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Showing posts older than #2728 · Back to latest

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Post #2726 317
Turn Your Latest Observations Into Timely Weather Decisions With NVIDIA Earth-2

https://developer.nvidia.com/blog/turn-your-latest-observations-into-timely-weather-decisions-with-nvidia-earth-2/
NVIDIA Technical Blog Turn Your Latest Observations Into Timely Weather Decisions With NVIDIA Earth-2 Weather-sensitive industries increasingly have access to observations that offer an earlier, more local view of changing conditions. Energy companies collect measurements across wind and solar assets…
Post #2722 520
TensorRT Edge-LLM Completes the MLPerf Edge Agentic Benchmark 6.4x Faster on Jetson AGX Thor

https://developer.nvidia.com/blog/tensorrt-edge-llm-completes-the-mlperf-edge-agentic-benchmark-6-4x-faster-on-jetson-agx-thor/
NVIDIA Technical Blog TensorRT Edge-LLM Completes the MLPerf Edge Agentic Benchmark 6.4x Faster on Jetson AGX Thor AI agents are moving from cloud data centers to vehicles, robots, and other edge devices. Unlike a chatbot that answers a single prompt, an agent works through a sequence of steps. It selects tools…
Post #2720 381
Translating CUDA Tile Operations from Python to Rust Using Agentic AI

https://developer.nvidia.com/blog/translating-cuda-tile-operations-from-python-to-rust-using-agentic-ai/
NVIDIA Technical Blog Translating CUDA Tile Operations from Python to Rust Using Agentic AI cuTile Rust () is a tile-based system for safe, idiomatic GPU kernel authoring in the Rust programming language. Extending the Rust ownership model to tile-based GPU kernels, it splits mutable outputs…
Post #2716 354
Dense vs. MoE Models: Active Parameters, Throughput, and When to Choose Each

https://developer.nvidia.com/blog/dense-vs-moe-models-active-parameters-throughput-and-when-to-choose-each/
NVIDIA Technical Blog Dense vs. MoE Models: Active Parameters, Throughput, and When to Choose Each How can a 30B-parameter model activate only 3B parameters per token, and still use the capacity of the larger model? Nemotron 3.5 Lightning illustrates the answer: It uses a Mixture-of-Experts (MoE)…
Post #2714 350
How NVIDIA Groq 3 LPX Deterministic Execution Drives Power-Efficient High-Interactivity Inference on NVIDIA Vera Rubin

https://developer.nvidia.com/blog/how-nvidia-groq-3-lpx-deterministic-execution-drives-power-efficient-high-interactivity-inference-on-nvidia-vera-rubin/
NVIDIA Technical Blog How NVIDIA Groq 3 LPX Deterministic Execution Drives Power-Efficient High-Interactivity Inference on NVIDIA Vera Rubin Power is a defining constraint for AI factories. As AI workloads demand a full compute platform to serve them, each component of that platform must maximize output within the factory’s limited power…
Post #2713 317
Scaling Federated Learning Across Docker, Kubernetes, and Slurm with NVIDIA FLARE

https://developer.nvidia.com/blog/scaling-federated-learning-across-docker-kubernetes-and-slurm-with-nvidia-flare/
NVIDIA Technical Blog Scaling Federated Learning Across Docker, Kubernetes, and Slurm with NVIDIA FLARE Federated learning (FL) projects often begin with a straightforward setup: one server, a few clients, and one dataset at each site. As those projects grow, the challenge shifts from running an…
Post #2712 312
From Megawatts to Tokens: How NVIDIA Maximizes AI Factory Production

https://blogs.nvidia.com/blog/from-megawatts-to-tokens-how-nvidia-maximizes-ai-factory-production/
NVIDIA Blog From Megawatts to Tokens: How NVIDIA Maximizes AI Factory Production On a sweltering August evening in Silicon Valley, as the sun dropped and air conditioning loads spiked, Silicon Valley Power sent a signal to an AI factory to adjust its power consumption. Varun Sivaram was watching on Zoom with about forty others — his team…
Post #2711 369
AI Infra Summit: NVIDIA Vera Rubin and DSX Platform Advancements Showcase Energy Efficiencies of Optimizing Tokens Per Watt for AI Factories

https://blogs.nvidia.com/blog/ai-infra-summit-vera-rubin-dsx-energy-efficiencies-tokens-per-watt-ai-factories/
NVIDIA Blog AI Infra Summit: NVIDIA Vera Rubin and DSX Platform Advancements Showcase Energy Efficiencies of Optimizing Tokens Per Watt for… Ian Buck, vice president of hyperscale and high-performance computing at NVIDIA, Tuesday spoke on AI factory efficiency at the AI Infra Summit, the Santa Clara Convention Center event that has morphed into a Coachella of infrastructure tech. Before a packed…
Post #2710 410
Heart of the Matter: How a Major Children’s Hospital Uses Open Source NVIDIA AI for Cardiac Care

https://blogs.nvidia.com/blog/childrens-hospital-open-source-ai-cardiac-care/
NVIDIA Blog Heart of the Matter: How a Major Children’s Hospital Uses Open Source NVIDIA AI for Cardiac Care Children’s Hospital of Philadelphia is using open source AI tools to model children’s hearts in seconds — with the goal of enabling safer, more precise care for kids with congenital heart disease.
Post #2709 461
Accelerating Dropless MoE Training in JAX with NVIDIA Transformer Engine

https://developer.nvidia.com/blog/accelerating-dropless-moe-training-in-jax-with-nvidia-transformer-engine/
NVIDIA Technical Blog Accelerating Dropless MoE Training in JAX with NVIDIA Transformer Engine Mixture of experts (MoE) has become one of the defining architectural trends in large-scale AI model training. DeepSeek, Qwen, and Mixtral are examples of MoE models that match or exceed the…
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