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36氪发布于 08/24 15:07

李泽湘投过的商业园林机器人完成数千万融资，瞄准海外绿地智能运维｜硬氪首发

作者 | 黄楠 编辑 | 袁斯来 硬氪获悉，商业园林机器人公司食铁兽科技（PANDAG）近日完成数千万元A轮融资，本轮由云时资本独家投资，星⾠资本担任财务顾问。资金将重点投入欧美澳市场交付体系搭建及全球渠道布局。此前，公司已获得李泽湘教授、奇绩创坛、险峰⻓⻘等机构投资。

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人人都是产品经理发布于 08/25 11:15

豆包工作评测：从问答助手到数字打工人

周报还要翻聊天记录磨两小时？让 AI 自己读文档、做表格、出 PPT，你只动嘴。豆包工作把”回答问题”升级成”交付结果”，本地和云端双线跑，几十块一个月就能雇个不知疲倦的数字同事。

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Solidot发布于 08/23 23:48

机器人短跑超越人类，但刹住是问题

Solidot是至顶网的科技资讯网站，主要面对开源自由软件和关心科技资讯读者群，包括众多中国开源软件的开发者，爱好者和布道者。口号是“奇客的知识，重要的东西”。

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AWS Machine Learning Blog发布于 08/25 03:32

Introducing new Ray capabilities on SageMaker HyperPod

（翻译）在 SageMaker HyperPod 上推出新的 Ray 功能

Amazon SageMaker HyperPod now offers managed Ray support on Amazon EKS. Create and monitor Ray clusters, connect JupyterLab and Code Editor notebooks to live clusters, get out-of-the-box observability, and run resilient distributed training and accelerated inference from SageMaker Studio, all with o

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Google AI Blog发布于 07/22 21:00

3 Google updates from Galaxy Unpacked 2026

（翻译）来自 Galaxy Unpacked 2026 的 3 项 Google 更新

We shared how Samsung users can boost productivity and get time back on new foldables, watches, and glasses coming soon.

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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

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NVIDIA Technical Blog发布于 08/22 00:21

GPU-Accelerated Clustering for Financial Instruments at Scale

（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…

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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

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AWS Machine Learning Blog发布于 08/21 00:11

Scaling cloud migrations with agentic AI on Amazon Bedrock AgentCore

（翻译）在 Amazon Bedrock AgentCore 上使用代理式 AI 扩展云迁移

Learn how AWS Professional Services uses a multi-agent framework built on Amazon Bedrock AgentCore to automate enterprise cloud migrations end to end. Purpose-built AI agents handle discovery, infrastructure as code generation, portfolio governance, and post-migration operations, reducing IaC develo

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