基本信息
- 来源: blogs_podcasts
- 原始来源: https://aws.amazon.com/blogs/machine-learning/evaluating-ai-agents-real-world-lessons-from-building-agentic-systems-at-amazon
来源摘要/节选
公开展示已截断至最多 800 个字符;请访问原始来源查看完整上下文。
The generative AI industry has undergone a significant transformation from using large language model (LLM)-driven applications to agentic AI systems , marking a fundamental shift in how AI capabilities are architected and deployed. While early generative AI applications primarily relied on LLMs to directly generate text and respond to prompts, the industry has evolved from those static, prompt-response paradigms toward autonomous agent frameworks to build dynamic, goal-oriented systems capable of tool orchestration, iterative problem-solving, and adaptive task execution in production environments.
We have witnessed this evolution in Amazon; since 2025, there have been thousands of agents built across Amazon organizations.…
来源说明
当前只保存了公开页面节选,不代表原文全文。请以原始来源为准。
本页只呈现已做哈希绑定的来源证据,不包含基于旧正文或缺失原文的扩展推断。