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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, 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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COLING 20222022Relational web-tables are significant sources of structural information that are widely used for relation extraction and population of facts into knowledge graphs. To transform the webtable data into knowledge, we need to identify the relations that exist between column pairs. Currently, there are only a handful of publicly available datasets with relations annotated against natural web-tables. Most datasets
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Frontiers in Artificial Intelligence2022Player identification is an essential and complex task in sports video analysis. Different strategies have been devised over the years and identification based on jersey numbers is one of the most common approaches given its versatility and relative simplicity. However, automatic detection of jersey numbers is challenging due to changing camera angles, low video resolution, small object size in wide-range
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ACM Transactions on Recommender Systems2022Modern recommender systems are often modelled under the sequential decision-making paradigm, where the system decides which recommendations to show in order to maximise some notion of either imminent or long-term reward. Such methods often require an explicit model of the reward a certain context-action pair will yield – for example, the probability of a click on a recommendation. This common machine learning
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KDD 2022 Workshop on Deep Learning Practice and Theory for High-Dimensional Sparse and Imbalanced Data (DLP)2022In this paper, we introduce a targeted data enrichment framework to mitigate the problem of biased training data distribution. In real world applications, it is often observed that the training data distribution differs from the online live traffic data due to multiple reasons such as topic changes, seasonalities, the nature of users. Our targeted data augmentation techniques generate samples that are most
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ICDM 2022 Workshop on Foundation Models for Vision and Language2022To solve video-and-language grounding tasks, the key is for the network to understand the connection between the two modalities. For a pair of video and language description, their semantic relation is reflected by their encodings’ similarity. A good multi-modality encoder should be able to well capture both inputs’ semantics and encode them in the shared feature space where embedding distance gets properly
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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.
