Lagrange Series (Fifty-Three): LA Token and Multilayer Perceptron Verification Practices Multilayer perceptrons (MLPs) are the foundation of AI models. In the Lagrange ecosystem, the LA token makes their verification simple and reliable. Through zero-knowledge machine learning, the LA token network provides cryptographic proofs for MLPs, ensuring transparency of AI decisions. This is more than just a technical integration; it's a practical step toward verifiable AI. First, understand the role of MLPs in verification. MLPs are commonly used for classification and prediction, but traditionally have been a black box. Lagrange's DeepProve library leverages the LA token network to generate ZK proofs, allowing users to verify each layer of the MLP computation. Provers who stake LA tokens can handle these tasks, earning fees while also enhancing the security of the entire ecosystem. Practice is simple: After developers train an MLP model, they export it to the Lagrange platform via ONNX. LA tokens serve as fuel to power the proof generation process. For example, in financial decision-making, MLP verification can prove the accuracy of predictions and mitigate the risk of manipulation. This allows LA token holders to directly participate in high-value applications. At the community level, LA token governance allows users to optimize the MLP verification protocol, such as increasing parallel processing to accelerate proofs. Support from over 85 operators ensures the network can handle large-scale MLP tasks without sacrificing decentralization. In short, this verification practice is moving AI from mystery to transparency. LA token users are not just investors; they are participants in building a trusted future. In the future, more MLP applications will rely on LA tokens, driving industry change. #lagrange @lagrangedev $LA