Quanta Magazine发布于 08/20 22:04

Are We Thinking Correctly About AI Intelligence?

(翻译)我们对 AI 智能的思考正确吗?

Computer scientist Melanie Mitchell discusses why artificial intelligence doesn’t “think” or “reason” like humans, and how we can create better methods for measuring machine cognition.

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雷峰网发布于 08/25 10:30

豆包工作正式发布:让 AI 从生成内容到完成工作

8月25日,豆包工作正式发布。作为豆包面向生产力场景推出的全新 Agent 产品与品牌,豆包工作能围绕用户目标自主拆解任务、调用工具、持续推进复杂工作流程。豆包工作还与飞书深度打通,让 Agent 基于企业上下文更准确地完成工作。

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Solidot发布于 08/24 20:27

Anthropic 最强模型难以吸引用户

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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人人都是产品经理发布于 08/25 11:16

阿里开源 Better Harness:AI Agent 真正的竞争,正在从“模型能力”转向“工作方式”

当AI Agent进入研发流程,代码生成不再是瓶颈,验证与信任成为关键。阿里开源的Better Harness通过检查Agent的工作闭环,而非仅看结果,试图解决这一难题。本文深入解析其前馈与反馈机制,并探讨产品经理如何从写需求转向设计Agent的工作制度,揭示AI竞争正从模型能力转向工作系统。

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Google AI Blog发布于 08/03 23:00

Inside our 353,000-person vibe coding course

(翻译)走进我们 35.3 万人的 vibe coding 课程

Kaggle’s AI Agents Intensive with Google brought learners together in a no-cost course to build and deploy the next frontier of AI.

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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 DeepMind Blog发布于 07/30 00:02

We’re launching Lyria 3.5 in Google Flow Music, with advances across musicality, lyrics, vocals, and creative control

(翻译)我们正在Google Flow Music中推出Lyria 3.5,在音乐性、歌词、人声和创作控制方面取得进展

Our newest music generation model, Lyria 3.5, delivers significant advancements across musicality, lyrics, and vocal quality, empowering you to craft richer tracks. We’r…

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AWS Machine Learning Blog发布于 08/25 02:59

Democratizing institutional knowledge: Building an AI-powered knowledge management system with AWS

(翻译)普及机构知识:使用 AWS 构建 AI 驱动的知识管理系统

Learn how to build a customizable, smart-caching knowledge management system on AWS that captures and delivers institutional (tribal) knowledge through a voice-first AI avatar. The accelerator uses Amazon Bedrock Knowledge Bases for retrieval-augmented generation and deploys in hours with AWS CloudF

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NVIDIA Technical Blog发布于 08/24 23:00

Solving Agentic AI Fleet Challenges with NVIDIA Vera CPU

(翻译)利用 NVIDIA Vera CPU 解决 Agentic AI 集群挑战

AI factories are interconnected systems where fleet economics depend on how efficiently the entire stack converts power and capital into completed agent tasks.

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