AITrainingDAOonchain

Our team builds AGI-Git, an innovative open-source platform for storing, sharing, and evolving AI models. featuring: 1- Advanced version control for copyright and collaboration clarity. 2- Extremely efficient storage and communication by saving only version differences. 3- Decentralized nostr protocol for data integrity and availability. 4- Economic incentives for model evolution and access. 5- Future integration with decentralized computing for on-platform training.

Decentralized HuggingFace (Nostr-based decentralized AGI model storage protocol + AGI Git version control + SAAS private model Tokenomics) AGI as a Service, GIT as a Service

AI is poised to significantly reshape various aspects of our digital world, with novel AI applications and interaction methods transforming traditional software and the web3 ecosystem. Models serve as the foundational framework for these applications, dictating the level of intelligence and user experience.

To foster the creation and sharing of high-quality models, our team is dedicated to developing an open-source, distributed platform for model storage and sharing called AGI-Git. This platform offers the following features and advantages:

1. Version control, which facilitates the establishment of copyright and clarifies contributions within collaborations;
2. Efficient storage management by storing only the differences between new and old versions, thereby conserving storage space and reducing communication data;
3. A decentralized relay protocol called nostr: Each data segment is processed with error-correcting codes and split into k parts, which are redundantly distributed across n relays. Statistically, users can recover the complete data by randomly selecting m relays from the total n (n > m > k). A single relay can store parts of multiple open-source models;
4. Economic incentives: Anyone contributing to the evolution of models can benefit financially from sharing on the platform. Manufacturers or individuals in need of models can purchase model files at various prices, while nodes providing storage and uploading services will receive corresponding rewards;
5. Future integration with decentralized computing could incorporate model training components into the platform.