区块链 - Cartesi汇总中的机器学习
是否有可能在Cartesi机器中以某种方式训练机器学习模型？我相信，如果模型在Cartesi外受过训练，则不可能审核结果完整性，如果有偏见。如果一切都在Cartesi中，我认为这是可能的。
我看到的项目：
https：//github.com/souzavinny/rollups-examps-rollups-examamples- /tree/main/biometrics
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可以采用两种方法：只需在Cartesi机器内运行训练有素的型号或在其中训练它即可。如果您的DAPP无法通过证明模型本身受益，则可以将模型仅移植到Cartesi机器。如果允许其他人复制培训以获得完全相同的模型对您的DAPP很重要，那么您可以将培训集与Cartesi Machine一起训练，以便其他人可以重现它。
请记住，如果您想在Cartesi机器内训练该模型，则必须将训练所需的所有依赖项移植，而如果您只想运行模型，则可以采用类似的方法，您提供的示例，仅需要对本机计算机上的依赖项来生成模型，而不必担心将它们移植到基于Cartesi Machine RISC-V基于ISA的ISA。
It's possible to have two approaches: just run the trained model inside the Cartesi Machine or train it inside. If your DApp doesn't benefit from proving the model itself, you can port just the model to the Cartesi Machine. If allowing others to replicate the training to obtain exactly the same model is important to your DApp, you can have the training set available along with the Cartesi Machine to train it so others can reproduce it.
Bare in mind that if you want to train the model inside the Cartesi Machine, you'll have to port all the dependencies needed to train it while if you just want to run the model you can take a similar approach to the one on the biometric example you provided, needing the dependencies only on your native machine to generate the model and not having to worry about porting them to the Cartesi Machine RISC-V based ISA.