Search: “hardware”

Does Execution Require Target KV Fidelity? A Mixed-Fidelity KV Runtime for LLM Serving

arXiv:2609.33536v1 Announce Type: new Abstract: Large language model (LLM) serving is increasingly constrained by the GPU memory consumed by key-value (KV) caches. Existing compression, eviction, and

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dream job token maxxing till open source wins

DGX agent

dream job token maxxing till open source wins getting acquired by @nvidia = hugging face can now hire people we couldn't as a small startup and give them a decade to make open-source AI win! if you're

hardwareclem-delangue--x

29 Sept 2026

Efficient World Action Model Inference with Adaptive Intermediate States

arXiv:2609.34608v1 Announce Type: new Abstract: World Action Models (WAMs) enable future-aware control by jointly modeling actions and environment dynamics. However, iterative diffusion or flow infere

Fill2SR: Repurposing Inpainting Diffusion Transformers for Real-World Super-Resolution

arXiv:2609.33582v1 Announce Type: new Abstract: Recent real-world image super-resolution (SR) methods often adapt text-to-image (T2I) backbones with ControlNet-style branches or spatial conditioning t

FLARE: Flow Matching with Local Axis-Angle Representations for Stochastic Micromagnetic Evolution

arXiv:2609.34070v1 Announce Type: new Abstract: Long-horizon micromagnetic simulation remains expensive because conventional and learned solvers typically propagate Landau--Lifshitz--Gilbert (LLG) dyn

FoldAttention: Declared-Reference Softmax for Fast Decode and Deterministic Backward

arXiv:2609.33410v1 Announce Type: new Abstract: Autoregressive decode repeatedly streams a growing KV cache, making attention a major cost at long context. Existing high-performance kernels use online

getting acquired by @nvidia = hugging face can now hire people we couldn't as a small startup and give them a decade to make open-source AI …

On September 29, 2026, Hugging Face co‑founder Clement Delangue announced that the company had been acquired by NVIDIA. The acquisition will let Hugging Face scale its hiring beyond what a small start

hardwareclem-delangue--x

In-Flight KV Cache with Clean Anchors for Faster Autoregressive Video Diffusion

arXiv:2609.32540v1 Announce Type: new Abstract: Few-step autoregressive video diffusion generates a long video by splitting the video into temporal chunks and generating chunk-by-chunk, each through a

JEPA Learns What the Mask Leaves Unrecoverable

arXiv:2609.32481v1 Announce Type: new Abstract: Joint-embedding predictive architectures are unusually sensitive to how the input is masked: block masks work, scattered masks do not, and the explanati

KV-streams for Efficient Compaction in Agentic Reinforcement Learning

arXiv:2609.35750v1 Announce Type: new Abstract: Scaling the horizon of agentic LLMs is bottlenecked by the need to fit ever longer context traces in GPU memory. Context compaction has been the most po

KVCMAS: Efficient KV cache Correction for Shared Context in Multi-Agent Systems

arXiv:2609.34060v1 Announce Type: new Abstract: Prompt-specialized multi-agent systems enable multiple agents to share a model while performing complementary roles to solve complex tasks. However, age

Learned Preconditioning for a Primal-Dual Interior-Point Method

arXiv:2609.35665v1 Announce Type: cross Abstract: Interior-point methods (IPMs) are among the most widely used algorithms for constrained optimization, yet their Newton-based search directions require

LionMuon: Alternating Spectral and Sign Descent for Efficient Training

arXiv:2609.35297v1 Announce Type: new Abstract: Pretraining a language model takes enormous compute, and the right optimizer can save a good part of it. Muon's spectral step gives a stronger direction

Lower the Cost of Building and Running Visual AI Agents with NVIDIA VSS Blueprint 3.3

NVIDIA released VSS Blueprint 3.3, a framework that stitches together vision‑language models (Cosmos), LLMs (Nemotron) and retrieval‑augmented generation to convert live or recorded video into natural

hardwarenvidia-developer

MarsLab: A Martian Rover Simulator for Planetary Rover Autonomous Navigation

arXiv:2609.34702v1 Announce Type: new Abstract: Future Mars missions will require rover autonomy that can operate across unstructured terrain, changing illumination, atmospheric dust, and limited comm

NOSA: Native and Offloadable Sparse Attention

arXiv:2510.13602v3 Announce Type: replace-cross Abstract: Decoding throughput improvements from larger inference batches are limited by GPU memory, which is largely consumed by the key-value (KV) cach

Nvidia’s scale-in play: Controlling agents is the next infrastructure priority

Nvidia Corp. is extending the data processing unit from infrastructure offload to a broader security role across the artificial intelligence factory. The opportunity is to make agentic AI safer to ope

hardwaresiliconangle

Our Secure Intelligence Institute works with researchers at Stanford, CMU, Duke, Columbia, Ohio State, and UVA. We’re also working with NVID…

