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	<title>Sai Srinivas Somarouthu &#8211; Noise</title>
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		<title>How A/B Testing and Multi-Model Hosting Accelerate Generative AI Feature Development in Amazon Q</title>
		<link>https://noise.getoto.net/2024/08/23/how-a-b-testing-and-multi-model-hosting-accelerate-generative-ai-feature-development-in-amazon-q/</link>
		
		<dc:creator><![CDATA[Sai Srinivas Somarouthu]]></dc:creator>
		<pubDate>Fri, 23 Aug 2024 12:02:29 +0000</pubDate>
				<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[Amazon Q]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[generative AI]]></category>
		<category><![CDATA[Technical How-to]]></category>
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					<description><![CDATA[Introduction In the rapidly evolving landscape of Generative AI, the ability to deploy and iterate on features quickly and reliably is paramount. We, the Amazon Q Developer service team, relied on several offline and online testing methods, such as evaluating models on datasets, to gauge improvements. Once positive results are observed, features were rolled out […]]]></description>
		
		
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