New research indicates that AI agents learn compressible models of data, which don’t have enough space to enable memorization.
How the Verus "program verifier", which automatically checks code against a mathematical specification of its functionality, helps increase security assurance in software projects.
Ten years after we founded the Automated Reasoning Group, mathematical logic has moved from academic research into production services that secure millions of customer workloads — demonstrating that systems can be provably correct, not just probably correct.
PatientAgentBench generates a synthetic patient health record, a realistic clinical vignette, and a patient agent that converses with the AI system under evaluation, to capture what a patient-facing agent actually has to do.
A new chiplet architecture, custom die-to-die connectivity, and support for DDR5-8800 memory and the latest PCIe gen6 interconnects improve performance by 25% for general-purpose and agentic AI workloads.
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August 26, 20265 min readDiscounting the opinions of LLM judges with highly correlated outputs ensures that panels of judges reflect a true diversity of perspectives. -
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The Build on Trainium program is a $110 million credit initiative supporting AI research at 30 universities including Stanford, UC Berkeley, UIUC, UCLA, CMU, and MIT, with a focus on Responsible AI.
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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ACM L@S 20202020E-learning is becoming popular as it provides learners the flexibility, targeted resources across the internet, personalized guidance, and immediate feedback during learning. However, lack of social interaction, an indispensable component in developing some skills, has been a pain point in e-learning. We propose using Alexa, a voice-controlled Intelligent Personal Assistants (IPA), in e-learning to provide
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ACM L@S 20202020Deep learning based knowledge tracing approaches achieve high accuracy in mastery prediction with pattern extraction on a large learning behavior data set. However, when there is little training data available, these approaches either fail to extract the key patterns or result in over fitting. Ideally, we aim to provide a similar learning experience to both the first group of learners, who interact with
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ACL 2020 Workshop on NLP for Medical Conversations2020Automatic speech recognition (ASR) systems in the medical domain that focus on transcribing clinical dictations and doctor-patient conversations often pose many challenges due to the complexity of the domain. ASR output typically undergoes automatic punctuation to enable users to speak naturally, without having to vocalise awkward and explicit punctuation commands, such as “period”, “add comma” or “exclamation
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ACM L@S 20202020Online learning systems that provide actionable and personalized guidance can help learners make better decisions during learning. Bayesian Knowledge Tracing (BKT) extensions [2] and deep learning based approaches have demonstrated improved mastery prediction accuracy compared to the basic BKT model; however, neither set of models provides actionable guidance on learning activities beyond mastery prediction
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KDD 20202020Personalized real-time recommendation has had a profound impact on retail, media, entertainment and other industries. However, developing recommender systems for every use case is costly, time consuming, and resource-intensive. To fill this gap, we present a black-box recommender system that can adapt to a diverse set of scenarios without the need for manual tuning. We build on techniques that go beyond
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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.
