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RBS-Attention: Radius-Bounded Sparse Prefill for Long-Context Large Language Models

arXiv:2609.20971v1 Announce Type: new Abstract: Long-context large language model inference is increasingly limited by prefill, where dense self-attention processes the entire prompt before generation

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Simplifying Model Serving Across Multiple GPUs with NVIDIA TensorRT Multi-Device Integration in NVIDIA Dynamo-Triton

DGX agent

NVIDIA TensorRT’s multi‑device inference lets a single TensorRT network span multiple GPUs using NCCL‑backed collectives, preserving all standard optimizations and supported from TensorRT 11.0 onward.

hardwarenvidia-developer

21 Sept 2026

Turn Your Latest Observations Into Timely Weather Decisions With NVIDIA Earth-2

NVIDIA Earth‑2 is an AI‑driven data‑assimilation platform that ingests observations from proprietary or third‑party sources—such as satellites, radar, and in‑situ sensors—to generate more frequent wea

hardwarenvidia-developer

Verify, Don't Trust: Agentic Model Development for Video Discovery Retrieval at Scale

arXiv:2609.21257v1 Announce Type: cross Abstract: Large language model (LLM) agents can propose, implement, and evaluate model changes. Autoresearch loops demonstrate this capability through minutes-s

VoxelTTO: Voxel-Aligned Feed-Forward 3D Gaussian Splatting with Test-Time Optimization

arXiv:2609.21498v1 Announce Type: new Abstract: Recent feed-forward 3D Gaussian Splatting (3DGS) methods typically regress pixel-aligned Gaussian primitives, often causing excessive overlap and artifa

Correction: “highly profitable” for Jensen, not for OpenAI or Anthropic or (afaik) their corporate customers.

Correction: “highly profitable” for Jensen, not for OpenAI or Anthropic or (afaik) their corporate customers. BREAKING: Nvidia CEO Jensen Huang says AI reached a major turning point this year, becomin

Jensen is right that we have existing laws relevant to cybersecurity. It is very unfortunate that the Trump administration appears not to be…

Jensen is right that we have existing laws relevant to cybersecurity. It is very unfortunate that the Trump administration appears not to be enforcing them. In the end, that will actually *increase* p

No one is surprised that Nvidia’s Jensen Huang thinks AI fears are overblown.

The man who may stand to make the most money from the AI boom seems to think he knows better than anyone else, including researchers who have studied and worked on AI for decades. In an interview with

hardwarethe-verge-ai

this is why nobody wants to stop agentic AI — no matter how dangerous it is.

this is why nobody wants to stop agentic AI — no matter how dangerous it is. Silicon Valley is shifting away from chatbot queries toward a future filled with resource-intensive agentic AI—and it's dri

Master class in spin. Is it really a “positive for the AI infra trade” that OpenAI and Anthropic are steadily losing market share top open m…

Master class in spin. Is it really a “positive for the AI infra trade” that OpenAI and Anthropic are steadily losing market share top open models and on a track to have hardly any? What happens to Cor

19 Sept 2026

Accelerating Sharded Data Parallelism at Scale with Federated Learning

arXiv:2609.20359v1 Announce Type: cross Abstract: The symbiotic scaling of artificial intelligence models and high-performance computing systems continually creates algorithmic challenges in their con

AGORA: Adversarial Generation Of Real-time Animatable 3D Gaussian Head Avatars

arXiv:2512.06438v4 Announce Type: replace Abstract: The generation of high-fidelity, animatable 3D human avatars remains a core challenge in computer graphics and vision, with applications in VR, tele

AI data center builder Crusoe valued at 30.9B in 3.9B round

Crusoe Inc. today announced that it has closed a 3.9 billion late-stage funding round at a 30.9 billion valuation. The Series F deal was led by Atreides Management, Mubadala Capital and Valor Equity P

hardwaresiliconangle

Astronex-World 1.0: Real-Time Interactive World Model Foundation

arXiv:2609.20034v1 Announce Type: cross Abstract: We present Astronex-World 1.0, an open controllable video world-model foundation. Given a text prompt (text-to-video) or an initial observation (image

Benchmarking LLM Inference at Scale with AIPerf

NVIDIA AIPerf is a benchmarking framework that supersedes GenAI‑Perf with a multiprocess architecture, eliminating client‑side bottlenecks during high‑concurrency LLM testing. It supports more than 15

hardwarenvidia-developer

DirtyMoCap: Robust Motion Capture from Unconstrained Markers

arXiv:2609.19927v1 Announce Type: new Abstract: Optical motion capture delivers high-fidelity human motion, but its reliance on strict marker layouts and clean trajectories severely limits its real-wo

