Open Information Distribution Protocol

The vision of the Open Information Distribution Protocol is to create a privacy-protective, open, practical, and composable information distribution protocol that frees users from the information cocoons brought by centralized giants. It has the following objectives:

• Privacy Protection: Usage data from users will not be leaked.
• Openness: Any third party can participate. The protocol is not controlled by any party, not even Terminus.
• Practicality: The recommendation algorithm must be effective.
• Generality: In addition to text content, it can also accommodate videos, music, and products for recommendations.
• Composability: Supports protocol modularization to reduce redundant computation while enhancing personalization.

You can try out the demo-level recommendation algorithm provided by the Terminus team at Wise.

Design Philosophy

A New Paradigm for Recommendation

The Open Information Distribution Protocol divides the recommendation process into two stages:

1. Content Providers in the cloud collect and vectorize global content, subsequently packaging it for user download.
2. Terminus downloads the data and uses locally-executed algorithms and local user interaction data for content recommendation.

As each Terminus device receives identical data from Content Providers and operates recommendation algorithms locally without internet, user feedback remains confidential.

Local Recommendation Framework

The recommendation framework running on Terminus orchestrates the Recommendation algorithms installed from the Market, ensuring these algorithms operate in a network-free sandbox environment.

Proof of Intelligent Contribution

The recommendation framework aims to establish a Proof of Work mechanism that fairly rewards users who actively contribute gradient data for model training, thereby advancing algorithms through federated learning.

Open Source Repo

• recommend-system-module: This is the internal recommendation system framework running within Terminus.

• r4: This is a demo algorithm developed by the Terminus team to illustrate the workflow of the recommendation framework.

• article-extractor: This module is responsible for extracting body texts from web pages.