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How a ‘Think Big’ idea helped bring Lookout for Vision to life

Learn about the science behind the new machine learning product for manufacturers — and how a unique approach solved a complex problem.Read More

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Amazon Alexa scientists Yang Liu and Ruhi Sarikaya named IEEE Fellows

Scientists are recognized for their contributions to conversational understanding systems.Read More

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Amazon takes top three spots in Audio Anomaly Detection Challenge

Team from Amazon Web Services also wins the best-paper award at the Workshop on Detection and Classification of Acoustic Scenes and Events.Read More

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A version of the BERT language model that’s 20 times as fast

Determining the optimal architectural parameters reduces network size by 84% while improving performance on natural-language-understanding tasks.Read More

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Amazon Research Award recipient develops new tool to diagnose dystonia

Dr. Kristina Simonyan and her team created an AI-based deep learning platform that offers patients some peace of mind.Read More

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Machine learning models that act on encrypted data

A privacy-preserving version of the popular XGBoost machine learning algorithm would let customers feel even more secure about uploading sensitive data to the cloud.Read More

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The science behind Endel’s AI-powered soundscapes

Alexa Fund company releases updated and streamlined skill for Alexa that includes “AI Lullaby” soundscape with vocals, music, and voiceovers by Grimes.Read More

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Mitigating social bias in knowledge graph embeddings

Method significantly reduces bias while maintaining comparable performance on machine learning tasks.Read More

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Amazon panel discusses fairness in AI

Watch the recorded panel discussion that aired the week of NeurIPS 2020.Read More

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Alexa & Friends features Ruhi Sarikaya, Alexa AI director of applied science

Newly named IEEE Fellow discusses his experience in the field of conversational AI, and the ways he and his team are working to make Alexa more intelligent.Read More

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Recent Posts

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  • Enabling Differentially Private Federated Learning for Speech Recognition: Benchmarks, Adaptive Optimizers, and Gradient Clipping
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