Fast Cross-Strength Multi-Contrast Brain MRI Translation using Latent Bridge Matching

arXiv:2609.20341v1 Announce Type: new Abstract: Magnetic Resonance Imaging (MRI) acquired at different field strengths exhibits pronounced variation in noise, resolution, homogeneity, and contrast, wh

Introducing Amazon SageMaker HyperPod Inference Gateway

Amazon SageMaker HyperPod Inference Gateway is a Kubernetes-native, GPU-aware routing add-on for Amazon EKS. It uses real-time GPU signals to send each inference request to the best-suited pod, cuttin

hardwareaws-ml-blog

Modality Discrepancy Transformer for Ambivalence and Hesitancy Recognition

arXiv:2609.19148v1 Announce Type: new Abstract: Ambivalence and hesitancy (A/H) are affective states in which individuals express contradictory signals across facial, vocal, and linguistic channels. A

hardwarearxiv-cs-cl

Recovering Aggressively Pruned Vision-Language-Action Models with Offline Hidden-State Distillation

arXiv:2609.19579v1 Announce Type: new Abstract: Vision-language-action (VLA) models let robots follow language instructions, but their language backbones of several billion parameters are the main obs

RoboGPU: Accelerating GPU Collision Detection for Robotics

arXiv:2603.01517v2 Announce Type: replace-cross Abstract: Autonomous robots are anticipated to be deployed soon in domains ranging from transportation to healthcare and home assistance. Enabling auton

S4R: Scaling for Rigid-Body Interpenetration Resolution

arXiv:2609.20524v1 Announce Type: cross Abstract: Rigid-body interpenetration frequently occurs in procedurally assembled and generated scenes and must be removed before downstream applications such a

Task-Oriented Active Learning of Residual Dynamics for Model Predictive Path Integral Control

arXiv:2609.19378v1 Announce Type: new Abstract: Online residual learning can reduce model mismatch in predictive control, but passive data collection may fail to adequately cover states that become im

The Output-Space Hypothesis: Enumerative Equivalence Checking for Tensor Programs

arXiv:2609.19611v1 Announce Type: cross Abstract: Tensor programs, as used in deep learning models, are a prime target for optimization, as small performance improvements can have a large impact acros

Accelerating Stateful Network Applications with Performance Prediction on SoC SmartNICs

arXiv:2410.22229v2 Announce Type: replace-cross Abstract: Offloading stateful network functions to multi-threaded SoC SmartNICs promises significant performance and cost benefits. However, realizing t

hardwarearxiv-cs-cl

ADAPT: Lightweight, Long-Range Machine Learning Force Fields Without Graphs

arXiv:2509.24115v2 Announce Type: replace Abstract: Point defects play a central role in driving the properties of materials. First-principles methods are widely used to compute defect energetics and

CapMap-MS-TTA: 3rd Place Solution for the MUMU Track of the 8th LSVOS Challenge at ECCV 2026

arXiv:2609.18206v1 Announce Type: cross Abstract: The MUMU track of the 8th Large-scale Video Object Segmentation (LSVOS) Challenge requires a single unified multimodal model to jointly solve image ta

FAME: An FPGA-Based Platform for Approximate Multipliers Evaluation with Pattern-Guided DNN Retraining

arXiv:2609.17730v1 Announce Type: cross Abstract: Approximate multipliers can reduce hardware area and energy consumption in Deep Neural Network (DNN) inference; however, they introduce computational

Fathom: Per-Query Read Depth for Sparse Decoding over Offloaded KV Caches

arXiv:2609.17652v1 Announce Type: cross Abstract: When agentic sessions run to a million tokens with many sessions resident at once, the KV cache and the index that ranks it live in host memory, and t

hardwarearxiv-cs-cl

Good implementation of agent shared memory from the NVIDIA team.

Good implementation of agent shared memory from the NVIDIA team. Banger paper from NVIDIA on shared memory for research agents. (bookmark it) If you run several coding agents on the same research prob

hardwaredair-ai--x

Google, Nvidia, and Emerald AI launch the AI Energy Management Alliance to advance data centers that dynamically adjust electricity use based on grid conditions (Amy Harder/Axios)

Amy Harder / Axios: Google, Nvidia, and Emerald AI launch the AI Energy Management Alliance to advance data centers that dynamically adjust electricity use based on grid conditions — A new coalition l

hardwaretechmeme

GroupKV: Hierarchical KV Cache Management for Long-Context Diffusion LLM Inference

arXiv:2609.17573v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) are emerging as a promising generative paradigm that complements autoregressive decoding. In long-context sett

Installing 6 GPUs in a standard case rather than using an open-frame chassis.

