To make humanoid robots useful, they need cognition and loco-manipulation that span perception, planning, and whole-body control in dynamic environments. ...

To make humanoid robots useful, they need cognition and loco-manipulation that span perception, planning, and whole-body control in dynamic environments. Building these generalist robots requires a workflow that unifies simulation, control, and learning for robots to acquire complex skills before transferring into the real world. In this post, we present NVIDIA Isaac GR00T N1.6…

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Large language models (LLMs) and multimodal reasoning systems are rapidly expanding beyond the data center. Automotive and robotics developers increasingly want...

Large language models (LLMs) and multimodal reasoning systems are rapidly expanding beyond the data center. Automotive and robotics developers increasingly want to run conversational AI agents, multimodal perception, and high-level planning directly on the vehicle or robot – where latency, reliability, and the ability to operate offline matter most. While many existing LLM and vision language…

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As robots take on increasingly dynamic mobility tasks, developers need physics-accurate simulations that translate across environments and workloads. Training...

As robots take on increasingly dynamic mobility tasks, developers need physics-accurate simulations that translate across environments and workloads. Training robot policies and models to do these tasks requires a large amount of diverse, high-quality data, which is often expensive and time-consuming to collect in the physical world. Therefore, generating synthetic data at scale using cloud…

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Large-scale AI innovation is driving unprecedented demand for accelerated computing infrastructure. Training trillion-parameter foundation models, serving them...

Large-scale AI innovation is driving unprecedented demand for accelerated computing infrastructure. Training trillion-parameter foundation models, serving them with disaggregated architectures, and processing inference workloads at massive throughput all push data center design to the limits. To keep up, service providers need infrastructure that not only scales but also delivers stronger security…

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

AI‑native organizations increasingly face scaling challenges as agentic AI workflows drive context windows to millions of tokens and models scale toward trillions of parameters. These systems currently rely on agentic long‑term memory for context that persists across turns, tools, and sessions so agents can build on prior reasoning instead of starting from scratch on every request.

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NVIDIA is bringing the world’s first optimized Ethernet networking with co-packaged optics to AI factories, enabling scale-out and scale-across on the NVIDIA...

NVIDIA is bringing the world’s first optimized Ethernet networking with co-packaged optics to AI factories, enabling scale-out and scale-across on the NVIDIA Rubin platform with NVIDIA Spectrum-X Ethernet Photonics, the flagship switch for multi-trillion-parameter AI infrastructure. This blog post explores key optimizations and innovations in the protocol and hardware of Spectrum-X Ethernet…

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AI developer activity on PCs is exploding, driven by the rising quality of small language models (SLMs) and diffusion models, such as FLUX.2, GPT-OSS-20B, and...

AI developer activity on PCs is exploding, driven by the rising quality of small language models (SLMs) and diffusion models, such as FLUX.2, GPT-OSS-20B, and Nemotron 3 Nano. At the same time, AI PC frameworks, including ComfyUI, llama.cpp, Ollama, and Unsloth are making functional advances, doubling in popularity over the past year as the number of developers using PC-class models has grown…

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Since its release, NVIDIA has continued to push performance of the Grace Blackwell-powered DGX Spark through continuous software optimization and close...

Since its release, NVIDIA has continued to push performance of the Grace Blackwell-powered DGX Spark through continuous software optimization and close collaboration with software partners and the open-source community. These efforts are delivering meaningful gains across inference, training and creative workflows. At CES 2026, the latest DGX Spark software release, combined with new model…

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AI has entered an industrial phase. What began as systems performing discrete AI model training and human-facing inference has evolved into always-on AI...

AI has entered an industrial phase. What began as systems performing discrete AI model training and human-facing inference has evolved into always-on AI factories that continuously convert power, silicon, and data into intelligence at scale. These factories now underpin applications that generate business plans, analyze markets, conduct deep research, and reason across vast bodies of…

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Generalist robot policies must operate across diverse tasks, embodiments, and environments, requiring scalable, repeatable simulation-based evaluation. Setting...

Generalist robot policies must operate across diverse tasks, embodiments, and environments, requiring scalable, repeatable simulation-based evaluation. Setting up large-scale policy evaluations is tedious and manual. Without a systematic approach, developers need to build high-overhead custom infrastructure, yet task libraries remain limited in complexity and diversity.

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NVIDIA is introducing the NVIDIA Jetson T4000, bringing high-performance AI and real-time reasoning to a wider range of robotics and edge AI applications....

NVIDIA is introducing the NVIDIA Jetson T4000, bringing high-performance AI and real-time reasoning to a wider range of robotics and edge AI applications. Optimized for tighter power and thermal envelopes, T4000 delivers up to 1200 FP4 TFLOPs of AI compute and 64 GB of memory, providing an ideal balance of performance, efficiency, and scalability. With its energy-efficient design and production…

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Building an agent is more than just “call an API”—it requires stitching together retrieval, speech, safety, and reasoning components so they behave like...

Building an agent is more than just “call an API”—it requires stitching together retrieval, speech, safety, and reasoning components so they behave like one cohesive system. Each layer has its own interface, latency constraints, and integration challenges, and you start to feel them as soon as you move beyond a simple prototype. In this tutorial, you’ll learn how to build a voice-powered RAG…

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Autonomous vehicle (AV) research is undergoing a rapid shift. The field is being reshaped by the emergence of reasoning-based vision–language–action (VLA)...

Autonomous vehicle (AV) research is undergoing a rapid shift. The field is being reshaped by the emergence of reasoning-based vision–language–action (VLA) models that bring human-like thinking to AV decision-making. These models can be viewed as implicit world models operating in a semantic space, allowing AVs to solve complex problems step-by-step and to generate reasoning traces that mirror…

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