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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2024Abductive reasoning is the process of making educated guesses to provide explanations for observations. Although many applications require the use of knowledge for explanations, the utilization of abductive reasoning in conjunction with structured knowledge, such as a knowledge graph, remains largely unexplored. To fill this gap, this paper introduces the task of complex logical hypothesis generation, as
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EPTC 20242024Plastic encapsulation is a key feature for System-in-Package (SiP) technology as it provides robust mechanical protection and structural support for all the electronic components enclosed within the package. This allows a highly compact design with minimal component-to-component spacing without compromising long-term reliability and performance. However, as the density and complexity of SiP modules continue
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2024In-context learning (ICL) adapts Large Language Models (LLMs) to new tasks, without requiring any parameter updates, but few an-notated examples as input. In this work, we investigate selective annotation for ICL, where there is a limited budget for annotating examples, similar to low-budget active learning (AL). Although uncertainty-based selection is unreliable with few annotated data, we present COVERICL
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LoG 20242024Graph clustering on text-attributed graphs (TAGS), i.e., graphs that include natural language text as additional node information, is typically performed using graph neural networks (GNNs), which forego the text in lieu of embeddings. While GNN methods ensure scalability and effectively leverage graph topology, text attributes contain rich information that can be leveraged using large language models (LLMs
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2024The superior performance of large foundation models relies on the use of massive amounts of high-quality data, which often contain sensitive, private and copyrighted material that requires formal protection. While differential privacy (DP) is a prominent method to gauge the degree of security provided to the models, its application is commonly limited to the model fine-tuning stage, due to the performance
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.
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A global university competition to drive secure innovation in generative AI technology, which focuses on responsible AI and LLM coding security.
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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.
