NVIDIA Technical Blog

AI agents are a powerful tool for synthesizing data to accelerate research, summarize information, and help teams make decisions faster. But combining internal...

High signal Matched: research, agent, agents

The rise of autonomous, long-running AI agents has introduced a new class of compute demand, namely tasks that maintain large context windows, spawn concurrent...

High signal Matched: multi-node, agents

Each wave of AI has created a new scaling law. Pretraining scaled intelligence through larger datasets, more parameters, and massively parallel GPU systems....

High signal Matched: gpu, pretraining, agentic

Modern LLM serving is hard to tune because each deployment is a stack of interacting choices: model backend, tensor-parallel shape, prefill/decode split, worker...

High signal Matched: serving, prefill, model

As AI models grow in complexity and regulatory scrutiny intensifies under frameworks including  California’s AB-2013 and the EU AI Act, software teams...

High signal Matched: model

AI applications are moving beyond text generation to multimodal systems that can perceive, search, and reason across images, documents, video, and...

High signal Matched: generation

The cold-start problem In production inference deployments, demand fluctuates over time, requiring inference replicas to scale elastically. However,...

High signal Matched: inference

Large language models (LLMs) are revolutionizing the financial trading landscape by enabling sophisticated analysis of vast amounts of unstructured data to...

High signal Matched: inference, blackwell

NVIDIA RTX provides game developers with direct paths to AI-driven characters, frame generation, and ray-traced rendering. This post walks through a meaningful...

High signal Matched: generation

NVIDIA CompileIQ tackles one of the hardest problems in performance engineering: finding the compiler options that unlock the best performance for a specific...

High signal Matched: kernel, performance

Developers can now use NVIDIA CUDA Tile programming within large existing C++  GPU codebases to develop highly optimized GPU kernels using tile-based...

High signal Matched: cuda, performance, gpu

NVIDIA CUDA 13.3 brings new capabilities and performance optimizations to developers across the CUDA ecosystem. The launch of NVIDIA CUDA Tile programming in...

High signal Matched: cuda, performance, gpu, launch

Precision medicine depends on two fundamental capabilities: understanding disease at the genomic level and identifying treatments at the molecular level. ...

High signal Matched: blackwell

Maximizing the value of AI infrastructure demands deep visibility into GPU utilization. Yet many platform teams running AI workloads on Kubernetes operate with...

High signal Matched: gpu

As AI models grow in scale and complexity, realizing the full performance of modern accelerated infrastructure depends as much on how workloads are placed as on...

High signal Matched: performance, gb200

Telcos around the world are building sovereign AI factories based on the NVIDIA Cloud Partner (NCP) reference architecture, giving governments, enterprises, and...

High signal Matched: cloud

Agent harnesses like Claude Code, Codex, and LangChain Deep Agents are excellent orchestrators. They manage sessions, chain tools, execute code, and respond to...

High signal Matched: research, agent, agents

Autonomous AI agents are becoming more capable. Open models, Model Context Protocol (MCP)-connected tools, and portable skills are also making agents easier to...

High signal Matched: model, agent, agents, mcp

Evaluating an AI model and evaluating an AI agent are related—but they answer fundamentally different questions. A model benchmark tests the capability of a...

High signal Matched: benchmark, model, evaluation, evaluating, agent, agentic

Agentic inference has fundamentally changed the runtime dynamics of inference workloads by introducing non-deterministic trajectories—actions, observations,...

High signal Matched: inference, introducing, agentic

The path from a trained AI model to production should be smooth, but rarely is. Many teams invest weeks fine-tuning models, only to discover that exporting to a...

High signal Matched: serving, model, fine-tuning

The compute capability of large GPU fleets presents unprecedented opportunities to innovate and provide value to customers in record time. Yet these...

High signal Matched: gpu, introducing

Bash is one of the most flexible and powerful interfaces exposed to AI agents. In the right system, a model that emits grep, curl, tar, or a shell pipeline is...

High signal Matched: decoding, generation, model, agents

NVIDIA GB200 NVL72 introduces a fundamentally new way to build GPU clusters by extending NVIDIA NVLink coherence across an entire rack. This design enables...

