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加速 AI 模型生产化:eBay 交易风控 AI 模型推理仿真设计和实现-王兵.pdf

上传人: 张** 编号:181094 2024-09-27 29页 5.60MB

1、eBay Payments Risk AI Model Inference SimulationAccelerating AI ProductionizationBing WangeBay Payments&RiskAgendaAI Model Productionization Process and ChallengesModel Inference Simulation Platform DesignModel Iteration Optimization By SimulationReflections and Future Works1234AI Model Productioniz

2、ation Process and ChallengesAI Model Productionization Process eBay Payments RiskProblems Identification&DefinitionData Exploration&AcquisitionFeatures Design&Offline ConstructionModel Deployment&IntegrationModel Performance EvaluationModel Development&TrainingOnline Features ConstructionExperimenta

3、tion Design&ImplementationExperimentation Result EvaluationBusiness AdoptionOfflineOnlineOnline Features ConstructionExperimentation Design&ImplementationExperimentation Result EvaluationModel Deployment&IntegrationBusiness AdoptionChallengers and Frictions During ProductionizationOnlineExperimentat

4、ions take more than one month to evaluate performance,and it may cause model update and re-deployments multiple times.Bad model performance in online experimentations would cause financial loss in payments risk detectionOnline Features ConstructionExperimentation Design&ImplementationExperimentation

5、 Result EvaluationModel Deployment&IntegrationBusiness AdoptionModel Inference Simulation OnlineModel Inference Simulation replicates the output of online model inference,significantly speeding up performance evaluation and subsequent model updates.This rapid iteration leads to swifter business inte

6、gration and adoption and avoid any economic loss.Model Inference SimulationTargets of Model Inference SimulationConsistency:ensure model inference performs consistently between simulation and online servingEfficiency:ensure model simulation efficiency to speed up business performance evaluation Mode

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本文主要介绍了eBay Payments在AI模型生产化过程中遇到的问题和挑战,以及他们提出的解决方案——模型推断仿真平台。该平台可以模拟在线模型推断的结果,大大加快了性能评估和后续模型更新,从而使业务集成和采用更加迅速,避免了经济损失。模型的在线实验评估可能需要一个多月,而且如果实验结果不佳,可能会导致支付风险检测中的财务损失。通过模型规格说明,保证了模型在仿真和在线服务中的一致性,并通过Docker镜像和Conda环境确保了运行环境的相同。此外,文章还提到了模型迭代优化、仿真的一致性和效率保证,以及未来工作的方向。
挑战与机遇" 如何加速AI生产流程?" AI模型如何助力业务决策?"
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