NVIDIA Technical Blog

Build the next generation of intelligent, autonomous applications. This isn't just a hackathon—it's your chance to unleash the power of agentic AI and show...

A defining strength of the NVIDIA software ecosystem is its commitment to continuous optimization. In August, NVIDIA Jetson AGX Thor launched, with up to a 5x...

The telecommunications industry is innovating rapidly toward 6G for both AI-native Radio Access Networks (AI-RAN) and AI-Core. The distributed User Plane...

NVIDIA cuQuantum is an SDK of libraries for accelerating quantum simulations at the circuit (digital) and device (analog) level. It is now integrated into...

If you're an application developer or a cluster administrator, you’ve likely seen how non-uniform memory access (NUMA) can impact system performance. When an...

Built for data scientists and bioinformaticians, NVIDIA Parabricks is a scalable genomics software suite for secondary analysis. Providing GPU-accelerated...

SemiAnalysis recently launched InferenceMAX v1, a new open source initiative that provides a comprehensive methodology to evaluate inference hardware...

For decades, traditional data centers have been vast halls of servers with power and cooling as secondary considerations. The rise of generative AI has changed...

The exponential growth in large language model complexity has created challenges, such as models too large for single GPUs, workloads that demand high...

As AI models grow larger and more sophisticated, inference, the process by which a model generates responses, is becoming a major challenge. Large language...

Generating text with large language models (LLMs) often involves running into a fundamental bottleneck. GPUs offer massive compute, yet much of that power sits...

Deploying large language models (LLMs) poses a challenge in optimizing inference efficiency. In particular, cold start delays—where models take significant...

The race to understand protein structures has never been more critical. From accelerating drug discovery to preparing for future pandemics, the ability to...

AI models, inference engine backends, and distributed inference frameworks continue to evolve in architecture, complexity, and scale. With the rapid pace of...

Inference has emerged as the new frontier of complexity in AI. Modern models are evolving into agentic systems capable of multi-step reasoning, persistent...

In recent years, AI workloads have grown exponentially—not only in the deployment of large language models (LLMs) but also in the demand to process ever more...

Logs are the lifeblood of modern systems. But as applications scale, logs often grow into endless walls of text—noisy, repetitive, and overwhelming. Hunting...

Unlike traditional LLM-based systems that are limited by their training data, retrieval-augmented generation (RAG) improves text generation by incorporating...

Unlike traditional systems that follow predefined paths, AI agents are autonomous systems that use large language models (LLMs) to make decisions, adapt to...

AI agents now solve multi-step problems, write production-level code, and act as general assistants across multiple domains. But to reach their full potential,...

Have you ever wanted to build your own reasoning models such as the NVIDIA Nemotron, but thought it was too complicated or required massive resources? Think...

This updated post was originally published on March 18, 2025. Organizations are embracing AI agents to enhance productivity and streamline operations. To...

Developers are increasingly turning to AI-enabled tools for coding, including Cursor, OpenAI Codex, Claude Code, and GitHub Copilot. While these automation...

NVIDIA KAI Scheduler is now natively integrated with KubeRay, bringing the same scheduling engine that powers high‐demand and high-scale environments in...

Over the last several years, the NVIDIA AI Red Team (AIRT) has evaluated numerous and diverse AI-enabled systems for potential vulnerabilities and security...

In a recent blog post, we introduced NVIDIA NV-Tesseract, a family of models designed to unify anomaly detection, classification, and forecasting within a...

Generative AI is opening new possibilities for analyzing existing video streams. Video analytics are evolving from counting objects to turning raw video content...

Today, Microsoft is making Windows ML available to developers. Windows ML enables C#, C++ and Python developers to optimally run AI models locally across PC...

In previous posts on FP8 training, we explored the fundamentals of FP8 precision and took a deep dive into the various scaling recipes for practical large-scale...

A recurring challenge in molecular design, whether for pharmaceutical, chemical, or material applications, is creating synthesizable molecules. Synthesizability...

Training robot policies from real-world demonstrations is costly, slow, and prone to overfitting, limiting generalization across tasks and environments. A...