High signal Matched: gpu, gb200

Model quantization is an effective method to reduce VRAM usage and improve inference performance on consumer devices such as NVIDIA GeForce RTX GPUs. By...

High signal Matched: inference, performance, model, training, post-training, quantization

Distributed deep learning depends on fast, reliable GPU-to-GPU communication using the NVIDIA Collective Communication Library (NCCL). When training slows down,...

High signal Matched: distributed, nccl, performance, gpu, training

The automotive cockpit is undergoing a fundamental shift from rule-based interfaces to agentic, multimodal AI systems capable of reasoning, planning, and...

High signal Matched: cloud, agents, agentic

Neural network techniques are increasingly used in computer graphics to boost image quality, improve performance, and streamline content creation. Approaches...

High signal Matched: inference, performance

Today, game developers can begin integrating NVIDIA DLSS 4.5 with Dynamic Multi Frame Generation, Multi Frame Generation 6X, and the second-generation...

High signal Matched: generation

NVIDIA CUDA Tile (cuTile) is a tile-based programming model that enables developers to write GPU kernels in terms of tile-level operations—loads, stores, and...

High signal Matched: kernel, cuda, gpu, model, agents

For decades, computational biology has operated under a reductionist compromise. To fit complex biological systems into the limited memory of a single GPU,...

High signal Matched: gpu

Agentic systems often reason across screens, documents, audio, video, and text within a single perception‑to‑action loop. However, they still rely on...

High signal Matched: model, open model, agent, agentic

DeepSeek just launched its fourth generation of flagship models with DeepSeek-V4-Pro and DeepSeek-V4-Flash, both targeted at enabling highly efficient...

High signal Matched: generation, gpu, blackwell

Federated learning (FL) is no longer a research curiosity—it’s a practical response to a hard constraint: the most valuable data is often the least movable....

High signal Matched: research

AI integration is redefining mainstream enterprise applications, from productivity software like Microsoft Office to more complex design and engineering tools....

High signal Matched: blackwell

As LLMs transition from simple text generation to complex reasoning, reinforcement learning (RL) plays a central role. Algorithms like Group Relative Policy...

High signal Matched: generation, throughput, fp8, training

AI tools are significantly accelerating software development and changing how developers work with code. These tools serve as real-time copilots, automating...

High signal Matched: serve, agents, agentic

Coding agents are starting to write production code at scale. Stripe’s agents generate 1,300+ PRs per week. Ramp attributes 30% of merged PRs to agents....

High signal Matched: inference, agents, agentic

When you’re writing CUDA applications, one of the most important things you need to focus on to write great code is data transfer performance. This applies to...

High signal Matched: cuda, performance, gpu

NVIDIA Ising is the world's first family of open AI models for building quantum processors, launching with two model domains: Ising Calibration and Ising...

High signal Matched: model

The release of MiniMax M2.7 adds enhancements to the popular MiniMax M2.5 model, built for agentic harnesses,...

High signal Matched: release, model, agentic

Slurm is an open source cluster management and job scheduling system for Linux. It manages job scheduling for over 65% of TOP500 systems. Most organizations...

High signal Matched: gpu, open source

Training LLMs requires periodic checkpoints. These full snapshots of model weights, optimizer states, and gradients are saved to storage so training can resume...

High signal Matched: model, weights, checkpoint, training

The NVIDIA GB200 NVL72 and NVIDIA GB300 NVL72 systems, featuring NVIDIA Blackwell architecture, are rack-scale supercomputers. They’re designed with 18...

High signal Matched: gb200, blackwell

In vision AI systems, model throughput continues to improve. The surrounding pipeline stages must keep pace, including decode, preprocessing, and GPU...

High signal Matched: throughput, gpu, model

The Gemmaverse expands with the launch of the latest Gemma 4 multimodal and multilingual models, designed to scale across the full spectrum of deployments, from...

High signal Matched: launch

In algorithmic trading, reducing response times to market events is crucial. To keep pace with high-speed electronic markets, latency-sensitive firms often use...

