Lifeboat Foundation

A network-theory model, tested on the work of Johann Sebastian Bach, offers tools for quantifying the amount of information delivered to a listener by a musical piece.

Great pieces of music transport the audience on emotional journeys and tell stories through their melodies, harmonies, and rhythms. But can the information contained in a piece, as well as the piece’s effectiveness at communicating it, be quantified? Researchers at the University of Pennsylvania have developed a framework, based on network theory, for carrying out these quantitative assessments. Analyzing a large body of work by Johan Sebastian Bach, they show that the framework could be used to categorize different kinds of compositions on the basis of their information content [1]. The analysis also allowed them to pinpoint certain features in music compositions that facilitate the communication of information to listeners. The researchers say that the framework could lead to new tools for the quantitative analysis of music and other forms of art.

To tackle complex systems such as musical pieces, the team turned to network theory—which offers powerful tools to understand the behavior of discrete, interconnected units, such as individuals during a pandemic or nodes in an electrical power grid. Researchers have previously attempted to analyze the connections between musical notes using network-theory tools. Most of these studies, however, ignore an important aspect of communication: the flawed nature of perception. “Humans are imperfect learners,” says Suman Kulkarni, who led the study. The model developed by the team incorporated this aspect through the description of a fuzzy process through which a listener derives an “inferred” network of notes from the “true” network of the original piece.

Researchers used artificial intelligence to decipher the text of 2,000-year-old charred papyrus scripts, unveiling musings on music and capers.

Google has launched Gemini, a new artificial intelligence system that can seemingly understand and speak intelligently about almost any kind of prompt—pictures, text, speech, music, computer code, and much more.

This type of AI system is known as a multimodal model. It’s a step beyond just being able to handle text or images like previous algorithms. And it provides a strong hint of where AI may be going next: being able to analyze and respond to real-time information from the outside world.

Although Gemini’s capabilities might not be quite as advanced as they seemed in a viral video, which was edited from carefully curated text and still-image prompts, it is clear that AI systems are rapidly advancing. They are heading towards the ability to handle more and more complex inputs and outputs.

Take a cassette and enjoy the experience.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 The world’s largest music label has yanked its artists’ music off TikTok Universal Music Group claims TikTok is unwilling to compensate musicians appropriately. (The Guardian) + Taylor Swift fans are kicking off. (Wired $) + Indie record labels don’t like the sound of Apple’s pay plans either. (FT $)

https://www.youtube.com/watch?v\u003dON8vxUInQYA\u0026si\u003d7bam3JUgkIjDhzvz

TikTok built its empire off popular music — but now it’s losing access to a ton of it.

In a statement, Universal Music Group said it has chosen to “call time out on TikTok” to pressure the social network for better rules on artificial intelligence, online safety, and artist compensation for its roster, which includes such luminaries as Taylor Swift, Drake, and BTS.

“Today, as an indication of how little TikTok compensates artists and songwriters, despite its massive and growing user base, rapidly rising advertising revenue and increasing reliance on music-based content, TikTok accounts for only about 1 percent of our total revenue,” the statement reads.

“Bodily maps of musical sensations across cultures”

Emotions, bodily sensations and movement are integral parts of musical experiences. Yet, it remains unknown i) whether emotional connotations and structural features of music elicit discrete bodily sensations and ii) whether these sensations are culturally consistent. We addressed these questions in a cross-cultural study with Western (European and North American, n = 903) and East Asian (Chinese, n = 1035). We precented participants with silhouettes of human bodies and asked them to indicate the bodily regions whose activity they felt changing while listening to Western and Asian musical pieces with varying emotional and acoustic qualities. The resulting bodily sensation maps (BSMs) varied as a function of the emotional qualities of the songs, particularly in the limb, chest, and head regions.

https://www.youtube.com/watch?v\u003dsDD_VcxmToE

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