Whenever Artificial Intelligence is discussed in the music production sphere, it’s almost exclusively about AI generated music/audio, and how they are worthless, soulless crap only good for YouTube videos or commercials. But I’m afraid that the majority of music makers have not realized what an LLM AI’s true strength is and what it’s meant to be - a productivity tool. The past month saw the introduction of Microsoft 365 Copilot and GitHub Copilot X, which I highly recommend checking out if you haven’t already, and get an idea of what a DAW copilot can look like in the future. It’s not about AI generating an entire wacky and wonky album, but assisting professionals to produce an album better and faster, as just one example.
Here is what GPT-4 has to say about it, and I personally found it fascinating. However many people might sneer at this concept, I hope you, the future facing Elektronaut, can find it at least somewhat inspiring:
In the future, a music production copilot AI could be a highly advanced and versatile tool that assists musicians, producers, and audio engineers throughout the entire process of creating music. Here are some potential capabilities that a music production copilot AI may possess:
1. Intelligent Composition Assistance: The AI could analyze a musician’s creative input, such as melody or chord progression ideas, and provide suggestions for harmonies, chord inversions, and melodic variations to enhance the composition.
2. Sound Design and Synthesis: The AI could generate unique and custom sounds using advanced sound synthesis techniques, and assist in designing sounds for different instruments, synthesizers, and virtual instruments. It could also analyze and identify sounds from audio samples, making it easier to recreate specific sounds or styles.
3. Arrangement and Mixing Assistance: The AI could help with arranging different sections of a song, optimizing the structure, and suggesting transitions. It could also analyze and optimize the mix, providing suggestions for EQ, compression, and other audio processing techniques to achieve a polished and professional sound.
4. Performance and Production Assistance: The AI could analyze and interpret audio recordings of performances, providing feedback on timing, pitch, and expression, and helping musicians improve their performances. It could also assist in the production process, such as automatically aligning and editing multiple takes, or automating repetitive tasks like vocal tuning or drum quantization.
5. Real-time Collaboration and Interactive Feedback: The AI could function as a real-time collaborator, providing instant feedback and suggestions during live recording sessions, jamming sessions, or online collaborations. It could adapt to different musical genres, styles, and preferences, and provide contextual feedback to enhance the creative process.
6. Music Theory and Education: The AI could serve as a comprehensive music theory and education resource, providing information, tutorials, and interactive lessons on various musical concepts, techniques, and genres. It could adapt its teaching approach to the user’s level of expertise and provide personalized guidance for learning and improving musical skills.
7. Creative Inspiration: The AI could generate new musical ideas, melodies, rhythms, and textures based on the user’s input, providing endless creative possibilities and helping musicians overcome creative blocks. It could also analyze and provide feedback on the emotional impact of the music, helping musicians evoke specific moods or emotions in their compositions.
Overall, a music production copilot AI of the future could be a powerful and versatile tool that enhances the creative process, streamlines production workflows, and provides valuable insights and assistance to musicians, producers, and audio engineers. It could revolutionize the way music is created and produced, opening up new creative horizons and possibilities.