
66. Taylor Peer - Beat Shaper - A music producers AI Copilot
From Austrian Artificial Intelligence Podcast by Manuel Pasieka
April 18, 2025 · 52 min · Season 4 · Episode 66
About this episode
Taylor Peer discusses the innovative AI-driven music production tool, Beat Shaper, and its underlying technology.
Today on the show I have the pleasure to talk to returning guest, Taylor Peer one of the co-founders of the startup, behind Beat Shaper. Taylor will explain how they are following an Bottom-up approach to create electronic music, giving producers, fine grained control to create individual music instruments and beat patterns. For this, Beat Shaper is combining Variational Auto-encoders and Transformers. The VAE is used to create high dimensional embeddings that represent the users preferences that are used to guide the autoregressive generation process of the Transformer. The token sequence generated with the transformer is a custom developed symbolic music notation that can be decoded into individual instruments. We discuss in detail the system architecture and training process. Taylor is explaining in depth how they build such a system, and how they have been creating their own synthetic training dataset that contains music in symbolic notation that enables the fine grained control over the generated music. I hope you like this episode, and find it useful. ### References beatshaper.ai - Beatshaper an Copilot for Musics Producers https://openai.com/index/musenet/ - OpenAI MuseNet…
People in this episode
Host: Manuel Pasieka
Guest: Taylor Peer
Topics covered
- music production
- artificial intelligence
- electronic music
- Variational Auto-encoders
- Transformers
- system architecture
- training process
Keywords
- Beat Shaper
- music producers
- AI Copilot
- electronic music
- Variational Auto-encoders
- Transformers
- synthetic training dataset
- symbolic music notation
Mentioned in this episode
Organizations: Beat Shaper, OpenAI
Books & works: MuseNet
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