Sound is one of the world’s richest but least accessible data sources. Most audio exists as a single, tangled mix—impossible to edit for humans and noisy for machines to understand. This talk explores how advances in audio separation are unmixing the world: splitting sound into its component parts so it can be edited, searched, and programmed like code. For humans, this means new creative control, immersive experiences, and copyright-safe workflows. For machines, it provides the fine-grained data needed to power multimodal training, boost speech recognition, and enable entirely new AI applications. By transforming raw sound into structured, usable data, separation is becoming the intelligence layer for audio—laying the foundation for the next generation of media, AI, and human-computer interaction.