'Music is not a problem to solve' Mikey Shulman, co-founder and CEO of Suno. 'Music is not a problem to solve' Mikey Shulman, co-founder and CEO of Suno. Is this man the future of music - or its executioner? AI evangelist Mikey Shulman says he's making pop, not slop Worth a staggering $2.45bn, Suno is an AI music company that can create a track with just a few prompts. Why is its CEO happy to see it called'the Ozempic of the music industry'?

Brit Award-winning singer Jorja Smith's record label has said it wants a share of the royalties for a song it claims was created using an artificial intelligence clone of the singer's voice. I Run by British dance act Haven went viral on TiKTok in October thanks, in part, to smooth soul vocals by an uncredited female singer. Although I Run has now been re-released with new vocals, Smith's label FAMM said it believes the track was made with AI trained on her work, and is seeking compensation. It's bigger than one artist or one song, FAMM wrote in a statement on Instagram . The label said it believes both versions of the track infringe on Jorja's rights and unfairly take advantage of the work of all the songwriters with whom she collaborates.

In the digital streaming landscape, it's becoming increasingly challenging for artists and industry experts to predict the success of music tracks. This study introduces a pioneering methodology that uses Convolutional Neural Networks (CNNs) and Spotify data analysis to forecast the popularity of music tracks. Our approach takes advantage of Spotify's wide range of features, including acoustic attributes based on the spectrogram of audio waveform, metadata, and user engagement metrics, to capture the complex patterns and relationships that influence a track's popularity. Using a large dataset covering various genres and demographics, our CNN-based model shows impressive effectiveness in predicting the popularity of music tracks. Additionally, we've conducted extensive experiments to assess the strength and adaptability of our model across different musical styles and time periods, with promising results yielding a 97\% F1 score. Our study not only offers valuable insights into the dynamic landscape of digital music consumption but also provides the music industry with advanced predictive tools for assessing and predicting the success of music tracks.

This was the year that gen Z had their "Brat summer", or so we were led to believe. Inspired by the hit album by pop sensation Charli xcx, the trend was seen to embody all the messiness of modern youth: trashy, chaotic and bright green. But on the teenager's social media platform of choice, TikTok, a more sepia music trend has been taking root. Despite having an endless amount of music to pair with their short, scrollable videos, TikTok users have been raiding the back catalogues of artists from yesteryear including Bronski Beat and Sade to soundtrack their posts. This year set a new high for use of old tracks on British TikTok posts, with tunes more than five years old accounting for 19 out of its 50 top tracks this year.

"The only thing to be worried about is if you're making music to chase an algorithm," he told Fox News Digital. "If you're making music to trend on TikTok. And to do that, you have to really unlock the codes to that matrix. If that's your whole [hustle], then AI is going to do a better job than that." The Black Eyed Peas singer does think people not involved in the creative process in the music industry are the ones who should worry about AI taking away their jobs.

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 process of instruction tuning aligns pre-trained large language models (LLMs) with open-domain instructions and human-preferred responses. While several studies have explored autonomous approaches to distilling and annotating instructions from more powerful proprietary LLMs, such as ChatGPT, they often neglect the impact of task distributions and the varying difficulty of instructions of the training sets. This oversight can lead to imbalanced knowledge capabilities and poor generalization powers of small student LLMs. To address this challenge, we introduce Task-Aware Curriculum Planning for Instruction Refinement (TAPIR), a multi-round distillation framework with balanced task distributions and dynamic difficulty adjustment. This approach utilizes an oracle LLM to select instructions that are difficult for a student LLM to follow and distill instructions with balanced task distributions. By incorporating curriculum planning, our approach systematically escalates the difficulty levels, progressively enhancing the student LLM's capabilities. We rigorously evaluate TAPIR using two widely recognized benchmarks, including AlpacaEval 2.0 and MT-Bench. The empirical results demonstrate that the student LLMs, trained with our method and less training data, outperform larger instruction-tuned models and strong distillation baselines. The improvement is particularly notable in complex tasks, such as logical reasoning and code generation.

In the last week, highly anticipated songs by Drake and Taylor Swift appeared to leak online, sparking enormous reactions. Massive Reddit threads spawned, dissecting musical choices. Meme videos were created simulating other rappers' reactions to being dissed by Drake. The rapper Rick Ross even responded to the song's bars about him with a diss track of his own. But there was one big problem: neither Swift nor Drake confirmed that the songs were real.

Billie Eilish, Nicki Minaj and Katy Perry are among 200 high-profile artists calling for the'predatory' use of AI in the music industry to be stopped. In an open letter, several of the world's biggest stars have warned the tech'will set in motion a race to the bottom' if left unchecked. The use of AI to steal artists' voices, likeness, and sound is an'assault on human creativity', they said, and would'destroy the music ecosystem'. Issued by the Artists Rights Alliance (ARA), the letter calls for a ban on AI tools that undermine or replace human songwriters or their work. The move is part of an industry-wide push for better regulation of generative AI, the technology behind chatbots like ChatGPT and image generators like Midjourney.

Sir Lucian Grainge, the chairman and C.E.O. of Universal Music Group, the largest music company in the world, is curious, empathetic, and, if not exactly humble, a master of the humblebrag. His superpower is his humanity. A sixty-three-year-old Englishman, who was knighted in 2016 for his contributions to the music industry and has topped Billboard's Power 100 list of music-industry players several times in the past decade, Grainge is compact and a bit chubby, with alert eyes behind owlish glasses. He isn't trying to be noticed. He presides over a public company worth more than fifty billion dollars, but he could be a small-business owner who sells music in a London shop, as did his father, Cecil.