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A simplified library for decentralized, privacy preserving machine learning
| Date | Stars |
|---|---|
| 2026-07-31 | 353 |
| 2026-08-06 | 353 |
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# <d></d> <img style="float: right;" src="docs/images/GettyImages-1148109728_EAA-graphic-A_112_0_72_RGB.jpg?raw=true"/> SWARM LEARNING
#### Product version: 2.3.0
Swarm Learning is a decentralized, privacy-preserving Machine Learning framework. This framework utilizes the computing power at, or near, the distributed data sources to run the Machine Learning algorithms that train the models. It uses the security of a blockchain platform to share learnings with peers in a safe and secure manner. In Swarm Learning, training of the model occurs at the edge, where data is most recent, and where prompt, data-driven decisions are mostly necessary. In this completely decentralized architecture, only the insights learned are shared with the collaborating ML peers, not the raw data. This tremendously enhances data security and privacy.
Swarm Learning nodes works in collaboration with other Swarm Learning nodes in the network. It regularly shares its learnings with the other nodes and incorporates their insights. This process continues until the Swarm Learning nodes train the model to desired state. User can monitor the progress of the current training as shown in the below image. It shows all running Swarm nodes, loss, model metric (for example, accuracy) and overall training progress for each User ML node. On hovering over the "progress bar", one can see the number of completed epochs and the total number of epochs.
<img width="100%" src="/docs/User/GUID-CB6F59C9-7CD9-4EE8-BA7C-3082F07B8491-high.png">
## Architecture
<img align="left" width="60%" src="/docs/User/GUID-899B556F-D33F-42D1-8D0D-37F191715709-high.png"> Swarm Learning framework is made up of various components known as nodes, such as Swarm Learning (SL) nodes, Swarm Network (SN) nodes, Swarm Learning Command Interface (SWCI) nodes, and Swarm Operator (SWOP) nodes. Each node of Swarm Learning is modularized and runs in a separate container. The **nodes represent different Swarm Learning _functionality_ and not physical server nodes**.
- SL nodes run the core of Swarm Learning. An SL node works in collaboration with all the other SL nodes in the network. It regularly shares its learnings with the other nodes and incorporates their insights. SL nodes act as an interface between the user model application (ML node) and other Swarm Learning components. SL nodes take care of distributing and merging model weights in a secured way.
- SN nodes form the blockchain network. The current version of Swarm Learning uses an open-source version of Ethereum as the underlying blockchain platform. The SN nodes interact with each other using this blockchain platform to maintain and track progress. The SN nodes use this state and progress information to co-ordinate the working of the other swarm learning components. Blockchain can be persisted across SN restart to preserve past progress network. User can lookup blockchain and see all history of operations. Users have the flexibility to stop Swarm after training is completed. Once user restarts the SN network, the existing history can be accessed using the `get` or `list` command of SWCI management interface.
**Sentinel Node** is a special SN node. The Sentinel node is responsible for initializing the blockchain network. This is the first node to start.
<blockquote>
NOTE: Only metadata is written to the blockchain. The model itself is not stored in the blockchain.
</blockquote>
- SWOP node is an agent that can manage Swarm Learning operations. SWOP is responsible to execute tasks that are assigned to it. A SWOP node can execute only one task at a time. SWOP helps in executing tasks such as starting and stopping Swarm runs, building and upgrading ML containers, and sharing models for training. For more information about SWOP, see [Swarm Operator node \(SWOP\)](./docs/User/Swarm_Operator_node_(SWOP).md).
- SWCI node is the command interface tool to the Swarm Learning framework. It is used to monitor the Swarm LearninExcerpt of 11,123 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:9faa6c885cbbae38, llm:Repository description and README: 'decentralized, privacy-preserving Machine Learning framework', topics include distributed-computing, distributed-ledger, privacy-enhancing-technologies, deep-learning, machine-learning; README describes training at edge, blockchain to share learnings, Swarm Learning nodes etc.
matched fp:9faa6c885cbbae38, llm:Repository description and README: 'decentralized, privacy-preserving Machine Learning framework', topics include distributed-computing, distributed-ledger, privacy-enhancing-technologies, deep-learning, machine-learning; README describes training at edge, blockchain to share learnings, Swarm Learning nodes etc.
matched fp:9faa6c885cbbae38, llm:Repository description and README: 'decentralized, privacy-preserving Machine Learning framework', topics include distributed-computing, distributed-ledger, privacy-enhancing-technologies, deep-learning, machine-learning; README describes training at edge, blockchain to share learnings, Swarm Learning nodes etc.
matched fp:9faa6c885cbbae38, llm:Repository description and README: 'decentralized, privacy-preserving Machine Learning framework', topics include distributed-computing, distributed-ledger, privacy-enhancing-technologies, deep-learning, machine-learning; README describes training at edge, blockchain to share learnings, Swarm Learning nodes etc.