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<!DOCTYPE html>
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<title> AWS Bedrock Agents</title>
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<h1 class="sitename">Compound <span class="red-project">AI Systems</span></h1>
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<h1> Automate -> <span class="red-sorry">Multistep -> Tasks</span> </h1>
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<h3><span class="red-project">What is an AI Agent?</span></h3>
<h2 class="letter">
In the simplest terms, an AI agent is a decoupled function or program within a broader AI model. Think of it as a specialized worker in a factory that performs specific tasks. When combined, these agents operate in parallel to enhance performance and functionality. This modular approach ensures that each component focuses on its own strengths, creating a more efficient and adaptable system.
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<h3><span class="red-project">Implementing AI Agents Strategically</span></h3>
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<h2 class="letter">1. Internal Modules of the AI Compound System</h2>
<h2 class="letter">AI compound systems are made up of multiple modules, each with a distinct role:</h2>
<h2 class="letter">a. Reasoning Module:</h2>
<h2 class="letter">This module is responsible for breaking down complex problems and creating plans. It leverages large language models (LLMs) to analyze the problem and outline a step-by-step solution.</h2>
<h2 class="letter">b. Action Module:</h2>
<h2 class="letter">The action module interacts with external tools and APIs to execute the plans created by the reasoning module. This could involve calling services like OCR, content summarization, or predictive analytics.</h2>
<h2 class="letter">c. Memory Module:</h2>
<h2 class="letter">This module stores and retrieves past interactions and outcomes. It’s crucial for learning from previous experiences and adapting to new situations.</h2>
<h2 class="letter">d. Coordination Module:</h2>
<h2 class="letter">The coordination module acts as the project manager. It oversees the activities of other modules, ensures they work together harmoniously, and delegates tasks based on the requirements.</h2>
<br/>
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<h3><span class="red-project">Real-World Examples with Amazon Web Services</span></h3>
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<h2 class="letter">**1. OCR Vision Capabilities:** The Action Module can utilize Amazon Textract for OCR tasks, extracting text from documents uploaded to an S3 bucket.</h2>
<h2 class="letter">**2. Content Summarization:** The Action Module can call AWS Comprehend to summarize documents, triggered by Lambda functions.</h2>
<h2 class="letter">**3. Intelligent Document Processing:** The combination of Amazon Textract and SageMaker within the Action Module can automate document processing tasks.</h2>
<h2 class="letter">**4. Predictive Analytics:** AWS Forecast can be integrated into the Action Module to generate predictions based on historical data.</h2>
<h2 class="letter">**5. Retrieval-Augmented Generation (RAG):** The Action Module can retrieve relevant information using RAG and ensure real-time updates with Lambda.</h2>
<h2 class="letter">By strategically implementing these agents, you create a flexible and powerful AI system. Each module knows its role, and the coordination module ensures they work together seamlessly.</h2>
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<h4>Types of <span class="red-project">AI agents</span> </h4>
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<h4>A Quote - Eliezer Yudkowsky</h4>
<p><span class="red-project">“Anything that could give rise to smarter-than-human intelligence—in the form of Artificial Intelligence, brain-computer interfaces, or neuroscience-based human intelligence enhancement – wins hands down beyond contest as doing the most to change the world. Nothing else is even in the same league.”
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