NVIDIA Developer Blog

Bringing Tensor Cores to Standard Fortran

Fri, 07 Aug 2020 19:35:39 GMT

Tuned math libraries are an easy and dependable way to extract the ultimate performance from your HPC system. However, for long-lived applications or those that need to run on a variety of platforms, adapting library calls for each vendor or library version can be a maintenance nightmare. A compiler that can automatically generate calls to […]html

Accelerating AI and ML Workflows with Amazon SageMaker and NVIDIA NGC

Fri, 07 Aug 2020 19:33:06 GMT

AI is going mainstream and is quickly becoming pervasive in every industry—from autonomous vehicles to drug discovery. However, developing and deploying AI applications is a challenging endeavor. The process requires building a scalable infrastructure by combining hardware, software, and intricate workflows, which can be time-consuming as well as error-prone. To accelerate the end-to-end AI workflow, […]html

Creating Robust Neural Speech Synthesis with ForwardTacotron

Fri, 07 Aug 2020 02:25:48 GMT

The artificial production of human speech, also known as speech synthesis, has always been a fascinating field for researchers, including our AI team at Axel Springer SE. For a long time, people have worked on creating text-to-speech (TTS) systems that reach human level. Following the field’s transition to deep learning with the introduction of Google […]html

Building a Simple AI Assistant with DeepPavlov and NVIDIA NeMo

Tue, 04 Aug 2020 21:09:58 GMT

In the past few years, voice-based interaction has become a feature of many industrial products. Voice platforms like Amazon Alexa, Google Home, Xiaomi Xiaz, Yandex Alice, and other in-home voice assistants provide easy-to-install, smart home technologies to even the least technologically savvy consumers. The fast adoption and rising performance of voice platforms drive interest in […]html

Improving INT8 Accuracy Using Quantization Aware Training and the NVIDIA Transfer Learning Toolkit

Mon, 03 Aug 2020 23:39:52 GMT

Deep neural network (DNN) models are routinely used in applications requiring analysis of video stream content. These may include object detection, classification, and segmentation. Typically, these models are trained on servers with high-end GPUs, either in stand-alone servers, such as NVIDIA DGX1, or on servers available in data centers or private or public clouds. Such […]html

Building Intelligent Video Analytics Apps Using NVIDIA DeepStream 5.0 (Updated for GA)

Mon, 03 Aug 2020 23:38:30 GMT

Whether it’s a warehouse looking to balance product distribution and optimize traffic, a factory assembly line inspection, or hospital management, making sure that employees and caregivers use personal protection equipment (PPE) while attending to patients, advanced intelligent video analytics (IVA) turn out to be useful. At the foundational layer, there are billions of cameras and […]html

Training Instance Segmentation Models Using Mask R-CNN on the NVIDIA Transfer Learning Toolkit

Mon, 03 Aug 2020 23:37:11 GMT

To convert pixels to actionable insights, computer vision relies on deep learning to provide an understanding of the environment. Object detection is a commonly used technique to identify individual objects in a frame such as to identify people or cars. While object detection is beneficial for certain applications, it falls short when you want to […]html