Physics plays a crucial role in robotic simulation, providing the foundation for accurate virtual representations of robot behavior and interactions within...

The increasing demand for robotics is driving the need for physics-accurate simulation at an unprecedented scale. Universal Scene Description (OpenUSD) is key...

Modern robotics requires more than what classical analytic dynamics provides because of simplified contacts, omitted kinematic loops, and non-differentiable...

While today's robots excel in controlled settings, they still struggle with the unpredictability, dexterity, and nuanced interactions required for real-world...

The new release introduces CUDA 13.0 support and new functions for ahead-of-time compilation module.

Autonomous vehicle (AV) technology is rapidly evolving, fueled by ever-larger and more complex AI models deployed at the edge. Modern vehicles now require not...

The world of embedded and edge computing is about to get faster, more efficient, and more versatile with the upcoming CUDA 13.0 release for Jetson Thor SoC...

Predicting where proteins are located inside a cell is critical in biology and drug discovery. This process is known as subcellular localization. The location...

Compression is a common technique to reduce storage costs and accelerate input/output transfer times across databases, data-center communications,...

As workloads scale and demand for faster data processing grows, GPU-accelerated databases and query engines have been shown to deliver significant...

In previous posts on AI in manufacturing and operations, we covered the unique data challenges in the supply chain and how smart feature engineering can...

Community detection algorithms play an important role in understanding data by identifying hidden groups of related entities in networks. Social network...

Over hundreds of Kaggle competitions, we've refined a playbook that consistently lands us near the top of the leaderboard—no matter if we’re working with...

The 25.08 release of RAPIDS continues to push the boundaries toward making accelerated data science more accessible and scalable with the addition of several...

Slow data loads, memory-intensive joins, and long-running operations—these are problems every Python practitioner has faced. They waste valuable time and make...

Scientists from NVIDIA, in collaboration with Lawrence Berkeley National Laboratory (Berkeley Lab), released a machine learning tool called Huge Ensembles...

Computer-aided engineering (CAE) forms the backbone for modern product development across industries, from designing safer aircraft to optimizing renewable...

NVIDIA PhysicsNeMo 25.08 is packed with powerful new workflows and recipes for CAE application developers.

In modern engineering, the pace of innovation is closely linked to the ability to perform accelerated simulations. Computer-aided engineering (CAE) plays a...

Telesurgery is no longer a futuristic idea—it’s quickly becoming essential to how care is delivered. With a global shortage of surgeons projected to reach...

When a CUDA kernel requires more hardware registers than are available, the compiler is forced to move the excess variables into local memory, a process known...

NVIDIA HPC SDK v25.7 delivers a significant leap forward for developers working on high-performance computing (HPC) applications with GPU acceleration. This...

As datasets get bigger, ensuring data security and integrity becomes increasingly important. Cryptographic techniques, such as inclusion proofs, data-integrity...

Building a robust visual inspection pipeline for defect detection and quality control is not easy. Manufacturers and developers often face challenges such as...

Powerful hardware-accelerated video processing in Python just got easier. PyNvVideoCodec is an NVIDIA Python-based library for GPU-accelerated video encoding,...

The constantly increasing compute throughput of NVIDIA GPUs presents a new opportunity for optimizing vision AI workloads: keeping the hardware fed with data....

Robotics is undergoing a revolution, moving beyond the era of specialist machines to generalist robotics. This shift moves away from single-purpose,...

First unveiled at NVIDIA GTC 2025, NVIDIA Cosmos Reason is an open and fully customizable reasoning vision language model (VLM) for physical AI and robotics....

Human action recognition is a capability in AI systems designed for safety-critical applications, such as surveillance, eldercare, and industrial monitoring....

As industrial automation accelerates, factories are increasingly relying on advanced robotics to boost productivity and operational resilience. The successful...

As enterprises generate and consume increasing volumes of diverse data, extracting insights from multimodal documents, like PDFs and presentations, has become a...

