NVIDIA Technical Blog发布于 08/24 23:00
Maximizing AI Factory Performance per Watt with NVIDIA DSX MaxLPS
（翻译）借助 NVIDIA DSX MaxLPS 最大化 AI 工厂每瓦性能
AI factories are power-constrained industrial systems. The question is no longer how many GPUs fit in a data center, but how much AI output each available…
AWS Machine Learning Blog发布于 08/24 23:53
AI-powered metadata correction and harmonization
（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
Google AI Blog发布于 07/07 16:54
Expanding Managed Agents in Gemini API: background tasks, remote MCP and more
（翻译）扩展Gemini API中的托管Agent：后台任务、远程MCP等
We’re announcing new capabilities in Managed Agents in Gemini API so developers can build reliable, production-ready agents.
Hugging Face Blog发布于 08/18 03:46
Same Cluster, 33 Points More Utilization: What Changed Was the Order
（翻译）同一集群，利用率提升33个百分点：改变的是顺序
A Blog post by Dharma-AI on Hugging Face
AWS Machine Learning Blog发布于 08/22 00:57
Accelerating aircraft IFEC diagnostics with agentic AI on AWS
（翻译）借助 AWS 上的智能体 AI 加速飞机 IFEC 诊断
Panasonic Avionics worked with AWS and the AWS Generative AI Innovation Center to build an agentic AI system on Amazon Bedrock, Amazon SageMaker, and AWS Glue that diagnoses in-flight entertainment and connectivity (IFEC) issues across a global fleet, reducing diagnosis time from hours to minutes wh
AWS Machine Learning Blog发布于 08/21 05:23
Build a no-code ML workflow with Snowflake, Amazon SageMaker Canvas and Amazon Quick – Part 2: Data preparation and model building with Amazon SageMaker Canvas
（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
AWS Machine Learning Blog发布于 08/21 00:06
AWS vector solutions: Build agentic AI where your data lives
（翻译）AWS 向量解决方案：在数据所在之处构建智能体 AI
AWS offers a broad portfolio of vector search built directly into the databases and storage services you already use, with no standalone vector database or data migration required. This post covers six purpose-built services, a decision framework for choosing the right engine, and customer proof poi
Hugging Face Blog发布于 07/30 23:09
GPU Management: Why Idle GPUs Are the New Grounded Aircraft
（翻译）GPU 管理：为何闲置 GPU 是新的停场飞机
A Blog post by Dharma-AI on Hugging Face
AWS Machine Learning Blog发布于 08/20 06:09
Automate Document Processing with Quick Automate and the IDP Accelerator
（翻译）利用 Quick Automate 与 IDP Accelerator 自动化文档处理
Classifying, extracting, and validating high volumes of documents is a challenge across banking, insurance, healthcare, and the public sector. See how a mid-size mortgage lender automates its entire document intake pipeline, from email to validated data, using the AWS GAIIC IDP Accelerator and Amazo
InfoQ 中文发布于 08/26 19:11
Netflix详述如何扩展其实时服务地图
Netflix描述了如何重新设计驱动Service Topology（实时服务依赖地图）的流处理管道以满足生产规模需求。该系统采用三阶段架构，将中间解析过程与丰富和持久化过程实现了分离，将回压传播回Kafka而不是丢弃记录，并在高流量内部传输时使用服务器发送事件（server-sent event）来取代gRPC。
arXiv cs.AI发布于 08/28 12:00
SAREF-based Ontology for Distributed AI Workflows across the Edge-Fog-Cloud Continuum
（翻译）基于SAREF的分布式AI工作流跨边缘-雾-云连续体本体
Abstract page for arXiv paper 2608.26160: SAREF-based Ontology for Distributed AI Workflows across the Edge-Fog-Cloud Continuum
人人都是产品经理发布于 08/31 13:09
AI互联网日报：字节跳动推迟豆包2.2、华为云发布病理大模型、小米实测续航1230公里
一个数字落进了长期账本：25%。Anthropic把Claude Code临时增幅的一部分写进长期周限额，字节跳动则推迟豆包大模型2.2，要把编程和工具调用再磨一遍。前者把短期优惠变成稳定供给，后者宁可晚一点上线，背后都在回答模型怎样持续交付，而不只是在发布当天漂亮。因为真正留住用户的，从来不是一场演示，而是每次打开都能把活干完。
