作者丨 张璐 编辑丨 岑峰 幸丽娟 &n
作者丨 幸丽娟 编辑丨岑 峰  
（翻译）WeatherNext：AI模型在预测气旋方面取得突破
（翻译）AI 驱动的元数据修正与协调
Metadata harmonization (standardizing labels, identifiers, and formats so datasets can work together) is still largely manual. This post shows how AI-powered metadata correction works in practice, covering two approaches, human-in-the-loop validation and autonomous agent-driven workflows, plus gover
（翻译）GPU加速的大规模金融工具聚类
Use AdaptGrow, a GPU-accelerated matrix factorization algorithm, to turn rolling correlation and tail-dependence matrices into hard clusters…
（翻译）使用Snowflake、Amazon SageMaker Canvas和Amazon Quick构建无代码机器学习工作流——第1部分：设置Snowflake环境
Healthcare, retail, and life sciences teams store large volumes of operational data in Snowflake, but turning it into predictions is hard. In Part 1 of this series, you set up your AWS account and Snowflake environment for a no-code ML workflow with Amazon SageMaker Canvas, laying the foundation for
（翻译）使用Snowflake、Amazon SageMaker Canvas和Amazon Quick构建无代码机器学习工作流——第2部分：使用Amazon SageMaker Canvas进行数据准备和模型构建
In Part 2 of this no-code ML series, you connect Amazon SageMaker Canvas to Snowflake, prepare and join transaction data with Data Wrangler visual transformations, and train an XGBoost fraud detection model. All without writing machine learning code, laying the groundwork for interactive dashboards
（翻译）使用多个 GPU 在几分钟内运行大规模 UMAP——且不损失精度
Uniform Manifold Approximation and Projection (UMAP) is a dimensionality reduction technique widely used for visualization and feature extraction.
（翻译）审计可解释人工智能鲁棒性与保真度的形式化方法论框架：从应用到信任认证
Abstract page for arXiv paper 2608.23817: A Formal Methodological Framework for Auditing Robustness and Fidelity in Explainable AI: From Application to Trust Certification
