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Johns Hopkins University
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OR3's innovative use of action-driven digital twins enables precise retrieval of critical OR events that traditional methods struggle to identify.
Task-specific architectures still crush large vision-language models when it comes to predicting where surgical instruments should interact with tissue.
Protein search agents can now leverage multi-dimensional reward-based RL and multimodal inputs (protein sequence + text) to produce higher quality reports for complex protein analysis tasks.
Unlock realistic OR video synthesis with a diffusion model conditioned on geometric abstractions, enabling controlled generation of rare and safety-critical events.
