BrianFagioli writes: Audacity 4.0 has been released with a rebuilt Qt interface, a new clip-editing model, customizable workspaces, native high-DPI rendering, and a new AUP4 project format. The open source audio editor also adds ASIO playback and recording support to official Windows builds, while bringing major changes to recording, playback, plugins, and project handling. The overhaul comes with some tradeoffs. Audacity 4.0 currently lacks several features found in Audacity 3, including Time Tracks, Note and MIDI tracks, Mixer, Macro Manager and scripting pipe, VAMP and LADSPA plugin hosting, and play-at-speed. The developers say they plan to bring the missing functionality back in future releases.

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BrianFagioli writes: Perplexity has built a local artificial intelligence engine designed specifically for Apple silicon and the Qwen3.6-35B-A3B model. Called Lily, the engine uses a Rust runtime and custom Metal kernels, with neither PyTorch nor MLX in its execution path. Perplexity says Lily averaged 23 percent faster prompt processing and 35 percent faster token generation than MLX-LM on an M5 Max MacBook Pro with 128GB of unified memory. Lily is more specialized than MLX-LM, which supports a much wider range of models and architectures. Perplexity says it plans to release Lily as open source, but the code is not available yet, leaving its performance claims dependent on internal testing for now.

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An anonymous reader quotes a report from The Guardian: The release of a new album by Taylor Swift might be a cause for celebration among her fans, but such events have also been linked to a more sombre phenomenon: an increase in fatal car crashes. The team behind a new study say it sheds light on the impact of distracted driving. Writing in the journal Jama Network Open, [Vishal Patel, first author of the study based at Harvard Medical School] and colleagues report how they focused on the release of 10 major albums, launched between 2017 and 2022, selected for having the highest number of Spotify streams over a single day. [...] The team found streaming volume for the top 200 songs in the US was 43% higher on the date of major album releases compared with the days surrounding the releases -- although such data does not reveal whether the music was being streamed in a car. [...] The researchers used data from a population-based registry of fatal US motor vehicle crashes to look at the number of traffic fatalities on the dates these albums were released, as well as for the 10 days either side. After taking into account the day of the week upon which the album was released, as well as federal holidays, and time of year, the researchers found the number of US traffic fatalities showed a relative increase of 15.1% on the date of major album releases, compared with similar days either side. "This is equivalent to approximately 182 fatalities in the US attributable to the release days of the 10 included albums," the team writes. Patel said the release of a new album could distract drivers because accessing music is a search task, not a single button press. "You unlock the phone, open the app, find the release, read down a tracklist, tap the right song. That's several seconds of looking at a screen," he said, adding unfamiliar music also demands more attention, while research has suggested listening to new, high-energy music measurably degrades driving performance. The researchers add the rise in traffic fatalities was greater among certain groups -- such as younger drivers, male drivers, people who were driving alone, and people driving cars with a built-in infotainment platform. The authors say the results suggest that "online music streaming through smartphones may significantly contribute to distracted driving and traffic fatalities."

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Researchers believe they've found evidence that brain signals reveal the pitches of notes in imagined musical melodies, reports Medical Express: Study participants were 10 epilepsy patients with electrodes on the surfaces of their brains for clinical monitoring. Participants quietly listened to the first bars of children's tunes, then imagined the melodies of subsequent bars before humming their imagined melodies. Brain activity from the patients carried information about relative pitches within the imagined melodies. Combining note-level pitch predictions over time allowed the research team to recreate melodic changes that reflected the structure of the imagined songs... "The model we created decodes relative pitch classes — such as do, re, mi, fa, sol, and la — rather than exact, absolute pitches," [said tudy co-lead Jii Kwon of Seoul National University]. "This is useful because people often recognize melodies by the relationships between notes, even when the same melody is played in a different key."

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Suno says it will begin watermarking and fingerprinting AI-generated songs, tighten download policies to curb mass distribution, and explicitly prohibit deceptive audio and unauthorized voice or likeness cloning. The changes come as the company faces mounting copyright lawsuits, a recent adverse ruling in Germany, and scrutiny over a past data breach that revealed training-data sources. TechCrunch reports: In a blog post, co-founder and CEO Mikey Shulman shared core principles and said that the platform wants to promote original creation while enabling more people to make music with its AI tools. One of the key points of contention involved users uploading AI-generated songs on other streaming platforms and gaming the system to earn revenue. Suno said that now it will use audio watermarking and fingerprinting to prevent misuse on other streaming platforms. It's not clear if Suno will use an existing system like Google's Synth ID or adopt a new one, and the company did not say when contacted by TechCrunch about this. The startup also signed an agreement with lyrics provider Musixmatch to use its Sentinel system for copyright detection, the blog post said. [...] The company added that it plans to add a new download policy to bar mass distribution on streaming platforms, but declined to provide details on the record. Suno has also changed its community guidelines to explicitly prohibit "deceptive audio presented as real" and "using a real person's voice or likeness without permission" to prevent copycats.

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