DOOM: The Dark Ages pushes real-time graphics to new limits by integrating RTX neural rendering and path tracing, setting a new standard for how modern games...

By leveraging large language and speech models, generative AI is creating intelligent 3D avatars that can engage users in natural conversation, from video games...

Running 3D applications that take advantage of advanced rendering and simulation technologies often requires users to navigate complex installs and have access...

Today at Gamescom 2025, NVIDIA unveiled updates to NVIDIA RTX neural rendering and NVIDIA ACE generative AI technologies that enable developers to deliver...

Transferring 3D data between applications has long been a challenge, especially with proprietary formats such as native computer-aided design (CAD) files. CAD...

The proliferation of generative AI video models, along with the new workflows these models have introduced, has significantly accelerated production efficiency...

As part of continued efforts to ensure NVIDIA Omniverse is a developer-first platform, NVIDIA will be deprecating the Omniverse Launcher on Oct. 1. Doing so...

Today, tweaking your PC to suit your workflows often involves digging through menus and settings across multiple control panels. Project G-Assist is an...

By 2030, the World Health Organization projects a global shortage of over 15 million healthcare workers, including surgeons, radiologists, and nurses. In the...

Researchers have developed an AI-powered tool that can analyze nurses’ shift notes to identify—far earlier than traditional methods—when an admitted...

NVIDIA TensorRT for RTX is now available for download as an SDK that can be integrated into C++ and Python applications for both Windows and Linux. At...

In the rapidly evolving robotics and edge AI landscape, the ability to efficiently process and transfer sensor data is crucial. Many edge applications are...

Model compression techniques have been extensively explored to reduce the computational resource demands of serving large language models (LLMs) or other...

Conservationists have launched a new AI tool that can sift through petabytes of underwater imaging from anywhere in the world to identify signs of abandoned or...

Researchers have unveiled a new AI model that can transform hard-to-see underwater images into clear, highly accurate 3D scenes. It can help ecologists more...

AI is becoming the cornerstone of innovation across industries, driving new levels of creativity and productivity and fundamentally reshaping how we live and...

NVIDIA HGX B200 is revolutionizing accelerated computing by unlocking unprecedented performance and energy efficiency. This post shows how HGX B200 is...

Ultra-low latency and reliable packet delivery are critical requirements for modern applications in sectors such as the financial services industry (FSI), cloud...

Building and deploying applications can be challenging for developers, requiring them to navigate the complex relationship between hardware and software...

AI scaling is incredibly complex, and new techniques in training and inference are continually demanding more out of the data center. While data center...

As large language models (LLMs) grow larger, they get smarter, with open models from leading developers now featuring hundreds of billions of parameters. At the...

It’s easy to underestimate how many moving parts a real-world, production-grade AI system involves. Whether you're building an agent that combines internal...

In AI infrastructure, data fuels the compute engine. With evolving agentic AI systems, where multiple models and services interact, fetch external context, and...

Deploying large language models (LLMs) at scale presents a dual challenge: ensuring fast responsiveness during high demand, while managing the costs of GPUs....

NVIDIA is reshaping the landscape of data-center connectivity by seamlessly integrating optical and electrical components. But it’s not doing it alone....

As the latest member of the NVIDIA Blackwell architecture family, the NVIDIA Blackwell Ultra GPU builds on core innovations to accelerate training and AI...

The exponential growth in AI model complexity has driven parameter counts from millions to trillions, requiring unprecedented computational resources that...

As artificial intelligence redefines the computing landscape, the network has become the critical backbone shaping the data center of the future. Large language...

Continuous integration and continuous delivery/deployment (CI/CD) is a set of modern software development practices used for delivering code changes more...

The NVIDIA Collective Communications Library (NCCL) is essential for fast GPU-to-GPU communication in AI workloads, using various optimizations and tuning to...

At its core, NVIDIA Air is built for automation. Every part of your network can be coded, versioned, and set to trigger automatically. This includes creating...

As AI workloads scale, fast and reliable GPU communication becomes vital, not just for training, but increasingly for inference at scale. The NVIDIA Collective...