A new approach to reducing carbon emissions reveals previously hidden emission “hotspots” within value chains, helping organizations make more detailed and dynamic decisions about their future carbon footprints.
How agentic systems work under the hood — and how AWS’s new AgentCore framework implements their essential components.
New technologies are helping vulnerable communities produce maps that integrate topographical, infrastructural, seasonal, and real-time data — an essential tool for many humanitarian endeavors.
In-context learning enables a model that can solve forecasting tasks with an arbitrary number of dimensions in a zero-shot manner.
"Kaputt" features 238,000+ images that advance the state of the art in detecting visual defects across complex retail applications.
Customer-obsessed science
Research areas
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November 20, 20254 min readA new evaluation pipeline called FiSCo uncovers hidden biases and offers an assessment framework that evolves alongside language models. -
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September 2, 20253 min read
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Featured news
Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
The collaboration will advance research in generative AI, robotics, natural language processing and cloud computing while fostering innovation in foundational and emerging technologies.
University teams battle to harden and hack AI coding assistants in head-to-head tournament
David Chang/Getty Images/iStockphoto
Led by David Luan and Pieter Abbeel, the lab will focus on developing new foundational capabilities for enabling useful AI agents.
The company's new state-of-the-art foundation models deliver frontier intelligence and industry-leading price performance.
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Applied Physics Letters2023Robust, low-loss photonic packaging of on-chip nanophotonic circuits is a key enabling technology for the deployment of integrated photon- ics in a variety of classical and quantum technologies including optical communications and quantum communications, sensing, and trans- duction. To date, no process has been established that enables permanent, broadband, and cryogenically compatible coupling with sub-dB
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NeurIPS 2023 Workshop on Efficient Natural Language and Speech Processing (ENLSP)2023This paper proposes a framework leveraging small samples from different Automatic Speech Recognition (ASR) data sources to predict model performance and facilitate ASR data selection decisions. By utilizing data distribution distance and a mapping technique inspired by neural scaling laws, our framework estimates the model performance for various data mixtures within the disclosed range and extrapolates
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NeurIPS 2023 Workshop on Deep Generative Models for Health2023Writing radiology reports from medical images requires a high level of domain expertise. It is time-consuming even for trained radiologists and can be error-prone for inexperienced radiologists. It would be appealing to automate this task by leveraging generative AI, which has shown drastic progress in vision and language understanding. In particular, Large Language Models (LLM) have demonstrated impressive
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Transfer learning, reinforcement learning for adaptive control optimization under distribution shiftNeurIPS 2023 Workshop on Distribution Shifts (DistShifts)2023Many control systems rely on a pipeline of machine learning models and handcoded rules to make decisions. However, due to changes in the operating environment, these rules require constant tuning to maintain optimal system performance. Reinforcement learning (RL) can automate the online optimization of rules based on incoming data. However, RL requires extensive training data and exploration, which limits
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NeurIPS 20232023We study the convergence behavior of the celebrated temporal-difference (TD) learning algorithm. By looking at the algorithm through the lens of optimization, we first argue that TD can be viewed as an iterative optimization algorithm where the function to be minimized changes per iteration. By carefully investigating the divergence displayed by TD on a classical counter example, we identify two forces
Collaborations
View allWhether you're a faculty member or student, there are number of ways you can engage with Amazon.
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Gretchen Ertl
The program offers unrestricted funds and other resources to support research at academic institutions and non-profit organizations in areas that align with our mission.
A global university competition to drive secure innovation in generative AI technology, which focuses on responsible AI and large language model coding security.
Credit: Wolfram Scheible
We partner with particular academic organizations across the world for deep and sustained collaborations in multiple research areas of mutual interest.
Courtesy of Pai-Ling Yin
We hire world-class academics to work on large-scale technical challenges, while they continue to teach and conduct research at their universities.
