Federity Overview

Federity is a version control platform for collaborative machine learning that ensures data privacy by training models locally and aggregating only updates globally. Each training iteration is treated as a verifiable "commit," allowing versioning, undoing changes, and tracking progress. It supports merging commits from different branches, enabling the integration of training done on diverse datasets. Models are tokenized as NFTs for ownership and trading, with zero-knowledge proofs validating every update and merge.

Federity is a platform designed for version control and collaborative machine learning that emphasizes data privacy. Here's how it works, with some similarities to GitHub:

• Local Training: Models are trained locally on individual datasets, so the data never leaves the user's location, ensuring privacy.
• Aggregator Updates: Only the model updates, not the data, are sent to a central server for aggregation.
• Verifiable Commits: Every training iteration is treated like a "commit." This allows you to track changes, revert to previous versions, or monitor progress over time, much like how GitHub handles code commits.
• Branch Merging: Federity supports merging commits from different branches, enabling seamless integration of training results from various datasets.
• Tokenized Models: Models are turned into NFTs, providing a unique, tradable, and provable ownership mechanism.
• Zero-Knowledge Proofs: Federity uses zero-knowledge proofs to validate updates and merges, ensuring that all changes are legitimate without revealing the underlying data.

Why Federity

Federity is a blockchain-based platform designed for collaborative machine learning on highly sensitive data, like hospital patient records. It allows users to train machine learning models using their private data without sharing it with anyone. Instead, the server sends a lightweight version of the machine learning model to the user's device, where training occurs locally. Only the model updates—no actual data—are sent back to a central server for aggregation. Users can choose whether to merge or revert these updates, similar to version control on GitHub.

Because it built on the Solana blockchain, every user is identified by his Solana wallet, ensuring transparency and complete control over his models. Federity functions like a community-driven AI, but with the blockchain's privacy protections, keeping personal data safe from external access.

Get Started

Here's how to get started:

• First, create a new repository and upload your machine learning model, whether it's built on Pytorch, TensorFlow, or any other framework!
• Next, invite your contributors to join the party—they can train the model right alongside you.
• As they work their magic, they'll submit their updates as commits for you to review and integrate.
• Or you can join someone else's repository and help evole the ML models using your local training. Happy collaborating!