Adrian Silva

Explore how #OpenUSD is enhancing autonomous vehicle workflows in this #SIGGRAPH2024 session. https://dy.si/HqbMG

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Learn how you can easily parallelize and optimize your C++ code with standard parallel algorithms and the NVIDIA HPC SDK in our latest blog 🔍

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Keeping your data close to the GPUs is essential, so we offer VAST Data as part of our #GPUasaService AI Platform. Let us help you #StepontheGaaS and move your #AI strategy forward. #Fast #Secure #Private Dominic Ken Michael Bill Traci

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✨ Get over 3x perf improvement for #LLM throughput - TensorRT-LLM Multiblock Attention on NVIDIA HGX H200 boosts long-sequence performance without impacting time-to-first-token. Read how ➡️

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Learn how to simplify camera calibration with real and synthetic data to enhance the accuracy of your AI-powered multi-camera tracking system.

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With NVIDIA NIM and NIM Agent Blueprints, medical researchers across the public sector can jump-start their adoption of state-of-the-art, optimized AI models to accelerate their work. 🔗 https://nvda.ws/3NnkMYy Learn how #NVIDIAInception startups Abridge & ConcertAI leverage NVIDIA AI solutions to improve efficiency, reduce administrative burdens, and advance medical research and patient care. 🩺 Abridge ConcertAI

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Watch @NVIDIAOmniverse's #OpenUSD livestream learn how to build OpenUSD-based #DigitalTwins at scale using Azure IoT and NVIDIA Omniverse for real-world data integration with interactive 3D environments.

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Learn how to reduce CPU launch overhead and accelerate #AI workloads using new #CUDA Graphs enhancements. Read about all the new CUDA Graph improvements and benchmark numbers now. #HPC

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A data-driven approach to driving wound healing outcomes Marcella Gomez, University of California, Santa Cruz https://lnkd.in/gAkWZYJT Meet: https://lnkd.in/g4AAWkcK YouTube Stream: https://lnkd.in/gwtqaTmf Talk details: https://lnkd.in/gWn3B3cU Subscribe for talk announcements: https://lnkd.in/g5ciuNuX Abstract: Precision medicine requires an ability to predict the response of an individual to a prescribed treatment regimen a priori. Thus, advancement in the field is challenged by a lack of predictive models and, arguably, a lack of time-series information for a highly dynamic system. Here, we discuss work in wound healing, for accelerating wound closure. We argue that timing of treatments is as critical to consider as the choice of drug or therapy. Due to system size and complexity, data-driven methods need to be explored to develop multi-dimensional quantifiable indicators tracking systemic changes. In this work I discuss how bioelectronic devices enhanced with deep learning can help facilitate real-time sensing and actuation for automated decisions in treatment for wound healing and preliminary work in transcriptomic based classification of wound states. Bio: Marcella M. Gomez is an associate professor at UC Santa Cruz in the department of Applied Mathematics and Associate Dean for Diversity, Equity, and Inclusion for Baskin Engineering. She received her PhD from Caltech in 2015 and a B.S. from UC Berkeley in 2009; both degrees in Mechanical Engineering. Her research interests are in the broad field of bio-control leveraging methods in machine learning and control theory. Applications range from controlling single-cell response to driving complex systems such as wound healing. #modeling #simulation #medicine #healing #trauma #predictivemodeling #datascience #data #woundhealing #biology #bioengineering #systemanalysis #sensing #omics

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Working on deploying ONNX models for performance-critical applications? Try our NVIDIA Nsight Deep Learning Designer ⚡ A user-friendly GUI and tight integration with NVIDIA TensorRT that offers: ✅ Intuitive visualization of ONNX model graphs ✅ Quick tweaking of model architecture and parameters ✅ Detailed performance profiling with either ORT or TensorRT ✅ Easy building of TensorRT engines Learn more and download ➡️

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