Amazon researchers' papers at NAACL predominately focus on LLMs. This paper guide sorts them by those that deal explicitly with LLMs or not, although in many cases, the ones that don’t present general techniques or datasets that could be used with either LLMs or more-traditional models. #NAACL2024 #LLMs
Amazon Science
Research Services
Seattle, Washington 356,325 followers
The latest news and research from Amazon’s science community. #AmazonScience
About us
Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Follow us on LinkedIn and visit our website to get a deep dive on innovation at Amazon, and explore the many ways you can engage with our scientific community. #AmazonScience
- Website
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https://www.amazon.science
External link for Amazon Science
- Industry
- Research Services
- Company size
- 10,001+ employees
- Headquarters
- Seattle, Washington
- Founded
- 2020
- Specialties
- Artificial Intelligence, Machine Learning, Computer Vision, Cloud, Economics, Sustainability, AI, ML, Conversational AI, Natural Language Processing, NLP, Robotics, Security, Privacy, Information, Knowledge Management, Operations, Scientific Research, Search, Amazon, and Alexa
Updates
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We're proud to be a diamond sponsor of this year's ACM SIGMOD/PODS conference, taking place this week in Santiago, Chile. Explore the list of papers below, and read them on our website: amzn.to/3Vh0HXi • Amazon MemoryDB: A fast and durable memory-first cloud database • Automated multidimensional data layouts in Amazon Redshift • COSMO: A large-scale e-commerce common sense knowledge generation and serving system at Amazon • Intelligent scaling in Amazon Redshift • Predicate caching: Query-driven secondary indexing for cloud data warehouses • Stage: Query execution time prediction in Amazon Redshift #SIGMOD2024 #AmazonScience #CloudComputing
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In our latest newsletter we cover Amazon's open-source model for time series forecasting, a new knowledge graph framework that uses #LLMs to discern commonsense relationships, research collaborations with UW and Columbia, new features for Amazon Bedrock, and more.
May 2024
Amazon Science on LinkedIn
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Registration has opened for the fourth edition of Amazon's ML Summer School in India, which launches next month and welcomes students enrolled in any recognized institute across the country who are expected to graduate in 2025 or 2026. The program offers an intensive course on key ML topics, and the opportunity to learn from and interact with Amazon scientists, to help students prepare for a career in machine learning. Learn more, and register by June 21: amzn.to/4e8Txgs #MachineLearning #ML
Register for Amazon ML Summer School India 2024
amazonmlsummerschoolindia.splashthat.com
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Deep metric learning is a powerful tool, but it yields inconsistent distances between data embeddings, which can hamper nearest-neighbor search. At this year's ICLR, Amazon researchers showed how to make distances more consistent, improving model performance. #ICLR2024 #MachineLearning
More reliable nearest-neighbor search with deep metric learning
amazon.science
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Find out how Amazon is using generative AI and computer vision to process multimodal information by synthesizing evidence from images captured during the fulfillment process and combining it with written customer feedback to help uncover both defects and, wherever possible, their cause — to address issues at the root before a product reaches the customer. #GenAI #ComputerVision #MachineLearning
How Project P.I. helps Amazon remove imperfect products
amazon.science
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With the support of an Amazon Research Award, a team of researchers led by the University of Washington have developed a new printed circuit board (PCB) that performs on par with traditional materials and can be recycled repeatedly with negligible material loss. Learn more about the team’s research, which was published in Nature Sustainability. Article: https://amzn.to/4avHruX Publication: https://amzn.to/3UQpb9H #AmazonScience #Sustainability
New circuit boards can be repeatedly recycled
washington.edu
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To help Amazon’s recommendation engine make more relevant commonsense inferences, our researchers have been building a knowledge graph that uses #LLMs to encode the relationships between products in the Amazon Store and the human contexts in which they play a role — their functions, their audiences, the locations in which they’re used, and the like. Learn more about the framework, COSMO, which will be presented at next month's Conference on Management of Data (SIGMOD).
COSMO: A large-scale e-commerce common sense knowledge generation and serving system at Amazon
amazon.science
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Join Amazon researchers on June 11 for an online panel about managing science teams. Featuring Amazon science managers Federica Cerina, Martin Gross, and Mauro Piacentini, discussion topics include how to transition from a scientist to manager role, tips to manage successfully, and lessons learned from personal experiences. Register here: amzn.to/4bXEc0h #AmazonScience #CareerDevelopment
Navigating the Scientist-to-Manager Transition: A Virtual Panel Discussion
app.brazenconnect.com
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At next month's SIGMOD 2024, researchers from Amazon Web Services (AWS) will present a paper on Amazon MemoryDB, where they will describe its architecture and how they leveraged Redis, an open-source data structure store, to build an enterprise-grade cloud database. Paper: https://lnkd.in/eEuquM8Q Conference: https://lnkd.in/esVMQcav #AWS #ML #Databases
Amazon MemoryDB: A fast and durable memory-first cloud database
amazon.science