<ul><li>Google released a 76-page whitepaper on AI agents called Agentic RAG, which aims to enhance traditional RAG systems by allowing agents to dynamically reformulate queries during task execution.</li><li>The whitepaper outlines the benefits of Agentic RAG in real-world scenarios like research assistance, customer support automation, and healthcare diagnostics.</li><li>It introduces a comprehensive evaluation stack for agents, including automated metrics and human-in-the-loop annotations, focusing on contextual benchmarking within full workflows.</li><li>Google's whitepaper details the architecture and deployment strategies of real-world agent systems, emphasizing the use of hybrid control models, privacy, and scalability.</li></ul>

Google Releases 76-Page Whitepaper on AI Agents A Deep Technical Dive into Agentic RAG, Evaluation…

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