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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2024In this work, we propose a novel sequence-discriminative training criterion for automatic speech recognition (ASR) based on the Conformer Transducer. Inspired by the large-margin classifier framework, we separate the “good” and the “bad” hypotheses in an N-best list produced from a pre-trained transducer model by a margin (τ ), hence the term, Max-Margin Transducer (MMT) loss. It is observed that fine-tuning
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2024Speech codec enhancement methods are designed to remove distortions added by speech codecs. While classical methods are very low in complexity and add zero delay, their effectiveness is rather limited. Compared to that, DNN-based methods deliver higher quality but they are typically high in complexity and/or require delay. The recently proposed Linear Adaptive Coding Enhancer (LACE) addresses this problem
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2024The traditional cascading Entity Resolution (ER) pipeline suffers from propagated errors from upstream tasks. We address this issue by formulating a new end-to-end (E2E) ER problem, Signal-to-Entity (S2E), resolving query entity mentions to actionable entities in textual catalogs directly from audio queries instead of audio transcriptions in raw or parsed format. Additionally, we extend the E2E Spoken Language
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2024Automated speaker identification (SID) is a crucial step for the per-sonalization of a wide range of speech-enabled services. Typical SID systems use a symmetric enrollment-verification framework with a single model to derive embeddings both offline for voice profiles extracted from enrollment utterances, and online from runtime utter-ances. Due to the distinct circumstances of enrollment and runtime, such
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ECIR 20242024Off-policy evaluation (OPE) methods allow us to compute the expected reward of a policy by using the logged data collected by a different policy. However, when the number of actions is large, or certain actions are under-explored by the logging policy, existing estimators based on inverse-propensity scoring (IPS) can have a high or even infinite variance. Saito and Joachims [13] propose marginalized IPS
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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.
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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.