Our Secure Intelligence Institute works with researchers at Stanford, CMU, Duke, Columbia, Ohio State, and UVA. We’re also working with NVIDIA and the Open Secure AI Alliance, and sharing tools and fi

hardwareperplexity--x

PrefLUT: Reusable and Refinable Personalized Color Editing from Pairwise Preferences

arXiv:2609.34133v1 Announce Type: new Abstract: Photographic color editing is inherently personal: the same image can appear too warm, too muted, or already satisfactory to different users. Most looku

PulseInfer: I/O-Centric Sparse KV Cache Offloading for Efficient Long-Context LLM Decoding

arXiv:2609.34555v1 Announce Type: new Abstract: Long-context LLM serving is increasingly bottlenecked by decode, where large KV caches limit batch size and underutilize GPUs. Sparse KV cache offloadin

SANTA++: Sampling Attention through Representative Keys

arXiv:2609.35629v1 Announce Type: new Abstract: Attention often concentrates on a small subset of tokens in the context, but which subset matters changes from one query to the next. To exploit this ch

Scope-WM: Scoped Computation for Efficient Visual World Models

arXiv:2609.33218v1 Announce Type: new Abstract: Visual world models enable robotic planning by predicting future observations, but dense latent-state propagation and sample-intensive trajectory optimi

Single-Layer MeMo as a Randomized Hamming-Kernel Classifier

arXiv:2609.34562v1 Announce Type: new Abstract: MeMo (Zanzotto et al., 2025) is a recent language-model architecture that stores associations between token contexts and next tokens in a correlation ma

Sources: Nvidia is in early-stage talks with insurance companies to structure risk-mitigation products to protect lenders against loan defaults by neoclouds (Financial Times)

Financial Times: Sources: Nvidia is in early-stage talks with insurance companies to structure risk-mitigation products to protect lenders against loan defaults by neoclouds — World's largest listed c

SparSP: Exploiting Communication Sparsity for Sequence-Parallel Video DiTs

arXiv:2609.32197v1 Announce Type: cross Abstract: Diffusion Transformers have become the dominant architecture for video generation. Their substantial computational cost motivates scaling inference ac

Spexis: Speculative Lookahead Scheduling for LLM Inference

arXiv:2609.34370v1 Announce Type: new Abstract: Spexis is a multi-GPU LLM inference framework that improves the efficiency of pipeline and tensor parallelism through speculative parallelism. Rather th

STAMP: Predicting Out-of-Distribution Generalization without Target Data

arXiv:2609.32672v1 Announce Type: new Abstract: Predicting whether a trained model will generalize under distribution shift remains difficult, especially when target-domain data are unavailable. We in

TempoKV: Timely Staging of LLM KV Caches for Memory-Semantic Flash

arXiv:2609.35065v1 Announce Type: cross Abstract: Reusable prefix key-value (KV) caches can outgrow GPU memory in large language model (LLM) serving. A memory-semantic flash hierarchy offers SSD-backe

Terrain-Aware Autonomous Planetary Exploration for Exteroceptive-Proprioceptive Mapping with Quadruped Scouts

arXiv:2609.35493v1 Announce Type: new Abstract: Autonomous planetary exploration requires robots to navigate unknown, uneven terrain while assessing risk, traversability, and energetic cost. Quadruped

TopoEP: Topology-Aware Load Balancing for Expert-Parallel MoE Training

arXiv:2609.35481v1 Announce Type: cross Abstract: Dynamic routing creates severe load imbalance in large-scale expert-parallel Mixture-of-Experts (MoE) training, turning GPUs that host hot experts int

Towards Kinematic Actionable Infeasibility Detection in Motion Planning

arXiv:2609.32806v1 Announce Type: new Abstract: Motion planning in robotics requires not only computing collision-free paths but also certifying infeasibility when no such path exists. Complete method

UnStep: Training-Free Acceleration of Causal Video Diffusion with Fewer Steps Than Distillation

arXiv:2609.32518v1 Announce Type: new Abstract: Distilling bidirectional multi-step video diffusion transformers into few-step causal models has become a common approach for streaming video generation

WorldAttention: An Efficient Attention Architecture for Interactive Video World Models

arXiv:2609.34606v1 Announce Type: new Abstract: Leveraging the paradigm of autoregressive diffusion, text-conditioned interactive video world models aim to simulate temporally coherent environments gu

AutoResearch at Production Scale: Failure Modes and a Multi-Agent Framework

arXiv:2609.30541v1 Announce Type: new Abstract: Optimizing embedding systems for production recommendation pipelines demands systematic exploration that consumes disproportionate engineering effort at

