two companies have become increasingly competitive in the podcast arena in recent months. But the live music scene is already fiercely competitive, and YouTube has a well-established foot in that door—which might explain the timing of the Music Nights announcement.

 

Data Drain: The Land and Water Impacts of the AI Boom 
A low hum emerges from within a vast, dimly lit tomb, whose occupant devours energy and water with a voracious, inhuman appetite. The beige, boxy data center is a vampire of sorts—pallid, immortal, thirsty. Sheltered from sunlight, active all night. And much like a vampire, at least according to folkloric tradition, it can only enter a place if it’s been invited inside.  In states and counties across the US, lawmakers aren’t just opening the door for these metaphorical, mechanical monsters. They’re actively luring them in, with tax breaks and other incentives, eager to lay claim to new municipal revenues and a piece of the explosive growth surrounding artificial intelligence.  That may sound hyperbolic, but data centers truly are resource-ravenous. Even a mid-sized data center consumes as much water as a small town, while larger ones require up to 5 million gallons of water every day—as much as a city of 50,000 people. Powering and cooling their rows of server stacks also takes an astonishing amount of electricity. A conventional data center—think cloud storage for your work documents or streaming videos—draws as much electricity as 10,000 to 25,000 households, according to the International Energy Agency. But a newer, AI-focused “hyperscale” data center can use as much power as 100,000 homes or more. Early in the AI boom, in 2023, US data centers consumed 176 terawatt-hours of electricity, roughly as much as the entire nation of Ireland (whose electric grid is itself nearly maxed out, prompting data centers there to use polluting off-grid generators), and that’s expected to double or even triple as soon as 2028. (ie: For every question asked CHAT GPT, 1/2 liter of water is consumed at 2.5 billion requests per day)

 

Suno’s Legal Battle Against Sony Music and UMG Just Got 100 Times More Serious—Literally
Universal Music and Sony Music are dramatically expanding their litigation against AI music giant Suno, claiming over 61,000 copyright infringements.  Just moments after Sony Music Entertainment expanded its lawsuit against AI music company Udio, Sony and Universal Music Group dramatically expanded their litigation against Suno, the biggest AI music platform in the game. Instead of just 560 works, the music label giants are claiming infringement of over 61,000 works—at least, if a judge approves their latest amended complaint.  In both of these expanded cases, the labels used Audible Magic, an industry-standard audio fingerprinting technology, to scan Suno’s training data, confirming that the platform used “millions” of their copyrighted tracks to train its AI models. Now, that data source is being submitted into the court record to await approval. Naturally, Suno strongly opposes this move, arguing it would effectively reset the case and delay their ability to pursue their “fair use” defense in a timely manner. However, the labels state that they could settle that matter via summary judgment separately before completing the discovery required for the newly submitted 61,000 tracks.

 

Musicians’ Union Sues Major Labels for Artists’ Share of AI Song Generator Settlement Money
The The American Federation of Musicians is suing major record companies Universal Music Group and Warner Music Group over the labels’ recent moves to settle their lawsuits with AI music generators Suno and Udio, arguing that the settlements’ benefits aren’t reaching the musicians themselves.  “While the Defendants protected their own interests and created a significant source of new revenue with the retrospective settlements and prospective licenses, they have refused to compensate the musicians whose work – created with their own instruments and through their talent, creativity, and hard work – is fed into AI machines for profit,” the AFM said in the complaint filed in federal court. The AFM’s lawsuit comes months after UMG and WMG reached settlements with Udio and Suno last fall. UMG, the world’s largest music company, struck the first deal, announcing a settlement and partnership with Udio in late October of 2025. WMG came after, announcing a partnership of its own with Udio in mid-November. Weeks after that, WMG became the first (and so far the only) major label to settle with Suno.  The “big three” record companies, which includes Sony Music Group alongside UMG and WMG, first sued Suno and Udio in 2024, accusing that the AI music generators of massive copyright infringement by training their models on thousands of iconic songs without permission. Sony is the lone major music company that hasn’t settled with either AI company. 

 

Spotify's AI bet: more of everything, less of what you want
Spotify was a music app at one time. Then it added podcasts. Then audiobooks. Now the company is piling AI features into its app at a pace that can feel overwhelming. The latest wave, announced at its investor day, skews heavily toward using AI to generate content rather than using AI to help users find content they actually want.  Until now, Spotify has been largely a platform for human-created content — music, podcasts, and audiobooks. As it adds AI-powered tools to generate all of those formats, the app is poised to look very different. That shift is also creating friction — AI can now produce music faster than Spotify can manage it. The company is no longer focused solely on consumption — it’s actively nudging users to create content, too, even if it’s just for themselves. The risk is that this trades depth for breadth: The more time users spend making sense of a cluttered app, the less time they spend discovering and listening to content by other creators. This raises the question: Is Spotify deepening its competitive moat or diluting what made it essential?