In a keynote address at the latest Amazon Machine Learning Conference, Amazon academic research consultant, Stanford professor, and recent Nobel laureate Guido Imbens offered insights on the estimation of causal effects in “panel data” settings.
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The Amazon AGI SF Lab will focus on developing new foundational capabilities for enabling useful AI agents.
Training infrastructure, benchmarks, responsible-AI methodology, and more.
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January 14, 2025Key exchange protocols and authentication mechanisms solve distinct problems and must be integrated in a secure communication system. -
December 24, 2024
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December 24, 2024
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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.
Caltech professor and Amazon Scholar John Preskill wins Bell Prize for applying both classical and quantum computing to the problem of learning from quantum experiments.
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ACM Digital Government Research and Practice (DGOV)2024Labor market information is an important input to labor, workforce, education, and macroeconomic policy. However, granular and real-time data on labor market trends are lacking; publicly available data from survey samples are released with significant lags and miss critical information such as skills and benefits. We use generative Artificial Intelligence to automatically extract structured labor market
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Nature2024A key challenge in realizing practical quantum networks for long-distance quantum communication involves robust entanglement between quantum memory nodes connected by fibre optical infrastructure1–3 . Here we demonstrate a two-node quantum network composed of multi-qubit registers based on silicon-vacancy (SiV) centres in nanophotonic diamond cavities integrated with a telecommunication fibre network. Remote
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2024In this paper, we investigate which questions are challenging for retrieval-based Question Answering (QA). We (i) propose retrieval complexity (RC), a novel metric conditioned on the completeness of retrieved documents, which measures the difficulty of answering questions, and (ii) propose an unsupervised pipeline to measure RC given an arbitrary retrieval system. Our proposed pipeline measures RC more
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2024Multi-document summarization (MDS) is a challenging task, often decomposed to subtasks of salience and redundancy detection, followed by text generation. In this context, alignment of corresponding sentences between a reference summary and its source documents has been leveraged to generate training data for some of the component tasks. Yet, this enabling alignment step has usually been applied heuristically
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2024Multimodal Large Language Models (MLLMs) excel at synthesizing key information from diverse sources. However, generating accurate and faithful multimodal summaries is challenging, primarily due to the lack of appropriate multimodal datasets for fine-tuning that meaningfully integrate textual and visual modalities. To address this gap, we present a new dataset specifically designed for image-text multimodal
Academia
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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.
JORDAN STEAD/(JORDAN STEAD / Amazon)
A global university competition to drive secure innovation in generative AI technology, which focuses on responsible AI and LLM 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.
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We hire world-class academics to work on large-scale technical challenges, while they continue to teach and conduct research at their universities.
