NEAR Blockchain Introduces Privacy Technology: The Fusion of Performance and Privacy

Recently, an important technology integration in the blockchain field has attracted attention. The high-performance public chain NEAR has announced the introduction of advanced blind computation and blind storage technologies, a move that will bring new privacy protection capabilities to many projects within the NEAR ecosystem.

NEAR, as a well-known Layer 1 blockchain network, has always been renowned for its outstanding performance. Its three core features include:

1. Nightshade Sharding Technology: Enhances transaction processing capacity and reduces network latency.
2. WebAssembly Runtime Environment: Supports Rust and AssemblyScript smart contract development
3. User-friendly account system: Use easily readable account names to enhance user experience.

These features have attracted a large number of developers and innovators who have come together to build a thriving ecosystem with over 750 applications.

The introduction of blind computation technology combined with NEAR's efficient transaction processing capabilities will bring the following advantages:

• Modular Data Privacy: Allow flexible execution of data storage and computation operations within privacy networks, while ensuring transparent settlements on the NEAR blockchain.
• Private Data Management: Provides private storage and computing services for various types of data, greatly expanding the design space for privacy protection applications.
• Privacy AI: Complementing NEAR's focus on autonomous AI, opening up new development directions for decentralized AI.

This episode opens up new avenues for privacy protection applications within the NEAR ecosystem, especially in the field of AI solutions:

1. Private AI Inference: Providing secure protection for proprietary machine learning models and user inputs.
2. Private AI Agents: Protecting user privacy information when using AI agents.
3. Federated Learning: Enhancing Privacy Protection in the Training Process of Distributed Datasets
4. Private Synthetic Data: Protecting Data Privacy During GAN Training
5. Privacy-Enhanced Retrieval-Augmented Generation (RAG): Achieving privacy-preserving information retrieval and semantic search

Apart from the AI field, this technology will also play an important role in the following areas:

• Cross-chain privacy solution: Facilitating cross-chain applications and asset transfers that promote privacy protection.
• Privacy-first community platform: enabling features such as private content storage, personalized recommendations, and secure voting.
• Secure DeFi: Supports private order books, confidential loan assessments, and hidden liquidity pools
• Privacy Development Tools: Provides developers with easy-to-use privacy feature APIs to simplify the application development process.

By combining high-performance infrastructure with advanced privacy technology, NEAR is creating an ideal environment for developers to build powerful and privacy-focused applications to meet real-world needs. This initiative is expected to drive the development of an open digital economy, allowing users to better control their assets and data.