Decentralized & Collaborative AI on Blockchain
A blockchain framework for hosting and collaboratively training publicly available machine learning models with free predictions.
What is Decentralized & Collaborative AI on Blockchain?
Sharing Updatable Models (SUM) on Blockchain is a framework that enables the hosting and collaborative training of machine learning models on a blockchain. It allows users to freely query models for predictions while contributing data through a validated process to improve model accuracy over time. The system uses smart contracts to manage data storage, model updates, and incentive mechanisms to ensure quality contributions.
Researchers and developers working on decentralized AI, blockchain applications, or collaborative machine learning systems who need transparent, publicly accessible models. It's also suitable for those exploring incentive mechanisms for data curation in open ecosystems.
It provides a unique blend of blockchain transparency with machine learning, offering free model predictions and a structured way for the community to improve models collaboratively. Unlike traditional centralized ML services, it ensures data permanence and public access while mitigating spam through built-in incentive mechanisms.
Overview
Sharing Updatable Models (SUM) on Blockchain
Use Cases
Best For
- Building publicly accessible machine learning models with free prediction APIs
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