In 2022, we introduced the concept of a compute protocol for machine learning and how it could be built. In 2023, we expanded on our vision for a machine learning compute protocol. One that connects every device in the world into an open network for machine intelligence, with no gatekeepers or artificial boundaries.
Now, we’re sharing our progress in public, with solutions to the core challenges:
Consistent Execution, ensuring compatibility across any device;
Trustless Verification, checking and agreeing on work performed in a scalable way;
Efficient Communication, sharing workloads between devices over the internet; and
Decentralised Coordination, identifying participants, aligning incentives, and managing attribution.
The Gensyn Protocol brings these components together into a single network for open machine learning - accessible to humans and machines alike and scalable to every computer in the world.
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Execution
RL Swarm
A peer-to-peer system for collaborative reinforcement learning over the internet, accessible by anyone on consumer or datacentre hardware.
An arbitration system for machine learning over untrusted nodes, enabled by RepOps, a library for bitwise reproducibility across heterogeneous devices.
A framework for training mixture-of-experts models in a parallel fashion, showing that introducing heterogeneity into the training process yields a better-performing ensemble.
A custom Ethereum rollup dedicated to machine learning and integrated with off-chain execution, verification, and communication frameworks. The network for machine intelligence.
