The Future: Ways to Incorporate AI in Music Production
The era of artificial intelligence is here. Everywhere, AI continues to streamline processes, revolutionize operations, and provide groundbreaking solutions. Music production is no different. From composition to mastering, design to marketing, AI is here. And I don’t think that is a bad thing.
One interesting application of AI comes from ChatGPT, a language model developed by OpenAI. This also happens to be the most known, and easily accessible. It can generate human-like text based on the prompts it's given. If you haven’t used it, imagine sending a text message to the smartest person in the world. And there are a plethora of uses for this ChatGPT, and AI more generally.
ChatGPT showcases how AI isn't just about crunching numbers or data analysis. It's a creative tool that can inspire new ideas, support the songwriting process, and contribute to a deeper understanding of music. Its potential applications are exciting and signal a future where AI acts as a collaborator, not just a tool, in the creative process.
So how can we use AI as musicians?
Here are some areas where AI has proven its potential to musicians, both as artists and marketers, the two hats we need to wear nowadays:
Music Composition: Tools such as OpenAI's MuseNet and AIVA use AI to generate original compositions in various styles and genres. But you can dumb in down even more. Hey ChatGPT, I need a soulful chord progression.
Songwriting and Lyrics Generation: AI can assist in generating song lyrics, with applications like Amadeus Code and LyricStudio offering this capability, ChatGPT certainly won’t struggle.
Mixing and Mastering: AI-powered plugins such as iZotope's Ozone and LANDR can mix and master tracks, allowing producers to achieve a polished sound more efficiently.
Sound Design: AI can assist in creating unique sounds, recalling patches and perhaps if not now but soon, recreating designs. I can envision an version of DALL-E whereby a prompt is given and a sound design is spat back.
Music Recommendation: Streaming platforms like Spotify use AI to analyze listener preferences and recommend songs. Not too dissimilar to the beloved engine behind Netflix, that seems to know what we want to watch next. Let alone ‘the algorithm’ that dictates social media.
Targeted Advertising: AI can analyze demographic data, user behavior, and market trends to identify potential listeners for specific genres or artists. This data can be used to create highly targeted advertising campaigns that reach a more relevant audience, optimizing marketing budgets.
Content Creation: AI can also assist in creating engaging content. For example, it can generate social media posts, emails, or even blog content about an artist or band, saving time and resources.
Music Video Production: AI is also entering the field of music video production. Tools like Runway ML leverage AI to assist in video editing, making the creation of engaging visual content more accessible and efficient.
Chatbots for Fan Interaction: AI-powered chatbots can enhance fan interaction by responding to queries, providing information about releases or concerts, and even selling merchandise or concert tickets. These bots can handle multiple inquiries at once, providing quick and efficient service.
Predictive Analytics: AI can analyze trends to predict future hits, helping labels and artists to focus their marketing efforts on tracks that have the potential to become popular.
Album Art: AI can generate album art. Not only ideas, but the art itself. With the combination of tools such as ChatGPT and DALL-E or MIDJourney, you now have both a creative director and a designer.
An oil painting of a man on a horse composing with a synthesizer. I created this using DALL-E. You can see how close we are to an album cover for a heavy metal band.
Generative Music and AI
Generative music is a term popularized by British musician Brian Eno to describe music that is ever-different and changing, created by a system. These systems, often algorithmic, use a set of rules or instructions to generate and reconfigure sound elements, thereby producing unique pieces each time they run.
Eno has often likened generative music to growing seeds in a garden. The composer acts not as an architect, but as a gardener, planting seeds (instructions) that grow into musical elements. The process is less about constructing a specific composition, and more about designing intelligent systems that yield music.
Eno's work with generative music can be seen as an extension of his pioneering efforts in ambient music, where he created immersive, expansive sonic landscapes. However, where ambient music is typically a static recording, generative music creates an environment that is dynamic and evolving. One of Eno's famous works in this field is "Bloom," an app that generates an endless piece of music based on a few simple user inputs.
While generative music can be performed live, its real strength lies in software that can produce an ongoing, non-repetitive stream of music. This aligns with Eno's fascination with creating works that exist beyond traditional time constraints, and evoke a sense of a perpetual, organic process.
Generative music is the ultimate collaboration between man and machine.
AI tools such as OpenAI's MuseNet are prime examples of this. MuseNet was trained on a large amount of music data from various genres and can generate four-minute musical compositions with ten different instruments. This process represents a significant step in generative music, showing how AI can be used to create complex and compelling musical pieces.
ChatGPT, too, might play a role in the future of generative music. While currently its capabilities are focused on text, similar technology could be used to develop more advanced music-generating AI models. For instance, a future model might not just predict the next word in a sentence, but the next note in a piece of music, taking into account melody, harmony, rhythm, and more, and could be trained on the musicality of some of the greats.
Incorporating generative music systems into music production can open up a world of possibilities. For example, a music producer could use these tools to generate a unique score, fight writers block or create an infinite amount of samples to send straight into the MPC. Alternatively, a live performer might use a generative music system to create an evolving soundscape to accompany their performance.
The combination of AI and generative music offers exciting opportunities for music creation, pushing the boundaries of what's possible in music production. As AI technology continues to develop, we can expect to see even more impressive capabilities in the realm of generative music.
Advantages and Limitations of AI in Music
This is generalised, and limited to my understanding.
| Advantages | Limitations |
|---|---|
| Efficiency: AI can automate routine tasks in music production, freeing up time for creative processes. | Lack of Emotional Depth: AI, as of now, cannot understand or feel emotions, which are crucial in music creation. |
| Speed: AI can quickly generate a large number of ideas, aiding in the creative process. | Originality: There's a risk of over-reliance on AI, leading to music that lacks a personal touch. |
| Accessibility: AI tools are often user-friendly and can be used by individuals without deep technical or musical knowledge. | Intellectual Property Issues: It's unclear who owns the rights to music that's generated by AI. |
As technology advances, the influence of AI on music production will undoubtedly grow. We might see more sophisticated AI composers, smarter mastering tools, and AI applications that we can't even imagine today. However, along with these advancements will come new challenges — legal, ethical, and aesthetic — that will need to be addressed, discussed, and ultimately, we all will need to adapt and accept this as a way of life.
AI in music production presents an exciting landscape full of opportunities and challenges. As we continue to embrace this technology, it's essential for music producers to stay informed about these developments and consider how they might use AI in their own workflows. While AI isn't a replacement for human creativity, it's a powerful tool that can complement and enhance our musical endeavours.
