AITech Interview with Markus Schwarzer

In an interview with Markus, CEO of Cyanite, we explore the AI-powered music transformer model and its potential to transform the music industry. Learn more!

With AI technology transforming various industries, the music industry is no exception. Markus and his team at Cyanite have been working on a revolutionary AI-powered music transformer model that promises to disrupt the way we listen to and search for music and deliver the right music content regardless of the use case. In this interview, we dive deep into the fascinating world of AI in music, discussing everything from the technology behind Cyanite’s music transformer model to the impact it will have on the music industry.

How do you ensure that Cyanite’s AI models are unbiased and free from algorithmic biases?

That is a really important question for us. In fact, our Chief of Data Roman is driving the conversation internally on how to best mitigate biases both from the data as well as the creators (us). The algorithms are only as good as the input data, so we are trying to get data from around the globe and not just the West. The fact we have customers from Korea, Japan, China, Dubai, South Africa, Colombia, Kazakhstan, and Brazil speaks to this work and is a big success for us.

How does Cyanite partner with music industry stakeholders such as record labels, streaming services, and artists?

As mentioned, most recommendation algorithms were built for music consumption in B2C. They’re not necessarily great for B2B use cases as they’re not targeted enough and don’t deliver any data insights on the music like the emotional effect etc. Our algorithms are specifically tailored to the language of advertisers, marketeers, or music supervisors. When a music company/rights holder wants to make it easier for the demand side to find their music and make an informed music decision, they come to us. We run their entire catalog through our engine and make a kind of B2B Spotify out of it. Afterward, they can answer music briefs easier and back up their decision using our detailed data insights.

Can you describe the technical architecture of Cyanite’s AI-powered music analysis platform?

The core of our tech is artificial intelligence which is based on transformer models. You will know these models from other products like Midjourney, ChatGPT, or Dall-E. We had an initial training process where our AI was taught any given feature that can be a denominator for music and sound. From this layer, we derive all our insights into music. It’s highly flexible and can be tailored to a customer’s specific language or use case. We provide this service via an API, our own web app, or the AWS marketplace.

How do you ensure the quality and accuracy of the music metadata generated by your platform?

We have a meticulous quality assurance mechanism where we run the analysis results of new machine learning models through a variety of automated and manual testing including a qualitative survey of music supervisors.

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In the next few years, artificial intelligence (AI) is going to take over many aspects of marketing. From personalized ads and customer service to predictive analytics and content creation, AI will change the landscape of marketing as you know it.