CPU : epyc 7262 MB : ROMED8-2T GPU : V100 16GB PCIE x6 I have built a server with six V100 GPUs. I am now testing it and plan to eventually run Qwen3.8-Next-Flash configured with TP2 and PP3. Because

hardwarer-localllama

Lecture notes on Physics Informed Neural Networks, Neural Operators, and their applications

arXiv:2609.17638v1 Announce Type: cross Abstract: This is the set of lecture notes for the PhD course href{https://www.unibz.it/en/faculties/engineering/phd-computer-science/study-course-offering/2025

Nvidia, Google and Emerald AI launch flexible data center consortium

Nvidia Corp., Google LLC and software startup Emerald AI Inc. have formed an industry consortium to promote the construction of flexible data centers. The AI Energy Management Alliance, or AEMA, offic

hardwaresiliconangle

Risk-Aware World Modeling with Flow-Guided Occupancy Evolution for Selective Trajectory Planning in Automated Driving

arXiv:2609.18442v1 Announce Type: new Abstract: Safe motion planning in automated driving requires anticipating evolving traffic risks and deciding when to revise the current planned trajectory. We in

TabICLv2: A better, faster, scalable, and open tabular foundation model

arXiv:2602.11139v2 Announce Type: replace Abstract: Tabular foundation models, such as TabPFNv2 and TabICL, have recently dethroned gradient-boosted trees at the top of predictive benchmarks, demonstr

Technical Report: One-Step Drifting Action Heads for GR00T N1.7

arXiv:2609.18108v1 Announce Type: new Abstract: One-step action generation can substantially reduce the inference cost of vision-language-action (VLA) policies, but its effect on closed-loop task succ

The Inference Engineering Pareto Atlas: Which Optimizations Dominate the Cost, Quality, and Latency Frontier?

arXiv:2609.17863v1 Announce Type: new Abstract: LLM inference optimizations report speedups on different models, GPUs, prompts, and quality metrics, making them hard to compare or combine. We build a

Visual Perception Engine: Fast and Flexible Multi-Head Inference for Robotic Vision Tasks

arXiv:2508.11584v3 Announce Type: replace-cross Abstract: Deploying multiple machine learning models on resource-constrained robotic platforms for different perception tasks often results in redundant

WeaveRL: Weaving Reconstruction into Scene-Aware Fabrics for Perceptive Reinforcement Learning

arXiv:2609.18685v1 Announce Type: new Abstract: Reinforcement learning allows robots to acquire complex skills, but producing policies for geometrically complex manipulation remains difficult. A promi

WFM: Wiki Foundation Model for Complex Agentic Reasoning

arXiv:2609.18182v1 Announce Type: new Abstract: Real-world agents fundamentally require persistent non-parametric knowledge for dynamic reasoning, i.e., long-term memory and retrieval-augmented genera

Accelerated Decoding of Centroid Positional Encoding for Instance Segmentation

arXiv:2609.16874v1 Announce Type: new Abstract: Beyond model inference, the decoding stage, which converts raw network outputs into task-level representations, constitutes a significant portion of the

“AI doomers should be held accountable for their doomsday claims. It’s made up… It’s irresponsible. We ought to just keep track of all that …

“AI doomers should be held accountable for their doomsday claims. It’s made up… It’s irresponsible. We ought to just keep track of all that and remind people when their claims don’t come true”—@Jensen

hardwareyann-lecun--x

Apple might make servers again to cash in on the AI rush

According to The Information, Apple is planning to get back into the server game and might just pair up with Nvidia to make it happen. Apple retired its Xserve line in 2011 and has largely left enterp

hardwarethe-verge-ai

Banger paper from NVIDIA. It's on the topic of choosing which models go into a multi-agent system. The team compared eight selection strateg…

Banger paper from NVIDIA. It's on the topic of choosing which models go into a multi-agent system. The team compared eight selection strategies, based on size, accuracy, answer diversity and error div

hardwaredair-ai--x

Confidential Computing keeps your data from being tracked or used in three ways: - End-to-end encrypted inference - Hardware-enforced isolat…

Confidential Computing keeps your data from being tracked or used in three ways: - End-to-end encrypted inference - Hardware-enforced isolation that extends to the GPU with @nvidia Confidential Comput

hardwarecohere--x

Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers

AI factories are the infrastructure of the intelligence era. Scaling them responsibly will depend as much on innovation across the grid as inside the data center. Today, Emerald AI, Google and NVIDIA

hardwarenvidia-blog