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
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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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2024Training a supervised news summarization model requires large amounts of high-quality training data consisting of news articles paired with reference summaries. However, obtaining such data is costly, and existing datasets contain considerable amount of noise. We present a new large-scale and high-quality dataset for supervised abstractive news summarization containing 1.3 million training samples, which
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ESWC 20242024We present an approach to represent composite values (lists and maps, in particular) as literals in RDF data, and to extend SPARQL with features related to such literals. These extensions include an aggregation function to produce these composite values, functions to operate on these composite values in expressions, and a new operator to unfold such composite values into their individual components. As
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SIOP 20242024Correlating assessment scores with performance in role (PIR) metrics provides a powerful form of validation evidence, but is complicated by the absence of PIR metrics for applicants who were not hired. Traditional range restriction perspectives state that the problem is a lack of PIR metrics for low assessment scores, and typical corrections make strong assumptions about how the relationship among incumbents
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PQC Standardization Conference 20242024The QC-MDPC code-based KEM BIKE is an alternative candidate for standardization for the NIST Post-Quantum Cryptography Standardization Project. Per NIST’s report [2] “The BIKE cryptosystem was initially designed for ephemeral key use but has now been claimed to also support static key use”. BIKE uses the BGF decoder of [9] where its Decoding Failure Rate (DFR) is estimated by means of an extrapolation method
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ICLR 2024 Workshop on Secure and Trustworthy Large Language Models (SET LLM)2024In this work, we propose sequence-level certainty as a common theme over hallucination in Knowledge Grounded Dialogue Generation (KGDG). We explore the correlation between the level of hallucination in model responses and two types of sequence-level certainty: probabilistic certainty and semantic certainty. Empirical results reveal that higher levels of both types of certainty in model responses are correlated
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.
