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	<title>Julien Simon &#8211; Noise</title>
	<atom:link href="https://noise.getoto.net/author/julien-simon/feed/" rel="self" type="application/rss+xml" />
	<link>https://noise.getoto.net</link>
	<description>The collective thoughts of the interwebz</description>
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		<title>Scaling Ad Verification with Machine Learning and AWS Inferentia</title>
		<link>https://noise.getoto.net/2021/09/22/scaling-ad-verification-with-machine-learning-and-aws-inferentia/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Wed, 22 Sep 2021 17:42:26 +0000</pubDate>
				<category><![CDATA[Amazon Rekognition]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS Inferentia]]></category>
		<category><![CDATA[Thought Leadership]]></category>
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					<description><![CDATA[Amazon Advertising helps companies build their brand and connect with shoppers, through ads shown both within and beyond Amazon’s store, including websites, apps, and streaming TV content in more than 15 countries. Businesses or brands of all sizes including registered sellers, vendors, book vendors, Kindle Direct Publishing (KDP) authors, app developers, and agencies on Amazon […]]]></description>
		
		
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		<title>Decoding the Social Effects Of Media with Machine Learning</title>
		<link>https://noise.getoto.net/2021/09/03/decoding-the-social-effects-of-media-with-machine-learning/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Fri, 03 Sep 2021 16:30:42 +0000</pubDate>
				<category><![CDATA[Analytics]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Thought Leadership]]></category>
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					<description><![CDATA[What if media were optimized to benefit people? This thought-provoking question is at the core of Harmony Labs‘ mission. A nonprofit organization headquartered in New York City, Harmony Labs strives to better understand the impact of media on society, and build communities and tools to reform and transform media systems. As Brian Wanieswki, Executive Director […]]]></description>
		
		
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		<title>Extract Insights From Customer Conversations with Amazon Transcribe Call Analytics</title>
		<link>https://noise.getoto.net/2021/08/04/extract-insights-from-customer-conversations-with-amazon-transcribe-call-analytics/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Wed, 04 Aug 2021 18:06:17 +0000</pubDate>
				<category><![CDATA[Amazon Transcribe]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
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					<description><![CDATA[In 2017, we launched Amazon Transcribe, an automatic speech recognition (ASR) service that makes it easy to add speech-to-text capabilities to any application. Today, I’m very happy to announce the availability of Amazon Transcribe Call Analytics, a new feature that lets you easily extract valuable insights from customer conversations with a single API call. Each […]]]></description>
		
		
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		<title>Paging Doctor Cloud! Amazon HealthLake Is Now Generally Available</title>
		<link>https://noise.getoto.net/2021/07/15/paging-doctor-cloud-amazon-healthlake-is-now-generally-available/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Thu, 15 Jul 2021 14:16:11 +0000</pubDate>
				<category><![CDATA[Amazon HealthLake]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Healthcare]]></category>
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					<description><![CDATA[At AWS re:Invent 2020, we previewed Amazon HealthLake, a fully managed, HIPAA-eligible service that allows healthcare and life sciences customers to aggregate their health information from different silos and formats into a structured, centralized AWS data lake, and extract insights from that data with analytics and machine learning (ML). Today, I’m very happy to announce […]]]></description>
		
		
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		<item>
		<title>Amazon SageMaker Named as the Outright Leader in Enterprise MLOps Platforms</title>
		<link>https://noise.getoto.net/2021/06/09/amazon-sagemaker-named-as-the-outright-leader-in-enterprise-mlops-platforms/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Wed, 09 Jun 2021 18:00:54 +0000</pubDate>
				<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[Thought Leadership]]></category>
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					<description><![CDATA[Over the last few years, Machine Learning (ML) has proven its worth in helping organizations increase efficiency and foster innovation. As ML matures, the focus naturally shifts from experimentation to production. ML processes need to be streamlined, standardized, and automated to build, train, deploy, and manage models in a consistent and reliable way. Perennial IT […]]]></description>
		
		
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		<title>Amazon SageMaker JumpStart Simplifies Access to Pre-built Models and Machine Learning Solutions</title>
		<link>https://noise.getoto.net/2020/12/08/amazon-sagemaker-jumpstart-simplifies-access-to-pre-built-models-and-machine-learning-solutions/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Tue, 08 Dec 2020 18:03:31 +0000</pubDate>
				<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[Events]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
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					<description><![CDATA[Today, I&#8217;m extremely happy to announce the availability of Amazon SageMaker JumpStart, a capability of Amazon SageMaker that accelerates your machine learning workflows with one-click access to popular model collections (also known as &#8220;model zoos&#8221;), and to end-to-end solutions that solve common use cases. In recent years, machine learning (ML) has proven to be a [&#8230;]]]></description>
		
