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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Click-through Rate (CTR) module is the foundation block of recommendation system and used for search, content selection, advertising, video streaming etc. CTR is modelled as a classification problem and extensive research is done to improve the CTR models. However, uncertainty method for these models are still an unexplored area. In this work we analyse popular uncertainty methods in the context of recommendation
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The problem of search relevance in the E-commerce domain is a challenging one since it involves understanding the intent of a user’s short nuanced query and matching it with the appropriate products in the catalog. This problem has traditionally been addressed using language models (LMs) and graph neural networks (GNNs) to capture semantic and inter-product behavior signals, respectively. However, the rapid
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International Conference on Business Forecasting and Marketing Intelligence 20242024Accurate sell-in and sell-out forecasting is a ubiquitous problem in the retail industry. It is an important element of any demand planning activity. As a global food and beverage company, Nestle´ has hundreds of products in each geographical location that they operate in. Each product has its sell-in and sell-out time series data, which are forecasted on a weekly and monthly scale for demand and financial
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Picture Coding Symposium 20242024In an adaptive bitrate streaming application, the efficiency of video compression and the encoded video quality depend on both the video codec and the quality metric used to perform encoding optimization. The development of such a quality metric need large scale subjective datasets. In this work we merge several datasets into one to support the creation of a metric tailored for video compression and scaling
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2024Large Language Models (LLMs) trained on large volumes of data excel at various natural language tasks, but they cannot handle tasks requiring knowledge that has not been trained on previously. One solution is to use a retriever that fetches relevant information to expand LLM’s knowledge scope. However, existing textual-oriented retrieval-based LLMs are not ideal on structured table data due to diversified
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.