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。

3781历史快讯
208开源工具
8当前结果
09 月 29 日 2026-09-29 快讯

AWS Machine Learning 动态:Bring near-Astra intelligence to everyday work with GPT-6.1 Sol on Amazon Bedrock

原文摘要:GPT-6.1 Sol is now generally available on Amazon Bedrock, bringing stronger reasoning to coding, computer use, and professional workloads that run frequently. 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。

The Decoder 官方资讯

The Decoder:OpenAI's reveals a new ChatGPT that looks less like a chatbot and more like an operating sys…

原文摘要:At DevDay, OpenAI announced a wave of updates that push ChatGPT well beyond its chatbot roots. The company is adding shared workspaces, collaborative documents and slides, 来源:The Decoder。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:Building an AI-powered contract intelligence platform with Amazon Quick and Amazon Bedrock A…

原文摘要:Manually extracting data from hundreds of vendor contracts doesn't scale, and RAG chat tools fall short on portfolio-wide questions. This post shares a contract intelligence platfo 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:Prompt engineering by Quick component: Patterns and pitfalls

原文摘要:Part 2 of our Amazon Quick prompt engineering series goes component by component. Learn the prompt patterns that get the best results from Amazon Quick Research, Quick Flows, Quick 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:Prompt engineering fundamentals for Amazon Quick

原文摘要:Prompt engineering in Amazon Quick shapes how accurately its AI-powered features respond to your requests. Part 1 of a two-part series covers the foundational principles and reusab 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:How Condé Nast built multimodal video discovery with Amazon Bedrock

原文摘要:Condé Nast's editorial teams spent an average of 250 minutes per task searching a library of more than 140,000 videos using only titles and descriptions. Working with the AWS Gener 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。