Customer-obsessed science
Research areas
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July 10, 20265 min readHydroShear, a new physics-based simulator, teaches robots how to use their sense of touch to perform complex manipulation tasks, in a way that transfers seamlessly to the real world. -
July 9, 202610 min read -
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Featured news
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 20232023Query reformulation (QR) is a widely used technique in web and product search. In QR, we map a poorly formed or low coverage user query to a few semantically similar queries that are rich in product coverage, thereby enabling effective targeted searches with less cognitive load on the user. Recent QR approaches based on generative language models are superior to informational retrieval-based methods but
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RecSys 20232023As E-commerce and subscription services scale, personalized recommender systems are often needed to further drive long term business growth in acquisition, engagement, and retention of customers. However, long-term metrics associated with these goals can require several months to mature. Additionally, deep personalization also demands a large volume of training data that take a long time to collect. These
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RecSys 20232023Modern recommender systems usually include separate recommendation carousels such as ‘trending now’ to list trending items and further boost their popularity, thereby attracting active users. Though widely useful, such ‘trending now’ carousels typically generate item lists based on simple heuristics, e.g., the number of interactions within a time interval, and therefore still leave much room for improvement
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ICCV 20232023We propose a Bidirectional Alignment for domain adaptive Detection with Transformers (BiADT) to improve cross domain object detection performance. Existing adversarial learning based methods use gradient reverse layer (GRL) to reduce the domain gap between the source and target domains in feature representations. Since different image parts and objects may exhibit various degrees of domain-specific characteristics
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AutoML Conference 20232023We introduce AutoGluon–TimeSeries—an open-source AutoML library for probabilistic time series forecasting.1 Focused on ease of use and robustness, AutoGluon–TimeSeries enables users to generate accurate point and quantile forecasts with just 3 lines of Python code. Built on the design philosophy of AutoGluon, AutoGluon–TimeSeries leverages ensembles of diverse forecasting models to deliver high accuracy
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.