		
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		<title>New – Amazon SageMaker Pipelines Brings DevOps Capabilities to your Machine Learning Projects</title>
		<link>https://noise.getoto.net/2020/12/08/new-amazon-sagemaker-pipelines-brings-devops-capabilities-to-your-machine-learning-projects/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Tue, 08 Dec 2020 17:59:41 +0000</pubDate>
				<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[Events]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
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					<description><![CDATA[Today, I&#8217;m extremely happy to announce Amazon SageMaker Pipelines, a new capability of Amazon SageMaker that makes it easy for data scientists and engineers to build, automate, and scale end to end machine learning pipelines. Machine learning (ML) is intrinsically experimental and unpredictable in nature. You spend days or weeks exploring and processing data in [&#8230;]]]></description>
		
		
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		<title>Introducing Amazon SageMaker Data Wrangler, a Visual Interface to Prepare Data for Machine Learning</title>
		<link>https://noise.getoto.net/2020/12/08/introducing-amazon-sagemaker-data-wrangler-a-visual-interface-to-prepare-data-for-machine-learning/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Tue, 08 Dec 2020 17:59:23 +0000</pubDate>
				<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
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					<description><![CDATA[Today, I&#8217;m extremely happy to announce Amazon SageMaker Data Wrangler, a new capability of Amazon SageMaker that makes it faster for data scientists and engineers to prepare data for machine learning (ML) applications by using a visual interface. Whenever I ask a group of data scientists and ML engineers how much time they actually spend [&#8230;]]]></description>
		
		
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			</item>
		<item>
		<title>New – Store, Discover, and Share Machine Learning Features with Amazon SageMaker Feature Store</title>
		<link>https://noise.getoto.net/2020/12/08/new-store-discover-and-share-machine-learning-features-with-amazon-sagemaker-feature-store/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Tue, 08 Dec 2020 17:58:35 +0000</pubDate>
				<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
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					<description><![CDATA[Today, I&#8217;m extremely happy to announce Amazon SageMaker Feature Store, a new capability of Amazon SageMaker that makes it easy for data scientists and machine learning engineers to securely store, discover and share curated data used in training and prediction workflows. For all the importance of selecting the right algorithm to train machine learning (ML) [&#8230;]]]></description>
		
		
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		<item>
		<title>Amazon SageMaker Edge Manager Simplifies Operating Machine Learning Models on Edge Devices</title>
		<link>https://noise.getoto.net/2020/12/08/amazon-sagemaker-edge-manager-simplifies-operating-machine-learning-models-on-edge-devices/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Tue, 08 Dec 2020 16:56:04 +0000</pubDate>
				<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[Amazon SageMaker Neo]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[Events]]></category>
		<category><![CDATA[Internet of Things]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
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					<description><![CDATA[Today, I&#8217;m extremely happy to announce Amazon SageMaker Edge Manager, a new capability of Amazon SageMaker that makes it easier to optimize, secure, monitor, and maintain machine learning models on a fleet of edge devices. Edge computing is certainly one of the most exciting developments in information technology. Indeed, thanks to continued advances in compute, [&#8230;]]]></description>
		
		
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		<item>
		<title>New – Amazon SageMaker Clarify Detects Bias and Increases the Transparency of Machine Learning Models</title>
		<link>https://noise.getoto.net/2020/12/08/new-amazon-sagemaker-clarify-detects-bias-and-increases-the-transparency-of-machine-learning-models/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Tue, 08 Dec 2020 16:38:22 +0000</pubDate>
				<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[Events]]></category>
		<category><![CDATA[launch]]></category>
		<category><![CDATA[news]]></category>
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					<description><![CDATA[Today, I&#8217;m extremely happy to announce Amazon SageMaker Clarify, a new capability of Amazon SageMaker that helps customers detect bias in machine learning (ML) models, and increase transparency by helping explain model behavior to stakeholders and customers. As ML models are built by training algorithms that learn statistical patterns present in datasets, several questions immediately [&#8230;]]]></description>
		
		
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			</item>
		<item>
		<title>New – Profile Your Machine Learning Training Jobs With Amazon SageMaker Debugger</title>
		<link>https://noise.getoto.net/2020/12/08/new-profile-your-machine-learning-training-jobs-with-amazon-sagemaker-debugger/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Tue, 08 Dec 2020 16:38:00 +0000</pubDate>
				<category><![CDATA[Amazon Machine Learning]]></category>
		<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[PyTorch on AWS]]></category>
		<category><![CDATA[Tensorflow on AWS]]></category>
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					<description><![CDATA[Today, I&#8217;m extremely happy to announce that Amazon SageMaker Debugger can now profile machine learning models, making it much easier to identify and fix training issues caused by hardware resource usage. Despite its impressive performance on a wide range of business problems, machine learning (ML) remains a bit of a mysterious topic. Getting things right [&#8230;]]]></description>
		
