As AI models grow larger, they become less insightful, not more. To ensure that they continue to learn, we need to reduce their inference time.
How do you match AI warnings about future events with what actually happens? A KDD test-of-time award recognizes a 2014 approach that modern systems still need.
In-context learning enables a model that can solve forecasting tasks with an arbitrary number of dimensions in a zero-shot manner.
The pandemic turbo-charged retail growth — teams of scientists at Amazon forged a path forward to handle the scale.
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February 2, 202610 min readEvery NFL game generates millions of tracking data points from 22 RFID-equipped players. Seventy-five machine learning models running on AWS process that data in under a second, transforming football into a sport where every movement is measured, modeled, and instantly analyzed. -
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December 29, 20256 min read
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Hosted by Danielle Perszyk, cognitive scientist at Amazon's AGI Lab, the podcast features conversations with leading AI researchers about the breakthroughs needed to achieve general intelligence.
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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Nature Digital Medicine2023Waist-to-hip circumference ratio (WHR) is now recognized as among the strongest shape biometrics linked with health outcomes, although use of this phenotypic marker remains limited due to the inaccuracies in and inconvenient nature of flexible tape measurements when made in clinical and home settings. Here we report that accurate and reliable WHR estimation in adults is possible with a smartphone application
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RecSys 2023 Workshop on Learning and Evaluating Recommendations with Impressions (LERI 2023)2023While recommender systems have significantly benefited from implicit feedback, they have often missed the nuances of multi-behavior interactions between users and items. Historically, these systems either amalgamated all behaviors, such as impression (formerly view), add-to-cart, and buy, under a singular ’interaction’ label, or prioritized only the target behavior, often the buy action, discarding valuable
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CIKM 20232023In e-commerce, product classification is widely used for various purposes. Misclassifying products can cause compliance issues and hurt the company’s reputation. To address this problem, we propose an automated system to proactively detect product misclassifications by overcoming several challenges. A large ecommerce retailer can sell billions of distinct products, on which many thousands of classification
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CIKM 20232023Growth of e-commerce has enabled the creation of thousands of small-scale brands. However, these brands lack information on a) what new products to develop and b) how to refine existing products to improve business metrics. We present a comprehensive Product Design Insights and Guidance service (named PRODIGY) that mines product attributes data available on e-commerce platforms and surface insights on a
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ESEC/FSE 20232023Automated static dataflow analysis is an effective technique for detecting security critical issues like sensitive data leak, and vulnerability to injection attacks. Ensuring high precision and recall requires an analysis that is context, field and object sensitive. However, it is challenging to attain high precision and recall and scale to large industrial code bases. Compositional style analyses in which
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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.
