hardware

arXiv:2610.01959v1 Announce Type: cross Abstract: Path finding and multi-robot motion planning require trajectories that are smooth, goal-directed, and collision-free in environments with complex geom

The neocloud market is moving past its origins as a stopgap for scarce graphics processing units. AI-native startups now choose their infrastructure on latency, burst capacity and openness, not just c

arXiv:2609.38438v1 Announce Type: cross Abstract: Machine learning surrogate models offer a promising path toward accelerating plasma turbulence simulations. We present PreVAE-Turb, a surrogate modeli

arXiv:2609.39111v1 Announce Type: new Abstract: Human intelligence relies heavily on learned intuition: recognising patterns and judging situations without explicitly unfolding every intermediate step

Learn how to use Amazon S3 Vectors as the persistent memory layer within the NVIDIA NeMo Agent Toolkit (NAT), deployed on Amazon Elastic Kubernetes Service (Amazon EKS). This post shows how NAT's memo

NVIDIA DOCA AI agent skills supply verified API signatures, hardware capability checks, and build constraints that let agents fully understand the DOCA library (Flow, GPUNetIO, PCC, RDMA) for BlueFiel

arXiv:2609.38570v1 Announce Type: new Abstract: Class 8 trucks differ from passenger cars in geometry, dynamics, and maneuvering requirements. As a result, vision-language-action (VLA) models trained

arXiv:2609.38617v1 Announce Type: new Abstract: Legged robots can learn expressive whole-body skills from the motions of humans and animals. Due to the morphology gap between the source and the robot,

arXiv:2605.21603v1 Announce Type: cross Abstract: Intra-device parallelism addresses resource under-utilization in ML inference and training by overlapping the execution of operators with different re

arXiv:2511.10333v2 Announce Type: replace-cross Abstract: Training large language models (LLMs) at scale incurs substantial communication overhead, while static gradient compression cannot adapt to gr

arXiv:2609.40093v1 Announce Type: cross Abstract: Expert parallelism (EP) enables inference of large Mixture-of-Experts (MoE) models by placing their experts across multiple GPUs, but requires substan

Mackenzie Hawkins / Bloomberg: Experts say mounting cases of Nvidia chips reaching Chinese AI companies despite US export controls are increasingly pointing to gaps in Nvidia's due diligence — Nvidia'

Spooky season is streaming in. Alongside falling leaves, pumpkin spice and everything nice, 25 new games are joining GeForce NOW throughout October, including six ready to play this week. From a new C

arXiv:2609.38198v1 Announce Type: new Abstract: Diffusion maps, and kernel methods more generally, provide an interpretable nonlinear spectral representation basis for geometric learning. In the geome

Generative AI has made remarkable progress in creating increasingly realistic representations of the world. Image models can synthesize photorealistic scenes, video models can generate complex dynamic

arXiv:2609.38312v1 Announce Type: cross Abstract: The Platonic Representation Hypothesis predicts that sufficiently scaled foundation models converge on a shared representation of the world. As each n

arXiv:2609.40297v1 Announce Type: new Abstract: Autonomous exploration demands that robots continuously evaluate candidate viewpoints based on their expected information gain and execution cost. Sampl

GPT-6 Astra Ultrafast, running on NVIDIA Blackwell GPUs, is available now in the OpenAI API and to eligible ChatGPT Work and Codex users. Accelerated by inference optimizations through OpenAI’s models

arXiv:2507.12133v2 Announce Type: replace Abstract: Device recognition is vital for security in wireless communication systems, particularly for applications like access control. Radio Frequency Finge

arXiv:2609.38900v1 Announce Type: new Abstract: Streaming video understanding requires models to process unbounded visual streams while preserving rich visual semantics across vast temporal horizons,

Storage architecture is being rewritten for artificial intelligence factories. Traditional enterprise storage was designed around workloads that scaled in relatively predictable ways. AI changes that

Artificial intelligence factory economics increasingly depend on more than access to high-performance graphics processing units. As agentic systems draw on multiple models, databases and tools, the en

arXiv:2609.38511v1 Announce Type: new Abstract: Autonomous underwater robots require robust perception, estimation and control to operate in confined environments. This paper presents an open-source B

arXiv:2609.38978v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have become a dominant architecture for video generation, but their efficiency is limited by the quadratic complexity of f

