Survey Finds 97% of Listeners Can’t Tell AI Music From Human Songs

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Nearly all listeners can no longer tell when a song has been composed by a machine.
A new Deezer–Ipsos survey revealed that 97% of respondents were unable to distinguish between AI-generated and human-made music, exposing the profound transformation — and disruption — that artificial intelligence is bringing to the global music industry.

The study, which polled 9,000 participants across eight countries, including the U.S., the U.K., and France, underscores how AI tools are reshaping creativity, raising copyright and ethical concerns, and threatening the income of traditional artists.

Despite their inability to detect the difference, most listeners want transparency. About 73% supported clear labelling for AI-generated tracks, 45% wanted filters to exclude them, and 40% said they would skip such songs entirely.

Deezer, which now receives over 50,000 AI-generated song uploads per day—a third of its total submissions—has introduced tagging systems and excluded synthetic tracks from editorial playlists and algorithmic recommendations.
“We believe creativity is a human value, and artists deserve protection,” said Deezer CEO Alexis Lanternier, calling for stronger transparency measures.

The company has also begun removing fake streams from royalty calculations and is exploring how to adjust payment structures for AI-generated music, though Lanternier admitted such changes would be complex.

The debate intensified earlier this year when AI band The Velvet Sundown gained over a million monthly Spotify listeners before being revealed as fully artificial. Meanwhile, Universal Music Group recently settled a copyright case with AI startup Udio and plans to launch a licensed AI-music tool in 2026.

Adding to the controversy, a Munich court ruled this week that OpenAI’s ChatGPT violated German copyright laws by reproducing song lyrics without permission.

IBM’s ‘Loon’ Chip Marks Major Step Toward Practical Quantum Computers by 2029

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IBM has unveiled a new experimental quantum computing chip, dubbed “Loon,” that the company says achieves a critical milestone toward building useful, error-corrected quantum computers by 2029.

Quantum computers hold the potential to solve complex problems in chemistry, physics, and logistics that would take traditional supercomputers thousands of years to complete. However, the fragile quantum states that power these machines are notoriously prone to errors — a challenge that has long stood in the way of practical applications.

To address this, IBM in 2021 proposed an innovative approach to error correction, adapting algorithms originally developed to improve cellphone signal reliability. The method uses a hybrid system combining quantum and classical chips to stabilize qubits — the basic units of quantum computation.

According to Jay Gambetta, IBM Research director and IBM Fellow, the Loon chip was fabricated at the Albany NanoTech Complex in New York, using the same advanced semiconductor tools found in cutting-edge commercial fabs.

“Loon remains in early stages,” Gambetta said, “but it demonstrates a critical step toward error-corrected quantum computing that can outperform classical systems.”

IBM also introduced another chip, “Nighthawk,” which will be made available by the end of this year. The company expects Nighthawk to surpass classical computers on specific tasks by late 2026.

Analyst Mark Horvath of Gartner called the new design “very clever,” noting that the inclusion of quantum interconnections between qubits makes the chips harder to build but exponentially more capable.

IBM plans to make Nighthawk’s code openly available to researchers and startups, fostering a community-driven testing model to validate claims of quantum advantage — when quantum systems outperform classical ones.

AMD Shares Jump After Company Sets $100 Billion Data Center Revenue Target

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Advanced Micro Devices (AMD) saw its shares climb nearly 5% in premarket trading on Wednesday after the company unveiled ambitious long-term growth goals, including a plan to reach $100 billion in annual data center revenue within five years by taking a larger share of the booming AI chip market from rival Nvidia.

Speaking at an investor event in New York, CEO Lisa Su said AMD expects the market for data center chips to expand to $1 trillion by 2030, driven by AI adoption and stronger software integration.

To capitalize on that opportunity, AMD is preparing to roll out its next-generation MI400 chips and the Helios rack system in 2026. These products are part of the company’s broader strategy to compete more aggressively in AI computing, an area dominated by Nvidia.

“AMD’s success will come from being better than NVIDIA on whatever metrics matter most to customers,” analysts at Morgan Stanley said, adding that factors like power efficiency, component availability, and performance will determine leadership in what they called a “winner-takes-most” market.

At the event, AMD projected 35% annual growth for its overall business and 60% annual growth in its data center segment over the next three to five years. Chief Financial Officer Jean Hu said the company also aims for earnings of $20 per share within that timeframe, compared to LSEG’s 2025 estimate of $2.68 per share.

While analysts praised AMD’s bold targets, some cautioned about execution challenges, potential AI spending slowdowns, and supply chain constraints.

AMD shares have already gained 97% this year and are up 16% since October 6, when the company announced a partnership with OpenAI.