Using the Neuron Kernel Interface, a Reactor–AWS collaboration tackled the dynamic shapes, memory access patterns, and cache management that make real-time autoregressive diffusion hard—building techniques that generalize across models.
Three new papers from Amazon Bio Discovery address bottlenecks in AI-driven antibody engineering, from benchmarking binding predictors to experimentally validating de novo design.
New research indicates that AI agents learn compressible models of data, which don’t have enough space to enable memorization.
How the Verus "program verifier", which automatically checks code against a mathematical specification of its functionality, helps increase security assurance in software projects.
Ten years after we founded the Automated Reasoning Group, mathematical logic has moved from academic research into production services that secure millions of customer workloads — demonstrating that systems can be provably correct, not just probably correct.
Customer-obsessed science
Research areas
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October 1, 202610 min readAugmenting a network graph with agentic AI produces a “digital twin” that can help isolate network failures. -
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August 21, 20269 min read
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July 30, 20268 min read
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July 29, 20266 min read
Featured news
The Build on Trainium program is a $110 million credit initiative supporting AI research at 30 universities including Stanford, UC Berkeley, UIUC, UCLA, CMU, and MIT, with a focus on Responsible AI.
The Antibody Developability Benchmark is powered by one of the most diverse antibody datasets in public literature, enabling transparent performance evaluation for AI-guided antibody design.
Challenge pushes teams to demonstrate measurable gains in secure-coding performance while building AI agents that advance real-world utility and reliability at scale.
Initiative will fund over 100 doctoral students researching machine learning, computer vision, and natural-language processing at nine universities.
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RecSys 20222022The modern e-commerce web pages have brought better customer experience and more profitable services by whole page optimization at different granularity, e.g., page layout optimization, item ranking optimization, etc. Generating the proper page layout per customer’s request is one of the vital tasks during the web page rendering process, which can directly impact customers’ shopping experience and their
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KDD 2022 Workshop on Online and Adaptive Recommender Systems2022Twitch is a community driven live streaming video service which uses recommendations trained on implicit feedback data. While this data is available in large quantities, it is subject to various biases and shortcomings. In particular, Twitch watch history data is heavily affected by the unpredictable and irregular behavior of users and streams going online and offline. Two resulting issues are: accounting
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IJCAI 20222022We introduce Neural Contextual Anomaly Detection (NCAD), a framework for anomaly detection on time series that scales seamlessly from the unsupervised to supervised setting, and is applicable to both univariate and multivariate time series. This is achieved by combining recent developments in representation learning for multivariate time series, with techniques for deep anomaly detection originally developed
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CVPR 2022 Workshop on Computer Vision for Fashion, Art, and Design2022Predicting outfit compatibility and retrieving complementary items are critical components for a fashion recommendation system. We present a scalable framework, OutfitTransformer, that learns compatibility of the entire outfit and supports large-scale complementary item retrieval. We model outfits as an unordered set of items and leverage self-attention mechanism to learn the relationships between items
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SIGDIAL 20222022Embodied agents need to be able to interact in natural language-understanding task descriptions and asking appropriate follow up questions to obtain necessary information to be effective at successfully accomplishing tasks for a wide range of users. In this work, we propose a set of dialog acts for modelling such dialogs and annotate the TEACh dataset that includes over 3,000 situated, task oriented conversations
Collaborations
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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.
