2.Sender Network

Sender Network is an AI-Centric decentralized AI transaction execution network, built on the OP Stack, combining innovation, revolution, and leadership as a cutting-edge AI+Web3 innovative project. It is supported by the globally renowned AI pioneer public chain Near Protocol, providing modular core component functions such as DA (Data Availability), Interoperability, and Chain Abstraction, and is driven by a decentralized free market of Solvers.

Sender Network provides users with a seamless, intelligent, and highly optimized trading environment by combining advanced AI technology, efficient transaction path optimization, and smart contract execution. Its core features include an AI large model natural language interaction interface, AI-driven complex intent parsing, dynamic Solver bidding mechanism, and powerful chain abstraction user experience integration, among others.

Sender Network not only significantly simplifies complex blockchain operations, making them easy to use for ordinary users, but also achieves optimal execution of transactions through its unique Solver network. This breakthrough design significantly lowers the barrier to entry for blockchain technology while improving transaction efficiency and cost-effectiveness. Additionally, it provides developers with various convenient and efficient development SDKs and API toolkits for developing and deploying smart AI agents.

Based on Near Protocol's advanced technological support, Sender Network is building the next generation of AI and Web3 combined decentralized free market. While reshaping decentralized finance (DeFi), it will activate AI's high-performance, dynamic optimization, and super-intelligent features, fully activating various application markets including games and payments.

In this rapidly evolving digital world, Sender Network is poised to become a key bridge between traditional users and the blockchain world, leading the innovative wave of AI+Web3 and bringing far-reaching transformative impacts to the entire blockchain ecosystem.

Sender Architecture

2.1 Settlement Layer

2.11 APOS: Adaptive Proof of Stake: AI-driven adaptive proof of stake mechanism:

APOS consensus mechanism is an advanced variant of Proof of Stake (POS) with dynamic validator weight adjustment, machine learning prediction models, adaptive parameter adjustment, network contribution evaluation, and other aspects. It can leverage AI large models to dynamically optimize network security, efficiency, and degree of decentralization.

2.12 Multi-Agent Consensus: Multi-AI agent collaborative validation system

The multi-AI agent collaborative consensus system involves AI Agents in the block validation and generation process. It includes a distributed AI agent network and collaborative block validation mechanism, as well as dynamic role assignment, greatly improving the system's degree of decentralization and resistance to attacks.

• The system continuously monitors the performance of each AI agent validator, including online time, response speed, block production accuracy, etc.

• The weight of AI agent validators is composed of the number of staked tokens + AI-evaluated reputation score.

• A continuously learning AI large model analyzes network node validation behavior, including detecting suspicious activities, adjusting validator reputation scores, triggering security protocols, etc.

• The system can dynamically assign AI agent validator roles to prevent a single agent from gaining too much power.

• AI agents can operate in a modular fashion, acting as sequencers, block builders, block MEV-Boost, block security monitors, and other enhanced chain functions.

• The minimum staking requirement for AI agents can be dynamically adjusted by the system based on network status.

• When multiple AI agents have conflicting states, the system makes dynamic adjustments based on network stability.

2.13 Security and Privacy: Software and hardware-level security and privacy protection measures

2.131 Enclave isolation technology

• Utilizes hardware-level secure enclaves (such as Intel SGX) to protect the data privacy and security of AI large models and Agents.

• Ensures AI agents operate in a secure environment, preventing external interference and internal data leakage.

• Supports remote attestation, allowing network participants to verify the integrity of AI agent computations and validation data.

2.132 Verifiable Computing and Zero-Knowledge Proofs

• Uses ZKP technology to prove the correctness of AI agent validation behavior while protecting privacy.

• Achieves verifiability of AI large model computation results without exposing raw data or model details.

• Allows network participants to permissionlessly verify the correctness of the consensus process without knowing the specific AI decision details.