Sonilo and Shutterstock are betting that licensed training data could define the future of AI music.
Updated
May 13, 2026 3:39 PM

A human operating a digital turntable. PHOTO: UNSPLASH
As copyright disputes continue to grow around AI-generated music, Sonilo, the world’s first professionally licensed video-to-music AI platform, has partnered with Shutterstock to train its models on licensed music catalogs.
The agreement gives Sonilo access to Shutterstock’s music library for AI model training. According to the companies, it is Shutterstock’s first partnership with a video-to-music AI platform and the timing is significant. AI music companies are facing growing pressure over how their systems are trained. Artists and record labels have increasingly challenged the use of copyrighted music in AI datasets, especially when licensing agreements or compensation structures are unclear.
That tension has created a divide across the industry. Some companies have continued building models around scraped or disputed data. Others are trying to position licensing as part of the product itself.
Sonilo falls into the second group. The company says its models are trained only on licensed material where artists and rights holders have agreed to participate and receive compensation. The Shutterstock partnership strengthens that position while giving Sonilo access to a larger pool of commercially cleared music.
The collaboration also points to a broader change happening inside generative AI. As AI tools move into commercial production, companies are being pushed to show not just what their models can generate, but also where their training data comes from.
Sonilo’s platform is built around video rather than text prompts. The system analyses footage directly, studies pacing and emotional tone, then generates an original soundtrack to match the content. The company says this removes the need for manual music searches, syncing or editing workflows. The generated tracks are cleared for commercial use across social media, branded content and broadcast production.
Shawn Song, CEO of Sonilo, said: "Music has always been the last unsolved layer of video creation, and video has always carried its own soundtrack. We built Sonilo to hear it and compose from it, without a single text prompt. But how we build matters as much as what we build. While others have chosen to take artists' work without permission and charge creators for the privilege, we've chosen a different path—one where artists are compensated from day one. Partnering with Shutterstock reflects that standard. Every model we train meets a bar the music industry can stand behind, because the most innovative AI platforms don't have to come at the expense of the artists who make all of these possible."
For Shutterstock, the deal expands the company’s growing role in generative AI infrastructure. The company has increasingly focused on licensing content for AI systems across images, video and music.
Jessica April, Vice President of Data Licensing & AI Services at Shutterstock, said: "AI innovation depends on access to high-quality, rights-cleared content and trusted licensing partnerships. Sonilo's approach reflects the growing demand for responsibly sourced training data and commercially safe AI workflows. We're pleased to support companies building generative AI products with licensed content and scalable data solutions that help accelerate innovation while respecting creators and rights holders."
The partnership also comes as Sonilo expands into creator and developer ecosystems. Earlier this month, the company launched as a native node inside ComfyUI, an open-source AI workflow platform used by millions of creators. Sonilo also offers API access for integration into creator tools, video platforms, game engines and other AI systems.
As AI-generated music becomes more common across advertising, creator platforms and digital media, the industry’s focus is shifting beyond generation alone. Questions around licensing, ownership and compensation are increasingly shaping how AI music companies position themselves and build trust with creators.
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A planned city explores how real-time data and automation can shape everyday urban systems
Updated
May 1, 2026 2:25 PM

A package being delivered by drone using the Meituan app. PHOTO: ADOBE STOCK
A newly built district in northern China is being used to test how cities function when infrastructure, data and automation are integrated from the ground up. In Xiong'an New Area, traffic systems, public monitoring and urban services are designed to respond in real time rather than operate on fixed rules.
At the centre of this is a traffic management system powered by more than 20,000 roadside sensors. These track traffic flow, vehicle types and congestion levels, feeding data into an AI system that adjusts signals in milliseconds. Official figures show this has reduced the average number of stops per vehicle by half. The system also detects equipment faults, sends alerts and generates maintenance requests without manual input.
Automation extends beyond roads. Drones are deployed across the city for routine monitoring. In the Rongdong district, roadside units release drones that follow fixed patrol routes of around 1.27 kilometres, completing each run in about five minutes. They are used to monitor traffic, detect illegal parking and inspect public spaces. Similar systems operate in parks to track water levels and issue flood alerts, while in some work zones, drones transport packages of up to five kilograms between buildings.
These applications reflect a broader approach: integrating multiple systems into a single, connected urban framework. Unlike older cities where infrastructure evolves in layers, Xiong’an has been built with coordinated digital systems from the outset. This allows transport, maintenance and public services to operate through shared data systems rather than in isolation.
Alongside this, the area is being developed as a technology and innovation hub. Since its establishment in 2017, it has attracted more than 400 branches of state-owned enterprises and over 200 companies working in sectors such as artificial intelligence, aerospace information and digital technology.
This ecosystem supports projects like the “Xiong’an-1” satellite, which completed research, design, production and testing within eight months of regulatory approval in 2025. The satellite is currently undergoing testing, with a planned launch expected in the second quarter of 2026. It forms part of a broader push to build an aerospace information industry in the region.
The area is also structured to bring companies, research and production closer together. At the Zhongguancun Science Park in Xiong’an, which spans 207,000 square metres, 269 technology companies operate across sectors including AI, robotics and biotechnology. The park hosts more than 2,700 researchers and industry professionals, with companies organised into sector-specific clusters.
Policy support continues to shape this development. In early 2026, the State Council approved the upgrade of Xiong’an’s high-tech industrial development zone to national level status, with a focus on attracting high-end research and strengthening links between scientific development and industrial output.
Xiong’an is positioned as a testing ground for how smart city systems can be deployed at scale. The model depends on coordinated planning, integrated infrastructure and sustained policy support. Whether these systems can be adapted to existing cities, where infrastructure and governance are more fragmented, remains an open question.