AI reasoning can be verified! @Lagrange Official reshapes the trust standard with DeepProve

Are AI output results trustworthy? Can cross-chain computing data ensure authenticity? These "trust blind spots" have made the integration of blockchain and AI difficult. However, the zero-knowledge proof (ZK) network developed by lagrangedev, #lagrange , is innovating technology to reshape industry trust standards, making "verifiable" the foundational capability for AI reasoning and cross-chain computing.

As a Web3 project focused on ZK technology, the technical matrix of @Lagrange Official is highly competitive: the decentralized ZK proof network brings together over 85 quality operators, with the participation of leading institutions like Coinbase and Kraken, ensuring both security and decentralization; the ZK co-processor simplifies on-chain query processes, making operations as convenient as using SQL, significantly lowering the barrier for developers; and the DeepProve zkML engine has achieved a 158-fold increase in AI proof speed, allowing for the efficient generation of "tamper-proof evidence" of AI reasoning results, effectively equipping AI with an "encrypted trust lock."

The LA token is the "value anchor" of the entire ecosystem. Node participants in proof tasks must stake $LA as collateral; failure to complete on time or proving errors will result in fund deductions to ensure task fulfillment quality; developers calling APIs for proof services pay a designated fee in LA; and community members participating in network rule revisions can exercise their voting rights by holding LA. Its tokenomics design is rigorous: a total supply of 1 billion, with only 4% released annually, and periodic token burns to tightly bind token value with network activity and actual usage. Now, chains like ZKsync and AltLayer utilize it to complete cross-chain proofs, and DeFi protocols generate results with proofs linked back when querying historical data, completely resolving the "data