Machine learning that runs outside the data center.
Bytes and Brains is a Rust framework for machine learning that runs across many small machines instead of one big cluster: phones, sensors, robots, lab fleets, peer-to-peer overlays.
You write the whole distributed computation once, as a composition of Modules. A compiler partitions it into per-node programs that run wherever the nodes are. It is early, open source, and being built in public.
What you can build on it
// a thought experiment: a nervous system for machinesA fun example of a workload Bytes and Brains was envisioned around.
// in this example: system 1 acts at 120 Hz, system 2 reasons at 10 Hz, system 3 unifies the fleet from the cloud, and action latents gossip over the lan. every arrow is bytes the framework moves for you.
What it is
// the moving partsThe Module
The unit of work. Modules compose into the whole distributed computation, recorded once, instead of hand-writing each node's half of every conversation.
The compiler
Lowers a Module to its own IR, serializable to ONNX, then partitions it into per-node programs: each node gets exactly the piece of the computation it is responsible for.
The engine
A sans-IO engine runs each node's program. It never owns your network or your hardware: you feed it bytes and events, and it tells you what to send.
Roadmap
// what is nextTwo tracks: extensions to the framework itself, and protocols built on its primitives. The list keeps growing as the core stabilizes.
First public release: framework + sans-IO Engine + Wire + role traits + CpuBackend reference.
read the release notes →From the blog
// latest postAI, Velocity, and Trust
On AI velocity, losing the plot, and the trust levels I am using to earn back my own codebase.
read the post →Building in public.
The library is on crates.io and the design lives in the whitepaper. It is early: 0.3 works, and 0.4 is a rework of the core. If you work on federated learning, gossip protocols, or peer-to-peer systems, reach out.
[email protected]