AI 每日快讯

AI 每日快讯

AI 产品、模型、开源工具和官方动态的时间流。保留历史记录,按分类、日期和标签继续筛选。

1147历史快讯
74开源工具
9当前结果
06 月 16 日 昨日快讯

AWS Machine Learning 动态:Safeguard your agentic AI applications with the Amazon Bedrock Guardrails InvokeGuardrailChe…

原文摘要:Today, we’re announcing a new API with Amazon Bedrock Guardrails. With this API, you can apply individual safeguards, also referred to as safety checks, at any point in your agenti 来源:AWS Machine Learning 动态。建议继续查看原文,重点核对它影响的工具入口、成本、风险和真实使用场景。

AWS Machine Learning 动态:Introducing container caching in Amazon SageMaker AI for faster model scaling

原文摘要:Today, we’re excited to announce container image caching for Amazon SageMaker AI inference, the next major advancement in our faster scaling optimization journey. This speeds up en 来源:AWS Machine Learning 动态。建议继续查看原文,重点核对它影响的工具入口、成本、风险和真实使用场景。

AWS Machine Learning 动态:Parallelize speculative decoding with P-EAGLE on Amazon SageMaker AI

原文摘要:This post walks you through how to use P-EAGLE directly within Amazon SageMaker AI. It will demonstrate how to select a compatible model from the SageMaker JumpStart catalog, confi 来源:AWS Machine Learning 动态。建议继续查看原文,重点核对它影响的工具入口、成本、风险和真实使用场景。

AI 资讯 官方资讯

AI 资讯:EU publishes its AI content labelling playbook ahead of the AI Act’s August deadline

原文摘要:The European Union has published its AI content labelling playbook, a voluntary Code of Practice meant to help companies meet transparency rules that become law across the bloc on 来源:AI 资讯。建议继续查看原文,重点核对它影响的工具入口、成本、风险和真实使用场景。

AI 资讯 官方资讯

AI 资讯:How AI-Powered CMS Platforms Are Transforming Enterprise Content Operations

原文摘要:For years, enterprise content management was largely a publication tool. How do you get the right content, in the right format, to the right channel, without breaking 工作流 tha 来源:AI 资讯。建议继续查看原文,重点核对它影响的工具入口、成本、风险和真实使用场景。

MarkTechPost 官方资讯

MarkTechPost:How to Build a Parsing Pipeline with Docling Parse for Layout-Aware Document Intelligence

原文摘要:In this tutorial, we build a 工作流 that uses Docling Parse to analyze PDF documents at a detailed structural level. We prepare a stable Python environment, handle common Colab d 来源:MarkTechPost。建议继续查看原文,重点核对它影响的工具入口、成本、风险和真实使用场景。