High signal Matched: inference, latency

Note: CUDA Tile Programming in BASIC is an April Fools’ joke, but it's also real and actually works, demonstrating the flexibility of CUDA. CUDA 13.1...

High signal Matched: cuda

Co-designed hardware, software, and models are key to delivering the highest AI factory throughput and lowest token cost. Measuring this goes far beyond peak...

High signal Matched: throughput, cost

In today’s AI factory environment, performance is not theoretical. It is economic, competitive, and existential. A 1% drop in usable GPU time can mean...

High signal Matched: performance, gpu

Spatial computing is moving from visualization to active collaboration, adding increasingly more GPU demands on XR hardware to render photorealistic,...

High signal Matched: gpu

In production Kubernetes environments, the difference between model requirements and GPU size creates inefficiencies. Lightweight automatic speech recognition...

High signal Matched: throughput, gpu, model

Developing new protein-based therapies and catalysts involves the challenging task of designing protein binders, or proteins that bind to a target protein or...

High signal Matched: model

In the AI era, power is the ultimate constraint, and every AI factory operates within a hard limit. This makes performance per watt—the rate at which power is...

High signal Matched: performance

Industrial and medical systems are rapidly increasing the use of high-performance AI to improve worker productivity, human-machine interaction, and downtime...

High signal Matched: performance

AI is moving from experimentation to production. However, most data enterprises need exists outside the public cloud. This includes sensitive information like...

High signal Matched: cloud

As large language model (LLM) inference workloads grow in complexity, a single monolithic serving process starts to hit its limits. Prefill and decode stages...

High signal Matched: inference, serving, prefill, model

Reasoning models are growing rapidly in size and are increasingly being integrated into agentic AI workflows that interact with other models and external tools....

High signal Matched: inference, multi-node, agentic

AI‑native organizations increasingly face scaling challenges as agentic AI workflows drive context windows to millions of tokens and models scale toward...

High signal Matched: introducing, agentic

AI is evolving, and reasoning models are increasing token demand, placing new requirements on every layer of AI infrastructure. More than ever, compute must...

High signal Matched: performance

NVIDIA Groq 3 LPX is a new rack-scale inference accelerator for the NVIDIA Vera Rubin platform, designed for the low-latency and large-context demands of...

High signal Matched: inference, latency, accelerator

The next generation of AI-driven robots like humanoids and autonomous vehicles depends on high-fidelity, physics-aware training data. Without diverse and...

High signal Matched: generation, training

AI agents are changing how you interact with your PC. Creators, developers, and AI enthusiasts are already using these agents extensively to assist with...

Watchlist Matched: agents

As AI agents move from the digital world to the physical environment, they can readily use NVIDIA Jetson to accelerate real-world deployment with optimized...

Watchlist Matched: agents, agentic

Developing autonomous vehicle (AV) policies requires bridging an important gap between training and deployment. Vision-language-action (VLA) models that can...

Watchlist Matched: training

Physical AI systems must understand the real world before they can act within it. Robots, autonomous vehicles, and smart spaces need to understand what's...

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The AI era is driving a new class of infrastructure: AI factories that transform data into intelligence for autonomous AI agents operating at unprecedented...

Watchlist Matched: agents, agentic

AI is now essential infrastructure, powered by AI factories that generate intelligence in the form of tokens. As demand grows, these factories must scale...

Watchlist Matched: none

High‑quality 3D medical imaging data is the foundation of modern radiology AI, but access to it is often constrained by data scarcity, privacy restrictions,...

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In quantitative finance, researchers build algorithms to trade assets, derivatives, and other financial instruments. A key part of that work is finding signals:...

Watchlist Matched: agent

Autonomous AI agents are taking on all types of work for businesses: routing logistics fleets, triaging support tickets, generating code, and orchestrating...

Watchlist Matched: agent, agents, agentic

In today’s data-driven world, organizations increasingly rely on video to capture critical information, yet extracting meaningful, real-time insights from...