AI factories are built by the megawatt, even by the gigawatt. Each megawatt factory costs roughly $60 million, and AI factory operators will only commit capital on that scale with a clear view of the

arXiv:2609.39082v1 Announce Type: new Abstract: As new evidence arrives, a sequence model must update what it remembers and how memory influences predictions. While Transformers incur computation and

The Information: SoftBank made the final 10B investment in its 30B pledge to OpenAI's last funding round; source: Nvidia also made its final 10B investment in the round — Nvidia and SoftBank have each

arXiv:2609.38830v1 Announce Type: new Abstract: Sparse attention is widely used to accelerate long-context inference in modern large language models (LLMs), but its input-dependent execution behavior

arXiv:2609.38984v1 Announce Type: cross Abstract: World-action models (WAMs) leverage pretrained video models to improve generalization in robot control by jointly predicting future visual states and

arXiv:2609.39704v1 Announce Type: cross Abstract: This paper demonstrate that whether masking-based token pruning helps or hurts worst-group robustness can be predicted before deployment, without labe

arXiv:2609.36800v1 Announce Type: new Abstract: Compiler backends are expensive to build and maintain as programming models, workloads, and accelerators evolve. We investigate whether large language m

arXiv:2609.36222v1 Announce Type: new Abstract: Large language models are increasingly expensive to serve. In large-scale serving systems, autoregressive decoding is often bottlenecked by transferring

arXiv:2609.36735v1 Announce Type: new Abstract: In branch-and-bound (B&B) for mixed-integer linear programming (MILP), branching variable selection critically impacts efficiency. Existing neural branc

Amazon Bedrock AgentCore Runtime Instances gives multi-agent workflows AWS managed EC2 infrastructure with GPUs, persistent volumes, and multi-day sessions. In this post, we deploy a three-agent music

Cognition is the first customer running @NVIDIA Vera Rubin, powered by @CoreWeave! Hopper in 2022. Blackwell in 2024. Now Vera Rubin: On SWE-2 inference, the new chips deliver about 4.8x more token th

Token economics are becoming a defining measure of artificial intelligence infrastructure efficiency. As AI workloads move beyond training, the economics of producing useful intelligence are starting

Generative recommender systems model recommendation as high‑cardinality event streams, turning user actions, context, and candidate items into tokens for sequence modeling over user behavior. NVIDIA’s

arXiv:2609.37829v1 Announce Type: new Abstract: Video diffusion transformers (DiTs) increasingly adopt mixture-of-experts (MoE) architectures to reduce active computation, but their full expert storag

arXiv:2609.37013v1 Announce Type: cross Abstract: Rapid assessment of building damage after natural disasters is essential to support emergency response. Earth Observation satellites can acquire relev

NVIDIA has released its cuObject client and server libraries, providing RDMA‑based APIs that allow GPUs to access object storage directly without routing data through the host CPU. The xio‑sig consort

arXiv:2609.36757v1 Announce Type: new Abstract: Diffusion-based video restoration recovers realistic details, but its practical deployment is limited by two efficiency bottlenecks: costly VAE encoding

arXiv:2605.06206v2 Announce Type: replace Abstract: Mixture of experts has emerged as the primary mechanism for making Large Language Models (LLMs) computationally efficient. However, in distributed s

Building on nearly a decade of co-engineering, CoreWeave has built NVIDIA compute, networking and software into a cloud purpose-built for AI that’s still returning on investment across multiple genera

arXiv:2609.36074v1 Announce Type: new Abstract: Memory-efficient scaling on clustering problems without sacrificing statistical accuracy is of central interest for large-scale data analysis and machin

Phoebe Liu / The Information: GPU cloud provider GMI Cloud raised 668M, including 223M in equity led by ARCHIV with participation from Nvidia and 445M in credit led by Taiwanese bank CTBC — GMI Cloud,

arXiv:2609.36134v1 Announce Type: new Abstract: Functional Kolmogorov-Arnold Networks (FunKAN) achieve state-of-the-art accuracy on MRI Gibbs artifact removal and anatomical segmentation, but their 11