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The @Lagrange Official uses ZK proofs to handle off-chain computations, then securely validates the results back on-chain. Simply put, it allows the blockchain to efficiently handle complex tasks, such as database queries and AI reasoning, without worrying about data tampering or privacy leaks. Their $LA token is not only used for governance and staking, but also directly drives the operation of the proof network. Node operators stake LA to bid for tasks and earn rewards. This mechanism reminds me of some DeFi projects, but Lagrange leans more towards the direction of 'verifiable computation,' which is particularly crucial in the era of AI explosion.
The biggest recent news is the launch of their DeepProve system. This thing is a killer application of zkML (zero-knowledge machine learning) that can prove the correctness of AI reasoning without exposing the original data. For example, in the medical field, hospitals use AI to calculate drug dosages. If the model makes a mistake, the consequences could be dire. DeepProve can generate a cryptographic proof to ensure that the model, inputs, and outputs are all correct, and it does so at speeds thousands of times faster than competing products. In early August, they tweeted a detailed explanation of the application process in a hospital setting: patient data input, AI recommends dosage, DeepProve verifies, and results are delivered to the doctor. It sounds simple, but the technical barrier behind it is frighteningly high. Many crypto bloggers have mentioned that this can make AI deployment in high-risk industries more stable, such as government welfare eligibility verification, where AI determines who is eligible for benefits, and DeepProve ensures that the process is fair and transparent, avoiding manipulation.
The recent performance of $LA has been good, with the price once soaring to around $0.6 after being listed on Binance, now stabilizing around $0.3. The total supply is 1 billion, with an annual inflation rate of 4%, mainly used to reward provers. Bloggers often mention its practicality: clients pay $LA to request proofs, nodes earn rewards, and with the integration of EigenLayer, the security is even stronger.
#lagrange
The biggest recent news is the launch of their DeepProve system. This thing is a killer application of zkML (zero-knowledge machine learning) that can prove the correctness of AI reasoning without exposing the original data. For example, in the medical field, hospitals use AI to calculate drug dosages. If the model makes a mistake, the consequences could be dire. DeepProve can generate a cryptographic proof to ensure that the model, inputs, and outputs are all correct, and it does so at speeds thousands of times faster than competing products. In early August, they tweeted a detailed explanation of the application process in a hospital setting: patient data input, AI recommends dosage, DeepProve verifies, and results are delivered to the doctor. It sounds simple, but the technical barrier behind it is frighteningly high. Many crypto bloggers have mentioned that this can make AI deployment in high-risk industries more stable, such as government welfare eligibility verification, where AI determines who is eligible for benefits, and DeepProve ensures that the process is fair and transparent, avoiding manipulation.
The recent performance of $LA has been good, with the price once soaring to around $0.6 after being listed on Binance, now stabilizing around $0.3. The total supply is 1 billion, with an annual inflation rate of 4%, mainly used to reward provers. Bloggers often mention its practicality: clients pay $LA to request proofs, nodes earn rewards, and with the integration of EigenLayer, the security is even stronger.
#lagrange
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