PyTorch

An image of bottles in a manufacturing processing plant.

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

A black and white GIF out a mouse walking on a wheel.

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

Sep 14, 2022

Upcoming Event: Deep Learning Framework Sessions at GTC 2022

Join us for these featured sessions to learn about optimizing PyTorch models, accelerating graph neural networks, improving GPU performance with automated code generation, and more.

1 MIN READ

Aug 03, 2022

Research Neural Fields Your Way with NVIDIA Kaolin Wisp

Research on neural fields has been an increasingly hot topic in computer graphics and computer vision in recent years. Neural fields can represent 3D data like...

5 MIN READ