NEAR Public Chain Introduces Privacy Technology: An Innovative Fusion of Performance and Privacy

A certain privacy protocol recently announced the integration of blind computation and blind storage technology into the L1 public chain NEAR, which is known for its speed and scalability. This integration combines NEAR's high performance with advanced privacy tools, allowing over 750 projects in the NEAR ecosystem to leverage blind computation technology.

NEAR is a mature L1 blockchain network known for its outstanding performance. Its three core features include:

1. Nightshade Sharding: A unique sharding solution that increases transaction throughput and reduces latency, suitable for high-performance applications.
2. WebAssembly Runtime: A Wasm-based virtual machine supports the development of smart contracts in Rust and AssemblyScript.
3. Readable Accounts: Adopting an intuitive account naming system to improve user experience and accessibility.

These features have attracted numerous developers, entrepreneurs, and creators to collaboratively build a thriving application ecosystem.

By integrating blind computing capabilities with NEAR's efficient transaction processing, the following advantages have been achieved:

• Modular Data Privacy: Privacy features seamlessly integrated with NEAR allow for modular execution of data storage and computation in a privacy network, while enabling transparent settlement on the NEAR blockchain.
• Private Data Management: Provides confidential storage and computation for various types of data, expanding the functionality of NEAR.
• Private AI: NEAR's focus on autonomous, user-owned AI complements its private storage and computing capabilities, opening up new design space for decentralized AI.

This integration opens new avenues for privacy protection applications within the NEAR ecosystem, especially in terms of AI solutions:

1. Private AI:

   • Private Inference: Achieve secure inference on AI models, protecting proprietary machine learning models and user sensitive inputs.
   • Private Proxies: With the rise of AI agents, privacy solutions have become crucial.
   • Federated Learning: Enhances privacy by protecting the aggregation process, ensuring sensitive information remains confidential during training.
   • Private synthetic data: Protect the privacy of the underlying data during the GAN training process.
   • Private Retrieval-Augmented Generation (RAG): An innovative privacy-preserving approach for information retrieval.

2. Cross-chain privacy solutions: Paving the way for privacy-protecting cross-chain applications and asset transfers.

3. Privacy-first community platform: Combining the advantages of decentralization and privacy protection to achieve private content storage, personalized recommendations, and secure community management.

4. Secure DeFi: Implement private order books, confidential loan assessments, and hidden liquidity pools to enhance the security and privacy of the NEAR DeFi ecosystem.

5. Privacy-focused Developer Tools: Provides privacy-centric tools and APIs to help developers integrate advanced privacy features into their applications.

By combining NEAR's high-performance infrastructure with advanced privacy technology, an environment is being created that enables developers to build powerful, privacy-protecting applications to meet real-world needs. This will help create a new open digital economy, allowing users to have better control over their assets and data.