The art of music permeates the globe as a universal expression, but as of late, advances in AI and IoT are elevating it from simply an art form to a whole new echelon rooted in science. What if listening to music was more than just a leisure pastime, and a song was more than just a choice of preference.
Rubato.life, a new LA-based startup, released their beta application SDK last week that enables wearable devices and music content providers to recommend music according to a listeners’ physiological and psychological state and ultimately enrich their well-being.
“We are changing the way music is currently consumed, from simply listening, to channeling a smart use of music in order to manage stress, improve sleep quality, and optimize your well-being,” explained Rubato CEO, Amit Sternberg, who founded the startup in 2019 with co-founder and CTO, Noam Guy. An educated musician, Sternberg, along with growing scientific studies, assert music’s categorical influence on the human brain and body. Considering a projected 526.8 million wearable device shipments in 2024, the biometric consumer data deluge coupled with advances in AI techniques have given biofeedback and predictive power in music new meaning.
Yet, the application of AI for music dates back around the same time the discipline was coined, mainly for the task of algorithmic composition and composing music based on previously fed songs. Over the last decade, countless projects have demonstrated the increasing acceptance of these techniques in practice. Examples include Eurovision's submission last year, Sony's Beatles-esque song, Pierre Barreau’s AIVA-based songs, or OpenAI’s new GPT-based Jukebox library. A handful of startups share the same ambition, like Amper Music's entire album and Landr's music creation tool, which combined have attracted a host of artists to adopt into their workflow. Despite these advances, meager progress has been made on the consumer’s experience front. Music recommendation systems of the top content providers, such as Spotify’s among many others, are based on usage history, audio data, demographic and social data, all devoid of indicators on the real-time state of the user.
“Naturally, everyone’s different and their reaction to music is unique,” explained Sternberg. “Some listener’s feel a dopamine rush in a song’s specific melody, while the resolve from an opera stimulates creativity for others.” According to Sternberg, these moments are no longer intangible, rather, they’re measurable, and predictable.
