Customer-obsessed science


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March 24, 2023By leveraging neural vocoding, Amazon Chime SDK’s new deep-redundancy (DRED) technology can reconstruct long sequences of lost packets with little bandwidth overhead.
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March 21, 2023Tailoring neighborhood sizes and sampling probability to nodes’ degree of connectivity improves the utility of graph-neural-network embeddings by as much as 230%.
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March 20, 2023With Alexa Arena, developers can create simulated missions in which humans interact with virtual robots, providing a natural way to build generalizable AI models.
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April 30 - May 4, 2023
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May 1 - 5, 2023
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May 3 - 5, 2023
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March 23, 2023The center will support UIUC researchers in their development of novel approaches to conversational AI systems.
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March 23, 2023How Amazon is shaping a set of initiatives to enable academia-based talent to harmonize their passions, life stations, and career ambitions.
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March 15, 2023The submission period opens March 15 and closes on April 26.
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March 16, 2023SURE provides students from historically underrepresented communities with research experiences at top-tier universities.
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2023This paper introduces Amazon Robotic Manipulation Benchmark (ARMBench), a large-scale, object-centric benchmark dataset for robotic manipulation in the context of a warehouse. Automation of operations in modern warehouses requires a robotic manipulator to deal with a wide variety of objects, unstructured storage, and dynamically changing inventory. Such settings pose challenges in perceiving the identity
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2023Autonomous exploration to build a map of an unknown environment is a fundamental robotics problem. However, the quality of the map directly influences the quality of subsequent robot operation. Instability in a simultaneous localization and mapping (SLAM) system can lead to poor-quality maps and subsequent navigation failures during or after exploration. This becomes particularly noticeable in consumer
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2023Advances in neural modeling have achieved state-of-the-art (SOTA) results on public natural language processing (NLP) benchmarks, at times surpassing human performance. However, there is a gap between public benchmarks and real-world applications where noise, such as typographical or grammatical mistakes, is abundant and can result in degraded performance. Unfortunately, works which evaluate the robustness
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2023Fixed-point (FXP) inference has proven suitable for embedded devices with limited computational resources, and yet model training is continually performed in floating-point (FLP). FXP training has not been fully explored and the non-trivial conversion from FLP to FXP presents unavoidable performance drop. We propose a novel method to train and obtain FXP convolutional keyword-spotting (KWS) models. We combine
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2023Automatic detection of bioacoustic sound events is crucial to monitor wildlife. With a tedious annotation process, limited labeled events and large volume of recordings, few-shot learning (FSL) is suitable for such event detections based on a few examples. Typical FSL frameworks for sound detection make use of Convolutional Neural Networks (CNNs) to extract features. However, CNNs fail to capture long-range
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March 08, 2023This year’s cohort is researching, among other topics, online changepoint detection algorithms and automated reasoning.
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March 01, 2023New fellows include PhD candidates in operations research and computer science.
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February 21, 2023University teams are competing to develop a bot that best responds to customer commands in a virtual world.
Working at Amazon
View allMeet the people driving the innovation essential to being the world’s most customer-centric company.
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March 14, 2023Ren Zhang and her team tackle the interesting science challenges behind surfacing the most relevant offerings.
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February 28, 2023How the former astrobiology professor is charting new territory as a scientist for Amazon Flex.
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February 08, 2023How her background helps her manage a team charged with assisting internal partners to answer questions about the economic impacts of their decisions.