At Cypher 2024, Siddharth Bhardwaj, Co-founder and CEO at Beatoven.ai, discussed the evolving landscape of music creation, with a focus on generative music technologies. His session explored the historical context of music creation, the challenges artists face in today’s fast-paced digital world, and how AI is reshaping the industry. With the rise of automated tools for background music, the session highlighted how technology is democratizing music production and bridging the gap between creativity and technical skills.
Core Concepts
Music creation has evolved significantly, beginning with folk traditions where communities played an active role. Over time, music shifted into a specialized domain, eventually leading to the commoditization of music through recording technologies. The speaker outlined how, before the invention of recording, live orchestras were the primary way to experience music. The introduction of recording equipment allowed artists to experiment more, and editing became more accessible, enabling complex compositions and multi-layered tracks.
The most significant shift in recent decades has been the transition from analog to digital, which eliminated physical tape and made editing far more efficient. With the rise of digital music production, tools such as MIDI (Musical Instrument Digital Interface) enabled seamless communication between software instruments, thus creating opportunities for home studios and democratizing music production.
Challenges and Solutions
The speaker also touched on the modern challenges faced by music creators, particularly in the age of streaming platforms. With millions of tracks being uploaded daily, artists are tasked with capturing listeners’ attention quickly. Shorter songs, with hook-centric structures, have become the norm to meet the demands of algorithm-driven platforms like Spotify and TikTok, which prioritize frequent content over creativity.
To fill the gap between an artist’s creative ideas and their technical abilities, generative AI tools are becoming increasingly important. These tools allow creators to generate music based on simple text prompts, offering flexibility to those without formal musical training. By providing automatic mixing, mastering, and even generating melodies from humming, AI tools are helping artists produce professional-grade content more efficiently.
Implementation Insights
For artists looking to incorporate generative AI into their workflow, several practical steps were shared during the session. First, creators can use AI for initial composition tasks, such as generating background scores for audiovisual content. Best practices include starting with text prompts to describe the desired mood or genre, and then refining the output by layering different instruments or sounds.
The speaker emphasized the importance of experimenting with AI-powered co-creation tools, which allow musicians to combine genres or styles that might otherwise be outside their expertise. For example, an artist working on a video set in ancient Egypt could use AI to generate historically accurate music by inputting descriptive prompts and modifying the results.
AI tools also streamline post-production tasks like mixing and mastering, which were previously time-consuming and required specialized skills. Tools like automatic mixing can handle these steps with precision, while offering creators more time to focus on the creative aspects of their work.
Industry Impact
Generative tools are not only changing how artists create but also how the music industry functions. With AI enabling rapid content creation, there is an increasing number of “bedroom producers” who are bypassing traditional recording studios. This democratization of music creation has led to a boom in independent music, allowing small creators to compete with established artists on streaming platforms.
AI has also opened up new revenue streams, such as licensing voices for songs or generating music tailored to specific playlists. For example, the speaker mentioned that some artists are making significant earnings by creating music specifically designed for playlist placements, rather than traditional album releases.
Looking ahead, AI is expected to play a larger role in both passive listening experiences—such as background music in retail environments—and active listening, where listeners engage deeply with the story behind the music. However, the speaker predicted that while AI-generated music will dominate passive listening, human-driven, story-rich music will continue to thrive in active listening scenarios.
Conclusion
The session concluded with key takeaways on the role of AI in music creation. As AI lowers the barriers to entry for new creators and streamlines the production process, it is likely to continue reshaping the industry. Yet, human creativity and storytelling will remain central to music that resonates with listeners on a deeper emotional level. Reflecting on this evolution, Siddharth highlighted the need for ethical considerations in AI music production, particularly around copyright and ownership issues. As the industry continues to adapt, creators who leverage AI while maintaining their unique artistic voices will be best positioned to succeed in the new landscape.
