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	<title>Laura Verghote &#8211; Noise</title>
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		<title>Implementing safety guardrails for applications using Amazon SageMaker</title>
		<link>https://noise.getoto.net/2025/05/12/implementing-safety-guardrails-for-applications-using-amazon-sagemaker/</link>
		
		<dc:creator><![CDATA[Laura Verghote]]></dc:creator>
		<pubDate>Mon, 12 May 2025 16:53:58 +0000</pubDate>
				<category><![CDATA[AI]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[Intermediate (200)]]></category>
		<category><![CDATA[SageMaker]]></category>
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					<description><![CDATA[Large Language Models (LLMs) have become essential tools for content generation, document analysis, and natural language processing tasks. Because of the complex non-deterministic output generated by these models, you need to apply robust safety measures to help prevent inappropriate outputs and protect user interactions. These measures are crucial to address concerns such as the risk […]]]></description>
		
		
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		<title>Securing the RAG ingestion pipeline: Filtering mechanisms</title>
		<link>https://noise.getoto.net/2024/11/19/securing-the-rag-ingestion-pipeline-filtering-mechanisms/</link>
		
		<dc:creator><![CDATA[Laura Verghote]]></dc:creator>
		<pubDate>Tue, 19 Nov 2024 21:51:24 +0000</pubDate>
				<category><![CDATA[Advanced (300)]]></category>
		<category><![CDATA[Amazon Bedrock]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Best practices]]></category>
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					<description><![CDATA[Retrieval-Augmented Generative (RAG) applications enhance the responses retrieved from large language models (LLMs) by integrating external data such as downloaded files, web scrapings, and user-contributed data pools. This integration improves the models’ performance by adding relevant context to the prompt. While RAG applications are a powerful way to dynamically add additional context to an LLM’s prompt […]]]></description>
		
		
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