Models / Libraries / Frameworks

Jul 17, 2025

Feature Engineering at Scale: Optimizing ML Models in Semiconductor Manufacturing with NVIDIA CUDA‑X Data Science

In our previous post, we introduced the setup of predictive modeling in chip manufacturing and operations, highlighting common challenges such as imbalanced...
6 MIN READ
Jul 16, 2025

CUTLASS 3.x: Orthogonal, Reusable, and Composable Abstractions for GEMM Kernel Design

GEMM optimization on GPUs is a modular problem. Performant implementations need to specify hyperparameters such as tile shapes, math and copy instructions, and...
12 MIN READ
Jul 16, 2025

CUTLASS: Principled Abstractions for Handling Multidimensional Data Through Tensors and Spatial Microkernels

In the era of generative AI, utilizing GPUs to their maximum potential is essential to training better models and serving users at scale. Often, these models...
12 MIN READ
Jul 14, 2025

Enabling Fast Inference and Resilient Training with NCCL 2.27

As AI workloads scale, fast and reliable GPU communication becomes vital, not just for training, but increasingly for inference at scale. The NVIDIA Collective...
9 MIN READ
Jul 14, 2025

Enhancing Multilingual Human-Like Speech and Voice Cloning with NVIDIA Riva TTS

While speech AI is used to build digital assistants and voice agents, its impact extends far beyond these applications. Core technologies like text-to-speech...
10 MIN READ
Jul 11, 2025

Forecasting the Weather Beyond Two Weeks Using NVIDIA Earth-2

Being able to predict extreme weather events is essential as such conditions become more common and destructive. Subseasonal climate forecasting—predicting...
9 MIN READ
Jul 09, 2025

Reinforcement Learning with NVIDIA NeMo-RL: Reproducing a DeepScaleR Recipe Using GRPO

Reinforcement learning (RL) is the backbone of interactive AI. It is fundamental for teaching agents to reason and learn from human preferences, enabling...
5 MIN READ
Jul 07, 2025

Think Smart and Ask an Encyclopedia-Sized Question: Multi-Million Token Real-Time Inference for 32X More Users

Modern AI applications increasingly rely on models that combine huge parameter counts with multi-million-token context windows. Whether it is AI agents...
8 MIN READ
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Jul 01, 2025

Per-Tensor and Per-Block Scaling Strategies for Effective FP8 Training

In this blog post, we’ll break down the main FP8 scaling strategies—per-tensor scaling, delayed and current scaling, and per-block scaling (including the...
10 MIN READ
Jun 26, 2025

Run Google DeepMind’s Gemma 3n on NVIDIA Jetson and RTX

As of today, NVIDIA now supports the general availability of Gemma 3n on NVIDIA RTX and Jetson. Gemma, previewed by Google DeepMind at Google I/O last month,...
4 MIN READ
Jun 25, 2025

Join Us at We Are Developers World Congress 2025

Join us at We Are Developers World Congress from July 9 to 11 to attend our workshops and connect with experts.
1 MIN READ
Jun 18, 2025

How Early Access to NVIDIA GB200 Systems Helped LMArena Build a Model to Evaluate LLMs

LMArena at the University of California, Berkeley is making it easier to see which large language models excel at specific tasks, thanks to help from NVIDIA and...
6 MIN READ
Jun 18, 2025

AI in Manufacturing and Operations at NVIDIA: Accelerating ML Models with NVIDIA CUDA-X Data Science

NVIDIA leverages data science and machine learning to optimize chip manufacturing and operations workflows—from wafer fabrication and circuit probing to...
8 MIN READ
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Jun 13, 2025

Run High-Performance LLM Inference Kernels from NVIDIA Using FlashInfer​​

Best-in-class LLM Inference requires two key elements: speed and developer velocity. Speed refers to maximizing the efficiency of the underlying hardware by...
6 MIN READ
Jun 12, 2025

Accelerated Sequence Alignment for Protein Science with MMseqs2-GPU and NVIDIA NIM

Protein sequence alignment—comparing protein sequences for similarities—is fundamental to modern biology and medicine. It illuminates gene functions by...
9 MIN READ
cuEquivariance expands to accelerate next-gen protein structure models
Jun 11, 2025

Accelerated Molecular Modeling with NVIDIA cuEquivariance and NVIDIA NIM microservices

The emergence of models like AlphaFold2 has skyrocketed the demand for faster inference and training of molecular AI models. The need for speed comes with...
8 MIN READ