DeepLearning.AI(@DeepLearningAI)
🖥️ Agents don't just consume tokens for input and output like humans do with early chatbots. Agents...
7.5内容质量
TL;DR · AI 摘要
AI代理需要更多基础设施和工具，而不仅仅是更快的模型。DeepLearning.AI强调代理的计算规模远超人类，需重构工程体系。
核心要点
- AI代理的计算规模是人类的数千倍，需重构基础设施
- Andrew Ng指出工具优化比模型加速更重要
- 搜索/存储/分析等能力需要专用系统支持
结构提纲
按章节快速跳转。
思维导图
用一张图看清主题之间的关系。
查看大纲文本（无障碍 / 无 JS 友好）
- AI代理与基础设施革命
- 核心差异
- 人类级交互 → 计算机级操作
- 输入输出 → 搜索/存储/分析
- 工程需求
- 专用基础设施
- 工具链重构
- 规模化系统设计
金句 / Highlights
值得收藏与分享的关键句。
Agents use computers: searching, storing, analyzing, transacting, at a scale no person matches
we need much more infrastructure, and faster tools, not just faster models
3:00 PM · Oct 10, 2026 6,711 Views
#AI工程#AI代理#基础设施#DeepLearning.AI
打开原文DeepLearning.AI on X: "🖥️ Agents don't just consume tokens for input and output like humans do with early chatbots. Agents use computers: searching, storing, analyzing, transacting, at a scale no person matches. In this week's Andrew's Letter in The Batch, Andrew Ng explains why that means we nee… / X
@DeepLearningAI
🖥️ Agents don't just consume tokens for input and output like humans do with early chatbots. Agents use computers: searching, storing, analyzing, transacting, at a scale no person matches. In this week's Andrew's Letter in The Batch, Andrew Ng explains why that means we need much more infrastructure, and faster tools, not just faster models. 🏗️ 📬
hubs.ly/Q04zR8n20
#DeepLearningAI
#AIEngineering
#AIAgents
3:00 PM · Oct 10, 2026
·
6,711
Views
13
8
49
7