Compress What You See, Not What You Say: Anchored Context Distillation for Latent-Observation Software Engineering Agents

arXiv:2609.31430v1 Announce Type: new Abstract: Tool observations dominate the context of software-engineering agents, making long interaction histories costly to maintain. Existing context compressio

hardwarearxiv-cs-ai

EAServe: Encode-Aware Disaggregated Serving for Multimodal Large Language Models

arXiv:2609.31551v1 Announce Type: cross Abstract: Disaggregating the two stages, Prefill and Decode, onto separate GPU pools is now a standard optimization for (text-only) LLM serving. However, multim

every agent will need a sandbox and the harness should live outside it - separate the brains from the hands great to see nvidia open sourcin…

hardwareharrison-chase--x

every agent will need a sandbox and the harness should live outside it - separate the brains from the hands great to see nvidia open sourcing tools here, agree with Andrew this is part of the harness

How NVIDIA DSX MaxLPS Maximizes AI Factory Throughput and Efficiency

NVIDIA’s DSX MaxLPS employs policy‑governed power sharing to dynamically reallocate power across GPU resources, enabling up to 40 % more GPUs within the same approved power budget. In a joint test at

hardwarenvidia-developer

I am concerned about all these disparate hard forks that target specific architectures instead of opening a PR against upstream

Other than the obvious self promotion, is there a practical reason people do this that I am missing? There's dozens of llamacpp forks with silly names that are supposedly 'optimized' for this or that

hardwarer-localllama

I-Parakeet: Integer-Only Conformer ASR on Mobile NPU

arXiv:2609.30846v1 Announce Type: new Abstract: In this paper, we propose I-Parakeet, an integer-only implementation of NVIDIA's Parakeet-CTC (0.6B parameters) that runs on a smartphone NPU without an

hardwarearxiv-cs-cl

Jensen Huang says AI model distillation is 'competition'; Scott Bessent described it as 'theft' in July and threatened sanctions against overseas companies (Kai Nicol-Schwarz/CNBC)

Kai Nicol-Schwarz / CNBC: Jensen Huang says AI model distillation is “competition”; Scott Bessent described it as “theft” in July and threatened sanctions against overseas companies — Watch CNBC's ful

KuaFu: Compressing Long User Behavior into Understanding at Billion Scale

arXiv:2609.31045v1 Announce Type: cross Abstract: Conversational agents, generative recommenders, and personalized advertising all rest on one capability: understanding each user from raw behavior. Pr

hardwarearxiv-cs-cl

MR. POP: Multi-Robot Parallel Optimizing Planner for Almost-Surely Asymptotically Optimal Planning

arXiv:2609.30644v1 Announce Type: new Abstract: Finding globally optimal paths remains a fundamental challenge in multi-robot motion planning. Despite acceleration of almost-surely asymptotically opti

Nvidia increases its share buyback program by 150B, raising the remaining authorized amount to 235B, aiming to complete it through FY 2028; NVDA is up 20% YTD (Amy Thomson/Bloomberg)

Amy Thomson / Bloomberg: Nvidia increases its share buyback program by 150B, raising the remaining authorized amount to 235B, aiming to complete it through FY 2028; NVDA is up 20% YTD — Nvidia Corp.,

Safety

NVIDIA Open Agent Safety Platform: A Reference for Continuous In-Silicon Agent Monitoring

The NVIDIA Open Agent Safety Platform blends the open‑source OpenShell runtime—executing autonomous AI agents in kernel‑isolated sandboxes—with hardware‑based enforcement via NVIDIA Sentry on BlueFiel

safetynvidia-developer

Samsung commits 1B to AI infrastructure company Helix, adding to the 10B already secured when a KKR-led consortium including Nvidia established Helix in June (Wall Street Journal)

Wall Street Journal: Samsung commits 1B to AI infrastructure company Helix, adding to the 10B already secured when a KKR-led consortium including Nvidia established Helix in June — Helix expects to le

SAP and NVIDIA OpenShell: Working Toward Governance and Security for Auditable AI Agents in Enterprise Systems

SAP and NVIDIA’s OpenShell are partnering to develop governance, security, and audit‑ability frameworks for AI agents deployed within enterprise systems. This collaboration focuses on creating standar

hardwaresap-news

Scepsy: Serving Agentic Workflows Using Aggregate LLM Pipelines

arXiv:2604.15186v2 Announce Type: replace-cross Abstract: Agentic workflows carry out complex tasks by orchestrating multiple large language models (LLMs) and tools. Serving them at a target throughpu

hardwarearxiv-cs-ai