Customer-obsessed science
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September 30, 2024From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money.
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September 19, 2024“Agentic workflows” that use multiple, fine-tuned smaller LLMs — rather than one large one — can improve efficiency.
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September 16, 2024A position paper presented at ACL proposes a framework for more-accurate human evaluation of LLMs.
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September 29 - October 4, 2024
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October 21 - 25, 2024
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September 25, 2024
Now open until November 6, Amazon Research Awards will be seeking proposals in the following research areas: AI for Information Security, Automated Reasoning, AWS AI, AWS Cryptography, and Sustainability.
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ICDE 20242024How can we effectively generate missing data transformations among tables in a data repository? Multiple versions of the same tables are generated from the iterative process when data scientists and machine learning engineers fine-tune their ML pipelines, making incremental improvements. This process often involves data transformation and augmentation that produces an augmented table based on its base version
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ICRA 20242024Robotic manipulation is a key enabler for automation in the fulfillment logistics sector. Such robotic systems require perception and manipulation capabilities to handle a wide variety of objects. Existing systems either operate on a closed set of objects or perform object-agnostic manipulation which lacks the capability for deliberate and reliable manipulation at scale. Object identification (ID) unlocks
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Krylov cubic regularized Newton: A subspace second-order method with dimension-free convergence rateAISTATS 20242024Second-order optimization methods, such as cubic regularized Newton methods, are known for their rapid convergence rates; nevertheless, they become impractical in high-dimensional problems due to their substantial memory requirements and computational costs. One promising approach is to execute second-order updates within a lower-dimensional subspace, giving rise to subspace second-order methods. However
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Predicting customer preferences for each item is a prerequisite module for most recommender systems in e-commerce. However, the sparsity of behavioral data is often a challenge to learn accurate prediction models. Given millions of items, each customer may only be able to interact with a small subset of them over time. This sparse behavioral data is insufficient to represent item-customer and item-item
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2024We introduce a novel and efficient approach for text-based video-to-video editing that eliminates the need for resource-intensive per-video-per-model finetuning. At the core of our approach is a synthetic paired video dataset tailored for video-to-video transfer tasks. Inspired by Instruct Pix2Pix’s image transfer via editing instruction, we adapt this paradigm to the video domain. Extending the Prompt-to-Prompt
Resources
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We look for talent from around the world for applied scientists, data scientists, economists, research scientists, scholars, academics, PhDs, and interns.
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We collaborate with leading academic organizations to drive innovation and to ensure that research is creating solutions whose benefits are shared broadly.
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Learn more about the awards and recognitions that Amazon researches from around the world have been honored with during their tenure.