		
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		<title>New – Managed Data Parallelism in Amazon SageMaker Simplifies Training on Large Datasets</title>
		<link>https://noise.getoto.net/2020/12/08/new-managed-data-parallelism-in-amazon-sagemaker-simplifies-training-on-large-datasets/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Tue, 08 Dec 2020 16:18:17 +0000</pubDate>
				<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[Events]]></category>
		<category><![CDATA[open source]]></category>
		<category><![CDATA[PyTorch on AWS]]></category>
		<category><![CDATA[Tensorflow on AWS]]></category>
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					<description><![CDATA[Today, I&#8217;m particularly happy to announce that Amazon SageMaker now supports a new data parallelism library that makes it easier to train models on datasets that may be as large as hundreds or thousands of gigabytes. As data sets and models grow larger and more sophisticated, machine learning (ML) practitioners working on large distributed training [&#8230;]]]></description>
		
		
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		<item>
		<title>Amazon SageMaker Simplifies Training Deep Learning Models With Billions of Parameters</title>
		<link>https://noise.getoto.net/2020/12/08/amazon-sagemaker-simplifies-training-deep-learning-models-with-billions-of-parameters/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Tue, 08 Dec 2020 16:17:56 +0000</pubDate>
				<category><![CDATA[Amazon Sagemaker]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[Events]]></category>
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					<description><![CDATA[Today, I&#8217;m extremely happy to announce that Amazon SageMaker simplifies the training of very large deep learning models that were previously difficult to train due to hardware limitations. In the last 10 years, a subset of machine learning named deep learning (DL) has taken the world by storm. Based on neural networks, DL algorithms have [&#8230;]]]></description>
		
		
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		<item>
		<title>Amazon Monitron, a Simple and Cost-Effective Service Enabling Predictive Maintenance</title>
		<link>https://noise.getoto.net/2020/12/01/amazon-monitron-a-simple-and-cost-effective-service-enabling-predictive-maintenance/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Tue, 01 Dec 2020 18:32:17 +0000</pubDate>
				<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[AWS re:Invent]]></category>
		<category><![CDATA[Events]]></category>
		<category><![CDATA[Internet of Things]]></category>
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					<description><![CDATA[Today, I&#8217;m extremely happy to announce Amazon Monitron, a condition monitoring service that detects potential failures and allows user to track developing faults enabling you to implement predictive maintenance and reduce unplanned downtime. True story: A few months ago, I bought a new washing machine. As the delivery man was installing it in my basement, [&#8230;]]]></description>
		
		
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		<title>Amazon SageMaker Continues to Lead the Way in Machine Learning and Announces up to 18% Lower Prices on GPU Instances</title>
		<link>https://noise.getoto.net/2020/10/07/amazon-sagemaker-continues-to-lead-the-way-in-machine-learning-and-announces-up-to-18-lower-prices-on-gpu-instances/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Wed, 07 Oct 2020 16:28:52 +0000</pubDate>
				<category><![CDATA[announcements]]></category>
		<category><![CDATA[Apache MXNet on AWS]]></category>
		<category><![CDATA[artificial intelligence]]></category>
		<category><![CDATA[open source]]></category>
		<category><![CDATA[PyTorch on AWS]]></category>
		<category><![CDATA[SageMaker]]></category>
		<category><![CDATA[Tensorflow on AWS]]></category>
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					<description><![CDATA[Since 2006, Amazon Web Services (AWS) has been helping millions of customers build and manage their IT workloads. From startups to large enterprises to public sector, organizations of all sizes use our cloud computing services to reach unprecedented levels of security, resiliency, and scalability. Every day, they&#8217;re able to experiment, innovate, and deploy to production [&#8230;]]]></description>
		
		
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		<title>Amazon Transcribe Now Supports Automatic Language Identification</title>
		<link>https://noise.getoto.net/2020/09/15/amazon-transcribe-now-supports-automatic-language-identification/</link>
		
		<dc:creator><![CDATA[Julien Simon]]></dc:creator>
		<pubDate>Tue, 15 Sep 2020 17:58:14 +0000</pubDate>
				<category><![CDATA[Amazon Transcribe]]></category>
		<category><![CDATA[announcements]]></category>
		<category><![CDATA[artificial intelligence]]></category>
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					<description><![CDATA[In 2017, we launched Amazon Transcribe,&#160;an automatic speech recognition service that makes it easy for developers to add a speech-to-text capability to their applications. Since then, we added support for more languages, enabling customers globally to transcribe audio recordings in 31 languages, including 6 in real-time. A popular use case for Amazon Transcribe is transcribing [&#8230;]]]></description>
		
		
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