Few-shot learning
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Learning computational tasks from single examples
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In the past decade, deep-learning systems have proven remarkably successful at many artificial-intelligence tasks, but their applications tend to be narrow. ...

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ICLR: The AI conference that helped redefine the field
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The International Conference on Learning Representations (ICLR), which will be virtual this year and begins next week, is only eight years old. But ...

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Speech synthesizer learns expressive style from one-second voice sample
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Text-to-speech (TTS) systems, like Alexa’s or the ones available to Amazon Web Services customers through Amazon Polly, convert text into synthetic speech. ...

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Learning new language-understanding tasks from just a few examples
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One of the first things a voice agent like Alexa does when receiving a new instruction is to classify its intent — playing music, getting the weather, ...

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3 questions with Marzia Polito: Performing computer vision tasks at scale with few-shot learning
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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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Question answering as a “lingua franca” for transfer learning
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Few-shot learning is a technique in which we attempt to learn a general machine learning model for a set of related tasks and then customize it to new tasks ...

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Amazon at CVPR: Pietro Perona on computer vision’s frontiers
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The Conference on Computer Vision and Pattern Recognition (CVPR) — the premier conference in the field of computer vision — was first held in 1985. Pietro ...

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Amazon Text-to-Speech group’s research at ICASSP 2022
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The automatic conversion of text to speech is crucial to Alexa: it’s how Alexa communicates with customers. The models developed by the Amazon ...

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20B-parameter Alexa model sets new marks in few-shot learning
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Most major advances in AI have come from supervised learning, in which machine learning models are trained on annotated data. But as commercial AI models ...

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