李财之道 蓝鸟会
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When ZK Meets AI: @Lagrange Official How to Restructure Trusted Computing with $LA
In the computational maze of Web3, zero-knowledge proof (ZK) is the key, and @Lagrange Official is using this key to unlock a new door of 'verifiable computation.' As a pioneer in the integration of ZK technology and AI, Lagrange Labs has been targeting one goal since its inception in 2022: to ensure that off-chain computation is both computationally efficient and on-chain trustworthy. Now, with its two 'trump cards,' ZK Prover Network and DeepProve, it has become the driving force behind 11 million ZK proofs, and has provided verifiable 'identities' for over 3 million AI inferences.
The power of DeepProve has long become a legend in the zkML field—generating proofs 158 times faster than similar products. This means that when AI performs credit scoring, user data does not need to be exposed, yet the results can be verified on-chain; when companies use AI to allocate resources, every decision can be traced for fairness. Behind all this, the $LA token is the indispensable 'adhesive': nodes must stake LA to accept tasks, which not only ensures network efficiency but also makes the token a dual carrier of computation power and trust.
@Lagrange Official never solely relies on technology to 'go solo.' It has partnered with EigenLayer, gathering 85 institutional-level operators to build a decentralized network; recently, it collaborated with NVIDIA and Intel to optimize AI inference performance while using FPGA technology to accelerate ZK computation. Now, zkSync has entrusted 75% of outsourced proofs to it, and projects like Manta Network and Polymer have become regulars. #lagrange is no longer a niche technology label, but rather the 'infrastructure' for Layer 2 and AI trustworthiness.
In the future computing world, cross-chain data can be verified without bridging, and AI outputs can be cryptographically 'validated' at any time—this is all hidden within the ecosystem driven by $LA . What #lagrange is doing is not just enhancing efficiency, but ensuring that every computation deserves the label 'trustworthy.'
In the computational maze of Web3, zero-knowledge proof (ZK) is the key, and @Lagrange Official is using this key to unlock a new door of 'verifiable computation.' As a pioneer in the integration of ZK technology and AI, Lagrange Labs has been targeting one goal since its inception in 2022: to ensure that off-chain computation is both computationally efficient and on-chain trustworthy. Now, with its two 'trump cards,' ZK Prover Network and DeepProve, it has become the driving force behind 11 million ZK proofs, and has provided verifiable 'identities' for over 3 million AI inferences.
The power of DeepProve has long become a legend in the zkML field—generating proofs 158 times faster than similar products. This means that when AI performs credit scoring, user data does not need to be exposed, yet the results can be verified on-chain; when companies use AI to allocate resources, every decision can be traced for fairness. Behind all this, the $LA token is the indispensable 'adhesive': nodes must stake LA to accept tasks, which not only ensures network efficiency but also makes the token a dual carrier of computation power and trust.
@Lagrange Official never solely relies on technology to 'go solo.' It has partnered with EigenLayer, gathering 85 institutional-level operators to build a decentralized network; recently, it collaborated with NVIDIA and Intel to optimize AI inference performance while using FPGA technology to accelerate ZK computation. Now, zkSync has entrusted 75% of outsourced proofs to it, and projects like Manta Network and Polymer have become regulars. #lagrange is no longer a niche technology label, but rather the 'infrastructure' for Layer 2 and AI trustworthiness.
In the future computing world, cross-chain data can be verified without bridging, and AI outputs can be cryptographically 'validated' at any time—this is all hidden within the ecosystem driven by $LA . What #lagrange is doing is not just enhancing efficiency, but ensuring that every computation deserves the label 'trustworthy.'
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