Customer-obsessed science
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October 04, 2024Rufus leverages AWS chips Trainium and Inferentia, AWS’s elasticity and scalability, and a custom-built large language model to quickly answer shoppers’ questions. -
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 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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NeurIPS 2023 Workshop on Table Representation Learning2023Tabular neural network (NN) has attracted remarkable attentions and its recent advances have gradually narrowed the performance gap with respect to tree-based models on many public datasets. While the mainstreams focus on calibrating NN to fit tabular data, we emphasize the importance of homogeneous embeddings and alternately concentrate on regularizing tabular inputs through supervised pretraining. Specifically
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NeurIPS 2023 Workshop on Table Representation Learning2023Tables stored in databases and tables which are present in web pages and articles account for a large part of semi-structured data that is available on the internet. It motivates the need to develop a modeling approach with large language models (LLMs) which can be used to solve diverse table tasks such as semantic parsing, question answering as well as classification problems. Traditionally, there existed
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EMNLP 20232023A particularly successful class of approaches for few-shot learning combines language models with prompts — handcrafted task descriptions that complement data samples. However, designing prompts by hand for each task commonly requires domain knowledge and substantial guesswork. We observe, in the context of classification tasks, that instruction-finetuned language models are remarkably robust towards some
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EMNLP 20232023Rich and diverse knowledge-bases (KB) are foundational building blocks for online knowledge-sharing communities such as StackOverflow and Quora and applications such as conversational assistants (aka chatbots). A popular format for knowledge bases is question-answer pairs (or FAQs), where questions are designed to accurately match a multitude of queries. In this paper, we address the problem of automatic
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EMNLP 20232023We present MultiCoNER V2, a dataset for fine-grained Named Entity Recognition covering 33 entity classes across 12 languages, in both monolingual and multilingual settings. This dataset aims to tackle the following practical challenges in NER: (i) effective handling of fine-grained classes that include complex entities like movie titles, and (ii) performance degradation due to noise generated from typing
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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Photo by Zak BrickettLearn more about the awards and recognitions that Amazon researches from around the world have been honored with during their tenure.