Watchlist Matched: agents

A massive-scale X-ray free-electron laser (XFEL) enables tracking structural and electron dynamics in novel systems, including fusion materials, semiconductors,...

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An agentic exchange must preserve a structured interaction: assistant turns interleave reasoning with one or more tool calls, and subsequent user turns return...

Watchlist Matched: agentic

Generative AI’s explosive first chapter was defined by humans sending requests and models responding. The agentic chapter is different.  Agents don't...

Watchlist Matched: agents, agentic

Modern supply chains operate under the constant pressures of fluctuating demand, volatile costs, constrained capacity, and interdependent decision-making....

Watchlist Matched: agent

Creative and visualization teams today produce more assets, in more formats, with leaner teams. Generative AI can accelerate that work – compressing tasks...

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The next wave of enterprise productivity is being built on AI factories. As organizations deploy agentic AI systems capable of reasoning, automation, and...

Watchlist Matched: agentic

The subsurface industry is at a critical point in its digital evolution. For decades, unlocking reservoir potential has relied on experts performing essential...

Watchlist Matched: agentic

In March 2026, three LLM agents generated over 600,000 lines of code, ran 850 experiments, and helped secure a first-place finish in a Kaggle playground...

Watchlist Matched: agents

In a previous post, we introduced the Universal Sparse Tensor (UST), enabling developers to decouple a tensor’s sparsity from its memory layout for greater...

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Higher-order optimization algorithms such as Shampoo have been effectively applied in neural network training for at least a decade. These methods have achieved...

Watchlist Matched: training

The boom in open source generative AI models is pushing beyond data centers into machines operating in the physical world. Developers are eager to deploy these...

Watchlist Matched: open source

Agents are evolving from question-and-answer systems into long-running autonomous assistants that read files, call APIs, and drive multi-step workflows....

Watchlist Matched: agent, agents

The development of socially acceptable nuclear reactors requires that they are safe, clean, efficient, economical, and sustainable. Meeting these requirements...

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Developing real-time vision AI applications presents a significant challenge for developers, often demanding intricate data pipelines, countless lines of code,...

Watchlist Matched: agents

For decades, computational chemistry has faced a tug-of-war between accuracy and speed. Ab initio methods like density functional theory (DFT) provide high...

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Proteins rarely function in isolation as individual monomers. Most biological processes are governed by proteins interacting with other proteins, forming...

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Physical AI—AI systems that perceive, reason, and act in physically grounded simulated environments—is changing how teams design and validate robots and...

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Delivering high-fidelity VR and AR experiences to enterprise users has typically required native application development, custom device management, and complex...

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In the current state of automotive radar, machine learning engineers can't work with camera-equivalent raw RGB images. Instead, they work with the output of...

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Agentic AI is an ecosystem where specialized models work together to handle planning, reasoning, retrieval, and safety guardrailing. As these systems scale,...

Watchlist Matched: rag, retrieval, agents, agentic

While consumer AI offers powerful capabilities, workplace tools often suffer from disjointed data and limited context. Built with LangChain, the NVIDIA AI-Q...

Watchlist Matched: agents

AI-native services are exposing a new bottleneck in AI infrastructure: As millions of users, agents, and devices demand access to intelligence, the challenge is...

Watchlist Matched: agents

Healthcare faces a structural demand–capacity crisis: a projected global shortfall of ~10 million clinicians by 2030, billions of diagnostic exams annually...

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Autonomous AI agents are driving the next wave of AI innovation. These agents must often manage long-running tasks that use multiple communication channels and...

Watchlist Matched: agents

Building AI factories is complex and requires efficient integration across compute, networking, security, and storage systems. To achieve rapid Time to AI and...

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AI has evolved from assistants following your directions to agents that act independently. Called claws, these agents can take a goal, figure out how to achieve...

Watchlist Matched: agents

Artificial intelligence is token-driven. Every prompt, reasoning step, and agent interaction generates tokens. Over the past year, token consumption has grown...

Watchlist Matched: agent

Physics forms the foundation of robotic simulation, enabling realistic modeling of motion and interaction. For tasks like locomotion and manipulation,...

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