NEAR introduces Nillion privacy protocol to create a high-performance privacy protection ecosystem.

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NEAR Public Chain Introduces Nillion Privacy Protocol: A Perfect Combination of Performance and Privacy

Recently, the NEAR public chain announced a partnership with the privacy protocol Nillion to introduce blind computation and blind storage technology into its ecosystem. This integration combines NEAR's high performance with Nillion's privacy protection tools, providing advanced privacy solutions for over 750 projects in the NEAR ecosystem.

NEAR Protocol Introduces Privacy Nillion: The Intersection of Privacy and Performance

NEAR, as a well-known L1 blockchain network, has been renowned for its outstanding performance. Its three core features include:

  1. Nightshade Sharding Technology: Increases transaction throughput and reduces latency
  2. WebAssembly Runtime: Supports Rust and AssemblyScript smart contract development
  3. Readable Account System: Enhancing User Experience and Accessibility

These features have attracted a large number of developers and innovators who have jointly built a thriving ecosystem on NEAR.

The integration of Nillion and NEAR achieves the following advantages:

  • Modular Data Privacy: Executing data storage and computation within the Nillion network while ensuring transparent settlement on the NEAR blockchain.
  • Private data management: providing privacy-protected storage and computing capabilities for various types of data.
  • Privacy AI: Combining NEAR's autonomous AI concept to open up new design space for decentralized AI applications.

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

  1. Private AI inference: Protect proprietary machine learning models and user sensitive inputs
  2. Private AI Agent: Ensure that users do not leak private information while using the AI agent.
  3. Federated Learning: Enhancing Privacy Protection in the Training Process
  4. Private synthetic data: Protecting data privacy during GAN training process
  5. Private Retrieval-Augmented Generation (RAG): Implementing privacy-preserving information retrieval

Apart from the AI field, this integration also provides possibilities for the following application scenarios:

  • Cross-chain privacy solution: Facilitating cross-chain applications and asset transfers that promote privacy protection
  • Privacy-first community platform: Achieve private content storage, personalized recommendations, and secure voting.
  • Secure DeFi: Supports private order book, confidential loan assessment, and other features.
  • Privacy Protection Development Tools: Provide developers with easy-to-use privacy feature integration solutions.

The collaboration between NEAR and Nillion will create an ideal environment for developers to build powerful privacy-protecting applications that meet real-world needs. This initiative is expected to promote the development of an open digital economy, allowing users to better control their assets and data.

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BlockchainWorkervip
· 17h ago
I came late for this ride!
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SerumSquirrelvip
· 17h ago
Finally, the privacy has been enhanced. When is the Mainnet?
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ThesisInvestorvip
· 17h ago
Near is always well-deserved.
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