Bring paths together
Support systems made from multiple processing paths while keeping their roles clear and their interaction manageable.
A research routing component for coordinating specialized processing paths inside composable intelligence systems.
Harmony explores a clean coordination layer for models built from reusable MLBricks components. The project focuses on helping different processing paths work together while keeping model construction flexible, understandable, and open to experimentation.
[ ABOUT HARMONY ]
Harmony investigates how reusable model components can be coordinated without turning the surrounding system into a rigid, one-purpose design.
Support systems made from multiple processing paths while keeping their roles clear and their interaction manageable.
Keep routing compatible with modular model construction so components can be combined, replaced, and studied independently.
Make room for interfaces that help researchers and students see how work moves through a routed system.
[ RESEARCH DIRECTION ]
Harmony is currently a research component. The emphasis is on modularity, adaptable model flow, practical experimentation, and compatibility with evolving MLBricks systems.
Explore model designs where different processing components can focus on different kinds of work within one larger system.
Keep the coordination layer useful as researchers add, remove, or reorganize components during experimentation.
Encourage model structures that can be inspected and explained instead of hiding coordination behind a single opaque block.
Study when coordinated model paths can help a system focus its active processing on the components most useful for a task.
The project is focused on understanding where coordinated routing is useful across modular MLBricks systems. Capabilities, interfaces, and performance characteristics may evolve as the research develops.
[ HARMONY / RESEARCH ]
Harmony is MLBricks' research direction for coordinating modular processing paths while keeping the surrounding system flexible enough for new model designs and new experiments.