SIWA Public Testnet Now Live!
The SIWA public testnet has officially gone live! SIWA is a public testnet designed for decentralized AI development and represents the first step towards an open, fair, and accessible AI-driven future.
Roadmap to Mainnet
The SIWA platform will progress through four phases to ultimately reach the mainnet.
Phase One: Currently, vast amounts of data are used for algorithm training, yet contributors often do not receive adequate compensation. This phase aims to achieve transparency in data flow and fair value distribution.
Phase Two: Data sets and models will be made interoperable on-chain.
Phase Three: An open testing environment will be launched, and the technical protocols will be open-sourced.
Phase Four: A robust data provenance mechanism and contribution certification system will be perfected.
Each phase will expand the platform's functionality, gradually building a more open and transparent intelligent economic ecosystem.
Introduction to Sahara AI
Sahara is a decentralized network platform dedicated to creating an open, secure, and privacy-focused intelligent service ecosystem. The platform allows users to freely build personalized intelligent knowledge assistants (Sahara KA), helping individuals and organizations transform and automate the application of knowledge value.
How Sahara AI Works
The Sahara platform features a dual-layer architecture designed to provide secure technical support for AI applications:
Core Execution Layer
Data processing is achieved through a distributed node network, supporting model optimization and privacy protection.
Encryption and digital watermarking are used to ensure data ownership is traceable.
Secure data storage and transmission solutions are provided, including homomorphic encryption and other privacy-preserving computing capabilities.
Open Application Layer
An integrated data service platform supports data collection, labeling, and quality management.
Customizable intelligent assistant development tools are provided for enterprise-level AI application deployment.
An innovative collaboration mechanism allows developers to share AI models and achieve value transformation.
The platform has already provided data services to multiple institutions and will continue to optimize its toolset to promote the development of a distributed intelligent ecosystem.
Sahara AI Team
Sean Ren is the co-founder and CEO of Sahara.
Tyler Zhou is the co-founder and COO of Sahara, a graduate of the University of California, Berkeley.
Sahara AI Funding
On August 14, 2024, Sahara completed a $43 million Series A funding round.
On March 5, 2024, Sahara completed a $6 million seed funding round.
Summary of Sahara AI
The core value of AI data annotation lies in providing high-quality data for algorithm training, which is key to improving model accuracy. The Sahara platform, through its innovative collaboration mechanism, enables users to participate in AI development and share in the value created. Although decentralized intelligence still faces challenges such as data standardization and security, it has advantages in privacy protection and fair incentives. As the platform continues to optimize, more open services will be launched in the future to promote the widespread application of intelligent technologies.
