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#BinanceTurns8 Collect all #BinanceTurns8 crypto star sign for a chance to win bonus BNB reward! https://www.binance.com/activity/binance-turns-8?ref=GRO_19600_4K8FT
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#BinanceTurns8 Collect all #BinanceTurns8 crypto star sign for a chance to win bonus BNB reward! https://www.binance.com/activity/binance-turns-8?ref=GRO_19600_4K8FT
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#LagrangeLA #LagrangeLA $LA #LagrangeCrash DeepProve Lagrange’s zero-knowledge machine learning (zkML) framework allows developers to cryptographically prove the correctness of AI model inferences without revealing the underlying model parameters or data. This can be used by projects to protect their proprietary data while proving the authenticity of the output. By utilizing advanced cryptographic techniques, DeepProve achieves proving times that are significantly faster than previous zkML solutions. For example, it can prove the inference of a neural network up to 158 times faster than leading alternatives. ZK Coprocessor Lagrange has pioneered an SQL-based ZK Coprocessor that’s designed for performing complex off-chain computations on data and verifying the results on-chain with cryptographic proofs. To achieve this goal, blockchain data is transformed into a ZK-friendly format. Provers use this data to perform intensive off-chain computations and generate ZK proofs that attest to the correctness of the computations. These proofs are then submitted to smart contracts on-chain, enabling trustless verification without revealing the underlying data. Lagrange State Committees In addition to these three components, Lagrange has also introduced Lagrange State Committees, a decentralized network that acts as a ZK light client protocol for optimistic rollups like Arbitrum, Optimism and Mantle Network. Each committee comprises nodes that have restaked at least 32 ETH via EigenLayer.These nodes monitor rollup activity and attest to the finality of blocks. Their collective signatures are aggregated into succinct ZK proofs that applications can use to verify rollup states without waiting for lengthy challenge periods.
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About la$LA #lagrangedev How does Lagrange work? Lagrange relies on zero-knowledge proofs, a cryptographic technique that allows one party to prove the validity of a computation without revealing its underlying data. It combines a ZK proving technique called DeepProve with its ZK Coprocessor and Prover Network. This combination enables complex tasks to be computed while providing on-chain verifiability that they were executed as intended. Let’s look at each of these components in detail below. DeepProve Lagrange’s zero-knowledge machine learning (zkML) framework allows developers to cryptographically prove the correctness of AI model inferences without revealing the underlying model parameters or data. This can be used by projects to protect their proprietary data while proving the authenticity of the output. By utilizing advanced cryptographic techniques, DeepProve achieves proving times that are significantly faster than previous zkML solutions. For example, it can prove the inference of a neural network up to 158 times faster than leading alternatives.
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What is Lagrange? Lagrange Labs, inspired by the mathematician and astronomer Joseph-Louis Lagrange, began as a venture using cryptography and zero-knowledge proofs to solve interoperability challenges between blockchain protocols. However, Lagrange’s scope has evolved beyond solely cross-chain solutions. The project now aims to unlock data-intensive and cross-chain use cases by enabling verifiable computation over blockchain data through its hyper-parallel ZK Coprocessor. Furthermore, Lagrange’s State Committees generate state proofs for optimistic rollups, supporting secure interoperability via protocols like LayerZero, Axelar and Polymer. Lagrange has also launched DeepProve, a groundbreaking zkML (zero-knowledge machine learning) library designed to make verifiable AI inferences faster and more scalable than ever — up to 158x faster than the leading zkML solution.#LagrangeLA
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