Conversational AI
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Filtering out “forbidden” documents during information retrieval
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Content owners make a lot of effort to eliminate bad content that may adversely affect their customers. Bad content can take many forms, such as fake news, ...

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Johns Hopkins and Amazon announce six fellows and nine faculty research awards
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Amazon and Johns Hopkins University (JHU) today announced the first recipients of PhD fellowships and faculty research awards as part of the JHU + Amazon ...

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Amazon and Virginia Tech announce inaugural fellowship and faculty research award recipients
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Amazon and Virginia Tech today announced the inaugural class of academic fellows and faculty research award recipients as part of the Amazon – Virginia Tech ...

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Five MIT PhD students named as inaugural Amazon Fellows
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Amazon and MIT announced that five MIT doctorate students have been named as the first set of Amazon Fellows as part of the Science Hub. ...

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Preventing updated NLP models from backsliding on particular tasks
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Machine learning (ML) models need regular updates to improve performance, but retraining a model poses risks, such as the loss of backward compatibility or ...

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reMARS revisited: Frontiers of fair and accessible AI
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In June 2022, Amazon re:MARS, the company’s in-person event that explores advancements and practical applications within machine learning, automation, ...

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Personalized federated learning for a better customer experience
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Federated learning (FL) is a framework that allows edge devices (e.g., Alexa devices) to collaboratively train a global model while keeping customers’ data ...

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Amazon releases code, datasets for developing embodied AI agents
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Alexa Arena is a new embodied-AI framework developed to push the boundaries of human-robot interaction. It offers an interactive, user-centric framework for ...

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Responsible AI in the generative era
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In recent years, and even recent months, there have been rapid and dramatic advances in the technology known as generative AI. Generative AI models are ...

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Differential privacy for deep learning at GPT scale
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Deep-learning models are data driven, and that data may contain sensitive information that requires privacy protection. Differential privacy (DP) is a ...

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