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Dive into the world of CUDA with Stephen Jones, exploring parallelism, multicore compute history, and how 3D rendering concepts unlocked major machine learning algorithms.
Discover how to build and optimize teams of AI agents using NVIDIA's AgentIQ open-source library, connecting various LLM frameworks to create complex agentic AI systems for enterprise applications.
Discover how to write multi-GPU libraries using task-based runtime systems that scale transparently without explicit communication, and learn to integrate your code with existing domain libraries.
Explore multi-GPU scaling strategies with NVIDIA's distributed libraries, learning how to efficiently scale beyond a single GPU and simplify the implementation process for accelerated computing.
Master XGBoost training and inference optimization using RAPIDS on NVIDIA GPUs, achieving 25x faster performance through hands-on practice with real taxi fare data in Google Colab.
Master graph analysis acceleration using RAPIDS and NetworkX on NVIDIA GPUs, achieving 72x faster performance with hands-on demonstrations of Betweenness Centrality and PageRank algorithms on real-world datasets.
Step-by-step guide to set up a retrieval-augmented generation (RAG) system using NVIDIA AI Workbench, enabling developers to create AI projects on their local machines without a GPU in about an hour.
Adjust settings in Autodesk Maya to fine-tune character animation, focusing on personality, reactions, and facial movements using NVIDIA ACE technology.
Discover practical implementations of LLMs through hands-on demonstrations of image search applications, coding assistance tools, and vision-language action models for robotics integration.
Learn to build an AI-enabled Network Video Recorder using NVIDIA Metropolis microservices for Jetson. Covers system setup, microservices, diagnostics, and code samples for various operations in edge AI applications.
Comprehensive guide to NVIDIA's Video Storage Toolkit for Jetson, covering installation, usage, code samples, and debugging. Ideal for developers working on edge AI applications with video management needs.
Learn to build an AI-enabled Network Video Recorder using NVIDIA Metropolis microservices for Jetson. Covers system setup, microservices, testing, diagnostics, and code samples for various operations in edge AI applications.
Discover how to scale Python and NumPy programs across multi-GPU systems using NVIDIA cuPyNumeric without complex parallel computing code on DGX Spark desktop clusters.
Explore how NVIDIA's 900+ CUDA-X libraries revolutionize industries from data science to quantum computing, driving breakthrough scientific and engineering innovations.
Discover CUDA 13.0's latest features and future GPU computing developments in this engineering-focused talk by NVIDIA's technical product lead.
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