In the evolving landscape of generative AI music, the challenge of attribution emerges as a critical concern. At SOMMS.AI, as we further refine our customer’s custom music models, we have a front row seat in witnessing their capabilities to generate music with artificial intelligence that sounds authentic.  As a result, there becomes a pressing need to recognize the foundations upon which these generations stand: human creativity.

AI-generated music does not emerge from a vacuum. Every track, every melody, every harmony generated by our music models has their roots in human-created music. This music, sourced ethically, with the consent of the various artists that are in the rosters of our customers, shape the very essence of what our AI produces. Consequently, it is imperative to ensure that these sources are recognized and attributed appropriately.

Therefore, we have invented a state-of-the-art attribution system designed to bridge this gap. By providing attribution, our system ensures that individual creators and rights-holders are recognized when AI music reflects their influence. This is not just about financial compensation; it’s about preserving the integrity of artistry and recognizing the dedication of musicians whose work has been instrumental in training these models.

In the discourse surrounding AI music attribution, a contentious point often emerges: the argument for exact mathematical attribution. Critics claim that without precise, mathematical delineation, true attribution remains elusive. However, this stance is a red herring. Music, in its very essence, is a blend of mathematics and emotive artistry, and attempting to reduce its nuances to algorithms oversimplifies its complexity. By blending tech advancements with a nuanced understanding of the business of music, our system is a blueprint for how the future of attribution can and should be approached.

I would argue that what we’ve invented at SOMMS.AI points to something essential in the broader Generative AI / AGI industry landscape. As a small startup, we have successfully navigated the complexities of AI and music to offer a solution that respects both artistry and technology. Given our scale and resources, it is implausible to argue that larger companies with billion dollar valuations, and with significantly more substantial technological and financial means, could not achieve similar results. The question then isn’t about capability, but rather, intent and prioritization. The onus is on all service providers, big and small, to adopt, support, and further innovate upon the standard that SOMMS.AI has set, ensuring a future where AI-generated music is attributed fairly and transparently.

While we have laid the groundwork, industry-wide standardization is paramount. Though it’s a good start, it is not enough for individual companies like ours to have their own siloed systems. There must be a universally accepted methodology, similar to how Performing Rights Organizations operate for live music. Such a unified system would ensure that all creators, irrespective of their association, receive the acknowledgments they deserve.

The role of legislative bodies cannot be understated in this scenario. As AI continues to reshape the music industry, it is essential that policies evolve in tandem to protect the rights of artists. Laws should be in place to ensure the ethical use of music for training AI models.

In summary, as we stand on the cusp of a new era in music, defined by the capabilities of generative AI, it is our collective responsibility to ensure that the essence of music – human creativity – remains respected and recognized. SOMMS.AI extends an invitation to industry stakeholders, artists, and policymakers to collaborate and establish a standardized attribution system. We must move forward with precision, clarity, and integrity, ensuring that music emerges stronger in the age of AI.