Amazon scientists and policy experts discuss how the company’s responsible-AI pipeline embeds safety and values throughout the AI development lifecycle.
Agentic mechanism enables Amazon and vendors to optimize supply chain management without disclosing private information.
How we reproduced three attacks that extract private training data from AI models and the cryptographic defenses that stop them.
Amazon engineers and scientists have created new tools to optimize delivery networks under uncertainty — and keep them adapting without missing a beat.
Isabelle/HOL's balance of expressiveness, automation, and scalability enabled the world's first formally verified cloud hypervisor.
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May 15, 20265 min readA new scaling law that relates particular architectural choices to loss helps identify models that improve throughput by up to 47% with no loss of accuracy. -
May 14, 202616 min read -
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April 15, 20268 min read
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Hosted by Danielle Perszyk, cognitive scientist at Amazon's AGI Lab, the podcast features researchers tackling the hardest problems in agentic AI — from building reliable perception systems to designing training environments that mirror human learning.
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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CIKM 20232023Predicting the click-through rate (CTR) of an item is a fundamental task in online advertising and recommender systems. CTR prediction models are typically trained on user click data from traffic logs. However, users are more likely to interact with items that were shown prominently on a website. CTR models often overestimate the value of such items and show them more often, at the expense of items of higher
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SPIE 2023 Applications of Digital Image Processing XLVI2023Super-resolution video coding describes the process of coding video at lower resolution and upsampling the result. This process is included in the AV1 standard, which ensures the same super-resolution process is employed on all receiving devices. Regrettably, the design is limited to horizontal scaling with a maximum scale factor of two. In this paper, we analyze the benefit of enabling two-dimensional
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CIKM 20232023Identifying similar products in e-commerce is useful in discovering relationships between products, making recommendations, and in-creasing diversity in search results. Product representation learning is the first step to define a generalized product similarity metric for search. The second step is to extend similarity search to a large scale (e.g., e-commerce catalog scale) without sacrificing quality.
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CIKM 2023 Industry Day2023In industrial settings, it is often necessary to achieve language-level accuracy targets. For example, Amazon business teams need to build multilingual product classifiers that operate accurately in all European languages. It is unacceptable for the accuracy of product classification to meet the target in one language (e.g, English), while falling below the target in other languages (e.g, Portuguese). To
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CIKM 20232023Traditionally, catalog relationship problems in e-commerce stores have been handled as pairwise classification tasks, which limit the ability of machine learning models to learn from the diverse relationships among different entities in the catalog. In this paper, we leverage heterogeneous graphs and Graph Neural Networks (GNNs) for improving catalog relationship inference. We start from investigating how
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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.
