From the course: Cloud Architecture: Design Decisions

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Advanced architecture scenario: Agentic AI computing

Advanced architecture scenario: Agentic AI computing

From the course: Cloud Architecture: Design Decisions

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Advanced architecture scenario: Agentic AI computing

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- In the last video, we looked at an enterprise content generation application that used generative AI. In this video, I'll show you a straight to the point architecture for a cloud-based autonomous AI agent system that can independently reason, plan, and execute tasks. Again, this is just an example. There are complete courses here on Agentic AI architectures. Please seek those out if you are interested in Agentic AI running on cloud computing systems. Thus, some of this may seem a bit cryptic, but it's designed to provide you with a real world example. Let's dive in. Core components are: the agent layer, LangChain for agent orchestration, AutoGPT for autonomous processing, vector memory store for agent state, and ReAct framework for reasoning engine. Execution layer: function calling API, tool integration framework, AWS Lambda for serverless actions, and Azure OpenAI for the core large language model. And finally, the control layer: agent supervisor systems, safety guardrails…

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