Deep Learning Programming Tutorials & Engineering Articles

The article discusses how Painkiller RTX utilizes generative AI to enhance game assets by transforming legacy textures into high-quality Physically Based Rendering (PBR) materials.

The article discusses how to utilize NVIDIA Earth-2 to downscale coarse climate projections into high-resolution, bias-corrected fields, enabling better assessment of local climate extremes.

The article discusses NVIDIA's advancements in AI model inference performance through the Blackwell architecture, emphasizing improvements in token throughput per watt and the enhancements made to ...

The article discusses the use of AI Model Distillation to create efficient financial data workflows, focusing on the optimization of large language models (LLMs) for applications in quantitative fi...

The NVIDIA Blackwell architecture has achieved the fastest training times across all MLPerf Training v5. 1 benchmarks, showcasing significant advancements in AI training performance.

The article discusses how JAX, a popular framework for AI model development, is being increasingly adopted in scientific computing, particularly for solving complex Partial Differential Equations (...

The article discusses the launch of the NVIDIA DRIVE AGX Thor Developer Kit, a powerful platform designed to accelerate the development of autonomous vehicles.

The article discusses the significant updates in CUDA Toolkit 13.

The article discusses the emerging threat of semantic prompt injections in multimodal AI systems, highlighting how adversaries can exploit visual inputs to bypass traditional security measures.

The article discusses how to build workflows for converting CAD models to USD (Universal Scene Description) using NVIDIA Omniverse.

The article discusses the advancements in subseasonal climate forecasting using NVIDIA Earth-2, emphasizing the importance of predicting extreme weather events.

NVIDIA Deep Learning Institute is offering a hands-on workshop at GTC Paris focused on enhancing large language models (LLMs) for multilingual applications.

The article discusses the growing trend of telecom companies across five continents building NVIDIA-powered sovereign AI infrastructure, highlighting the strategic importance of AI factories for na...

The article discusses how to leverage NVIDIA CUDA-X and Coiled to simplify data science workflows in the cloud, particularly for analyzing large datasets like NYC ride-share journeys.

The article discusses how to accelerate Deep Learning (DL) and Large Language Model (LLM) inference using Apache Spark in cloud environments.

This article provides a simplified introduction to CUDA, NVIDIA's parallel computing platform, and programming model.

The article discusses the importance of structuring application prompts to enhance the security of key-value (KV) caching in large language model (LLM) applications.

The article discusses optimizing transformer-based diffusion models for video generation using NVIDIA TensorRT, highlighting significant reductions in latency and total cost of ownership (TCO) achi...

Uber's blog post discusses their migration of machine learning workloads to Kubernetes using Ray, detailing the challenges faced with their previous setup and the improvements achieved with the new...

The article introduces NVIDIA's R²D² initiative, which focuses on enhancing robot mobility and whole-body control through innovative workflows and AI foundation models.

The article discusses the transformative role of OpenUSD in enhancing modular and scalable robotic simulation and development.

NVIDIA's advancements in neural rendering and digital human technologies were showcased at GDC 2025, highlighting the transformative impact of AI on gaming visuals, performance, and gameplay.

The article discusses the features and improvements introduced in NCCL 2. 24, focusing on networking reliability and observability at scale for multi-GPU and multinode communication.

NVIDIA has released a new Generative AI Teaching Kit aimed at enhancing education in generative AI technologies.

The article discusses the release of CUDA Toolkit 12. 8, which introduces support for NVIDIA's Blackwell architecture, enhancing performance in AI, data science, and scientific computing.

The article provides a comprehensive guide on how to use OpenUSD, an open framework for managing 3D assets and workflows.

The article discusses an advanced deep-learning model designed to automate X-ray analysis for spinal health diagnostics, enhancing speed and accuracy in assessing conditions like scoliosis and kyph...

The article discusses how RAPIDS cuML can accelerate time series forecasting by utilizing GPU-accelerated machine learning techniques.

NVIDIA has introduced the GeForce RTX 50 Series GPUs and the NVIDIA RTX Kit, which includes advanced neural rendering technologies aimed at enhancing graphics for games and applications.

Airbnb made significant contributions at the 2024 KDD conference in Barcelona, showcasing research on Deep Learning, Search Ranking, Online Experimentation, and Two-sided Marketplaces.

The NVIDIA Deep Learning Institute has launched the Accelerated Data Science Teaching Kit, aimed at educators to enhance data science education.

The article discusses the integration of NVIDIA GPUs with Windows 365 Cloud PCs, emphasizing their role in enhancing AI-augmented workloads.

Dale Durran from the University of Washington introduces a deep learning model that enhances the accuracy of long-range weather and climate forecasting by integrating atmospheric and oceanic data.

A new deep learning model developed by researchers at the University of Texas Southwestern Medical Center aims to reduce the need for invasive surgeries in diagnosing breast cancer metastasis.

The article discusses the integration of the AWS Energy HPC Orchestrator with NVIDIA Energy Samples to enhance high-performance computing (HPC) in the energy sector.

The article discusses optimizing the computer vision (CV) pipeline in automotive vehicle development using the Programmable Vision Accelerator (PVA) engine from NVIDIA.

The article discusses the development of an AI-enabled virtual wind tunnel designed to enhance engineering education by providing intuitive computational fluid dynamics (CFD) tools.

The article discusses how machine learning, particularly through NVIDIA PhysicsNeMo and Fourier neural operators (FNOs), is transforming computational fluid dynamics (CFD) simulations by enhancing ...

NVIDIA showcased its AI security expertise at the Black Hat USA and DEF CON conferences, focusing on the evolving landscape of AI in cybersecurity.

The article discusses the development of MariNeXt, an AI-powered deep learning framework designed to detect and identify marine pollution using high-resolution Sentinel-2 imagery.

The article discusses NVIDIA's advancements in audio generative AI with the introduction of BigVGAN v2, a universal neural vocoder that synthesizes audio waveforms with state-of-the-art quality and...

The article discusses the development and deployment of real-time neural receivers (NRX) in 5G New Radio (5G NR) systems, highlighting their potential to enhance wireless communication through AI-d...

The article discusses the impressive performance of the NVIDIA Triton Inference Server in the MLPerf Inference v4.

The article discusses the NVIDIA GH200 Grace Hopper Superchip, highlighting its significant advancements in energy efficiency and node consolidation for Apache Spark workloads.

The article discusses the integration of a new technique called Simplicits into the NVIDIA Kaolin Library, enabling the simulation of elastic objects across various input geometries, including mess...

The article discusses the development of product configurators using OpenUSD and NVIDIA Omniverse, emphasizing the integration of generative AI to create interactive, photorealistic experiences.

The article discusses HP 3D Printing's collaboration with NVIDIA to open-source AI surrogates for additive manufacturing using the NVIDIA PhysicsNeMo framework.

The article discusses NVIDIA's NeMo framework and its new support for Hybrid State Space Models (SSMs), which enhance the training and efficiency of large language models (LLMs).

The article discusses the vulnerabilities associated with tokenizers in Large Language Models (LLMs) and how malicious actors can exploit these weaknesses to compromise application integrity.

The article introduces the Parameter Vulnerability Factor (PVF), a new metric designed to assess AI systems' vulnerability to silent data corruptions (SDCs) in model parameters.