PyTorch
Jan 17, 2024
Release: PyTorch Geometric Container for GNNs on NGC
The NVIDIA PyG container, now generally available, packages PyTorch Geometric with accelerations for GNN models, dataloading, and pre-processing using...
1 MIN READ
Dec 08, 2023
Available Now: NVIDIA AI Accelerated DGL and PyG Containers for GNNs
From credit card transactions, social networks, and recommendation systems to transportation networks and protein-protein interactions in biology, graphs are...
9 MIN READ
Nov 20, 2023
Transforming Industrial Defect Detection with NVIDIA TAO and Vision AI Models
Efficiency is paramount in industrial manufacturing, where even minor gains can have significant financial implications. According to the American Society of...
11 MIN READ
Nov 08, 2023
New Workshop: Rapid Application Development Using Large Language Models
Interested in developing LLM-based applications? Get started with this exploration of the open-source ecosystem.
1 MIN READ
Oct 12, 2023
Workshop: Model Parallelism: Building and Deploying Large Neural Networks
Learn how to train the largest neural networks and deploy them to production.
1 MIN READ
Oct 04, 2023
Analyzing the Security of Machine Learning Research Code
The NVIDIA AI Red Team is focused on scaling secure development practices across the data, science, and AI ecosystems. We participate in open-source security...
12 MIN READ
Aug 09, 2023
Just Released: NVIDIA Modulus 23.08
NVIDIA Modulus is now part of the NVIDIA AI Enterprise suite, supporting PyTorch 2.0, CUDA 12, and new samples.
1 MIN READ
Jul 18, 2023
Research Unveils Breakthrough Deep Learning Tool for Understanding Neural Activity and Movement Control
A primary goal in the field of neuroscience is understanding how the brain controls movement. By improving pose estimation, neurobiologists can more precisely...
8 MIN READ
Jun 06, 2023
Develop Physics-Informed Machine Learning Models with Graph Neural Networks
NVIDIA Modulus is a framework for building, training, and fine-tuning deep learning models for physical systems, otherwise known as physics-informed machine...
6 MIN READ
May 16, 2023
Sparsity in INT8: Training Workflow and Best Practices for NVIDIA TensorRT Acceleration
The training stage of deep learning (DL) models consists of learning numerous dense floating-point weight matrices, which results in a massive amount of...
12 MIN READ
May 05, 2023
Why Automatic Augmentation Matters
Deep learning models require hundreds of gigabytes of data to generalize well on unseen samples. Data augmentation helps by increasing the variability of...
13 MIN READ
Apr 25, 2023
Increasing Inference Acceleration of KoGPT with NVIDIA FasterTransformer
Transformers are one of the most influential AI model architectures today and are shaping the direction of future AI R&D. First invented as a tool for...
6 MIN READ
Apr 04, 2023
Topic Modeling and Image Classification with Dataiku and NVIDIA Data Science
The Dataiku platform for everyday AI simplifies deep learning. Use cases are far-reaching, from image classification to object detection and natural language...
11 MIN READ
Jan 17, 2023
New Course: Introduction to Graph Neural Networks
Learn the basic concepts, implementations, and applications of graph neural networks (GNNs) in this new self-paced course from NVIDIA Deep Learning Institute.
1 MIN READ
Nov 29, 2022
New Workshop: Data Parallelism: How to Train Deep Learning Models on Multiple GPUs
Learn how to decrease model training time by distributing data to multiple GPUs, while retaining the accuracy of training on a single GPU in this new instructor-led workshop.
1 MIN READ
Oct 21, 2022
Upcoming Webinar: A Deep Dive into MONAI
Join us on October 24 for a deep dive into MONAI, the essential framework for AI workflows in healthcare—including use cases, building blocks, and more.
1 MIN READ