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.
Keep Reading
A global survey shows robot anxiety drops when people encounter robots in real life
Updated
April 1, 2026 8:55 AM

Ameca the humanoid robot, featuring a grey rubber face. PHOTO: ADOBE STOCK
People often assume robots make people uneasy everywhere. But a new global study suggests something more nuanced. Robot anxiety tends to be highest in places where people rarely see robots in real life. Where robots are more visible, attitudes are often far more positive. That insight comes from a global study by Hexagon AB, which surveyed 18,000 participants across nine major markets. The research explored how adults and children think about robots and how those views change depending on everyday exposure.
In the United Kingdom, anxiety about robots is the highest among the countries studied. Around 52% of adults say they feel worried that something might go wrong when they think about interacting with or working alongside robots. South Korea sits at the other end of the spectrum, with only 29% reporting similar concerns. One factor appears to explain much of the gap: familiarity.
British adults are among the least likely to have encountered robots in real life. Only about 30% say they have seen or used one. In contrast, countries where robots are more visible tend to report greater comfort. China offers the clearest example. Around 75% of adults there say they have seen or interacted with robots. At the same time, 81% say they feel excited about the technology’s future potential.
The study suggests that attitudes toward robots are not fixed. Instead, they shift depending on where people encounter them and what tasks they perform. When robots are seen solving clear, practical problems, confidence tends to rise.
Across the surveyed countries, adults report the highest comfort levels with robots working in factories and warehouses. Around 63% say they are comfortable with robots in those environments. These are settings where tasks are clearly defined and safety standards are well understood. Acceptance drops in more personal spaces. Only 46% say they feel comfortable with robots in the home, while comfort falls further to 39% when robots are imagined in classrooms.
In other words, context matters. People appear more willing to accept robots when they take on physically demanding or dangerous work. Half of the respondents say improved safety is one of the main advantages of robotics in those environments. A similar share point to productivity gains as another benefit. Another finding challenges a common assumption about public fears. Job loss is often described as the biggest concern surrounding robotics. But the study suggests security risk worries people more.
Around 51% of adults say their biggest concern about robots at work is the possibility that the machines could be hacked or misused. That fear outweighs worries about physical malfunction or injury, which stand at 41%. Concerns about being replaced at work appear at the same level.
For many respondents, the issue is not simply whether robots can perform tasks. It is whether the systems controlling them are secure. According to researchers involved in the study, these concerns reflect how people evaluate emerging technologies. Instead of having a single opinion about robotics, people tend to judge each situation individually.
A robot helping assemble products in a factory may feel acceptable. The same technology operating in more sensitive environments can raise different questions. Dr. Jim Everett, an associate professor in moral psychology, says trust in artificial intelligence and robotics is often misunderstood. People are not simply asking whether they trust the technology, he notes. They are thinking about specific tools performing specific roles.
A robot assisting in a classroom or helping in healthcare carries different expectations than an AI system used in defense or surveillance. Even though these technologies are often grouped together in public debates, people evaluate them differently depending on their purpose.
Finally, the study also highlights another important factor shaping public attitudes: experience. When people actually encounter robots, fear often declines. Michael Szollosy, a robotics researcher involved in the project, says reactions tend to change quickly when individuals meet a robot for the first time.
The idea of an autonomous machine can feel intimidating in theory. But when people see a small service robot or an industrial machine performing a straightforward task, the reaction is often much calmer. Exposure can shift perceptions from abstract fears to practical understanding.
That shift matters because robotics is moving steadily into everyday environments. From manufacturing and logistics to healthcare and public services, machines capable of autonomous or semi-autonomous work are becoming more common.
As that happens, the study suggests public confidence may depend less on technical breakthroughs and more on visibility and transparency. Burkhard Boeckem, chief technology officer at Hexagon AB, argues that trust grows when people understand what robots are designed to do and where their limits lie.
Anxiety tends to increase when systems feel invisible or poorly understood. Clear boundaries and clear explanations can have the opposite effect. When people see robots working safely alongside humans, performing well-defined tasks and operating within clear rules, the technology becomes easier to accept.
In that sense, the future of robotics may depend as much on public familiarity as on engineering. The machines themselves are advancing quickly. But the relationship between humans and robots is still being negotiated. For now, the study offers a simple insight: the more people encounter robots in everyday life, the less mysterious they become. And once the mystery fades, the conversation often changes from fear to curiosity.