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Explaining changes in real-world data
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The success of deep learning is a testament to the power of statistical correlation: if certain image features are consistently correlated with the label ...

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Amazon open-sources library for prediction over large output spaces
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In the Internet age, many computational tasks involve finding a handful of solutions in an enormous space of candidates. Question-answering systems, for ...

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Two Amazon Scholars elected to prestigious science organizations
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Two Amazon Scholars recently have been elected to prestigious science organizations that promote the advancement of science for the public good.Dirk ...

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ICLR: What representation learning means in the data center
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Until relatively recently, a major concern of machine learning research was feature engineering, or determining which aspects of a machine learning model’s ...

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Caltech names eight AI4Science fellows supported by Amazon
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In January, eight scientists were named as 2021 Amazon AI4Science Fellows at Caltech, the world-renowned science and engineering research institution based ...

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Amazon helps launch workshop on synthetic data generation
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We are excited to announce the first Workshop on Synthetic Data Generation, to be held virtually at ICLR 2021 on May 7, 2021.Synthetic data is a powerful ...

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How Muthoni Ngatia’s childhood in Kenya led her to a career in economics
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To understand how to best serve customers around the world, it’s essential to have employees with diverse and unique perspectives. Muthoni Ngatia certainly ...

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How Endel’s AI-powered Focus soundscapes earned the backing of neuroscience
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(Editor’s Note: This is the second in a series of articles Amazon Science is publishing related to the science behind products and services from companies ...

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3 questions with Michael Kearns: Designing socially aware algorithms and models
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The first Amazon Web Services (AWS) Machine Learning Summit on June 2 will bring together customers, developers, and the science community to learn about ...

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Improving explainable AI’s explanations
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Explainability is an important research topic in AI today. If we’re going to trust deep-learning systems to make decisions for us, we often want to know why ...

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