How NVIDIA Uses GRU

The article discusses advancements in AI-based 3D robot perception and mapping, focusing on NVIDIA's research efforts to create a unified 3D perception stack.

This article discusses the application of deep learning techniques in recommender systems, highlighting the advantages of using neural networks over traditional methods.

This article discusses the winning solution by NVIDIA's team in the Booking.

This article is the second part of a series on building deep learning-powered recommender systems, focusing on the application of deep learning techniques to enhance recommendation quality.

The article discusses the NVIDIA A100 Tensor Core GPU and its innovative Multi-Instance GPU (MIG) feature, which allows for secure partitioning of the GPU into up to seven isolated instances.

This article provides a comprehensive guide on deploying real-time Text-to-Speech (TTS) applications using NVIDIA's TensorRT, focusing on the conversion of PyTorch models to TensorRT for optimized ...

The article discusses the advancements in Neural Machine Translation (NMT) inference using TensorRT 4, NVIDIA's inference accelerator.

NVIDIA's TensorRT 4, released at CVPR 2018, enhances deep learning inference for applications like neural machine translation, recommenders, and speech recognition.

NVIDIA's JetPack 3. 1 significantly enhances the low-latency inference performance of the Jetson TX1 and TX2 platforms, doubling the deep learning inference capabilities for real-time applications.

JetPack 2. 3 enhances the performance of Deep Neural Networks (DNNs) on the Jetson TX1 platform, achieving over two-fold increases in run-time efficiency through the integration of TensorRT.

The article discusses the optimizations made in cuDNN 5 for Recurrent Neural Networks (RNNs), focusing on performance improvements and new features that enhance the efficiency of sequence learning ...

This article is the second part of a series on neural machine translation (NMT) using GPUs, focusing on the encoder-decoder architecture.