By learning the idiosyncrasies of accumulated layers of legacy systems, AI agents can preserve institutional knowledge and provide a unified interface to a range of services.
As AI agents become more autonomous, the key challenge isn't what they can do; it's how to design the human side of the equation.
What machine learning theorists learned using AI agents to generate proofs — and what comes next.
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.
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Research areas
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March 20, 202615 min readSimplifying and clarifying the assembly code for core operations enabled automated optimization and verification. -
March 19, 202611 min read -
February 17, 20263 min read
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January 13, 20267 min read
Featured news
Now open across seven research areas, including Agentic AI and Robotics. Applicants receive unrestricted funds, AWS promotional credits, and training resources. Submission deadline is May 6
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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2025Open-vocabulary (OV) 3D object detection is an emerging field, yet its exploration through image-based methods remains limited compared to 3D point cloud-based methods. We introduce OpenM3D, a novel open-vocabulary multi-view indoor 3D object detector trained without human annotations. In particular, OpenM3D is a single-stage detector adapting the 2D-induced voxel features from the ImGeoNet model. To support
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KDD 2025 Workshop on AI for Supply Chain2025Neural networks have lead to improvements in demand forecast accuracy for supply chain and retailers. These neural networks have been designed and trained on data representing their particular use cases. We investigate the zero-shot performance of those deep learning models on retail dataset outside of their original use case. As such, we focus on the hypothesis that this zero-shot performance of deep learning
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SigDial 2025 DSTC-12 Workshop2025Conversational analytics has been on the forefront of transformation driven by the advances in Speech and Natural Language Processing techniques. Rapid adoption of Large Language Models (LLMs) in the analytics field has taken the problems that can be automated to a new level of complexity and scale. In this paper, we introduce Theme Detection as a critical task in conversational analytics, aimed at automatically
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IJCAI 2025 Workshop on User-Aligned Assessment of Adaptive AI Systems2025Effectively assessing AI systems, particularly those operating in specialized domains or producing dynamic outputs, requires translating nuanced human expertise into scalable, quantitative measures. Traditional metrics often fall short in capturing qualitative requirements that domain experts intuitively grasp. This paper presents a novel framework that systematically transforms qualitative expert feedback
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RecSys 20252025Audio streaming services, on both voice assistants and in visual apps, often field requests such as 'play more like Foo Fighters.' The service then returns a sequence of tracks that is both relevant to the request and personalized to the requester. While it is natural to evaluate the policies that produce these sequences in terms of customer engagement, such metrics do not assess their performance on other
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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.
