Search: “hardware”

The first thing we learned building autoscaling for dedicated inference is that CPU-style metrics don't tell the whole picture. A GPU can re…

The first thing we learned building autoscaling for dedicated inference is that CPU-style metrics don't tell the whole picture. A GPU can read 60% busy while the engine's queue is already backing up,

hardwaretogether-ai--x

31 Jul 2026

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Hardware

Together AI gives developers a high-throughput production path for running Inkling-Small on NVIDIA Accelerated Infrastructure across multimo…

DGX agent

Together AI gives developers a high-throughput production path for running Inkling-Small on NVIDIA Accelerated Infrastructure across multimodal, coding, and agentic workloads. Start building: https://

hardwaretogether-ai--x

31 Jul 2026

Understanding Is Done Early: A Depth Division of Labor in Large Language Models and Its Use for Unbounded-Context Memory

arXiv:2607.28263v1 Announce Type: new Abstract: Transformer depth is not used uniformly: lower and middle layers build semantic representations, while upper layers increasingly specialize them for pre

hardwarearxiv-cs-cl

31 Jul 2026

Model Releases

What’s new in AI infrastructure and orchestration this month

model-releasesgoogle-cloud-ai

At Google, AI is a soup-to-nuts endeavor. Obviously, we make leading AI models like Gemini and Nano Banana. We incorporate AI into the tools you use every day (think Gmail, BigQuery, AlloyDB, Google C

31 Jul 2026

BATS: Resource-Efficient Volumetric Segmentation with Boundary-Aware Mixed-Resolution Tokens

arXiv:2607.26829v1 Announce Type: new Abstract: Many high-performing volumetric segmentation models maintain dense multi-scale feature maps, leading to high activation memory and inference cost. We pr

Best in Class: Stream PC Games and Study on the Same Laptop With GeForce NOW

Back to school means balancing assignments, deadlines and downtime. GeForce NOW makes it easy to have it all. With cloud gaming, everyday laptops used for class can also become GeForce RTX-powered gam

hardwarenvidia-blog

Can AI agents conduct open-ended AI research? Most evaluations of agents conducting AI research focus on narrow, verifiable tasks. But AI re…

Can AI agents conduct open-ended AI research? Most evaluations of agents conducting AI research focus on narrow, verifiable tasks. But AI research is often open ended. Researchers pick hypotheses, dec

hardwareyann-lecun--x

Can an open-source model perform like a foundation model? @Osmosis_AI is betting yes, using reinforcement learning and the dedicated @ycombi…

Osmosis_AI claims that an open‑source model can rival a foundation model by leveraging reinforcement learning techniques. To demonstrate this, they will use the Y Combinator‑dedicated GPU cluster on T

hardwaretogether-ai--x

Four Ways to Deploy More Secure AI Agents

NVIDIA’s AI Red Team found common failure modes in enterprise AI agents: weak access controls, unrestricted code execution via tools, unprotected network egress, and exposure of plaintext secrets. The

hardwarenvidia-developer

Genie Sim PanoWorld: An Infinite Indoor 3D World Generation Pipeline via Panoramic Scene Modeling and Simulation

arXiv:2607.26646v1 Announce Type: new Abstract: We address the problem of reconstructing a high-fidelity, freely navigable 3D scene from a single 360^irc panorama, without per-scene optimization or mu

I built ganfs: A Python package that uses GANs to automate feature selection for high-dimensional datasets. (No domain expert required) [P] [R]

hardwarer-machinelearning

Hey everyone, I recently open-sourced a new Python package called ganfs (Generative Adversarial Network Feature Selection), and I wanted to share it with the community. The Problem: Selecting the best

Lightweight Image Classification of Raptor Species for Edge Devices: Rare-Species Dataset Expansion via Video Frame Extraction, Knowledge Distillation, and TensorRT Deployment

arXiv:2607.26238v1 Announce Type: new Abstract: We investigate lightweight raptor-species classification for real-time edge deployment in wind-turbine collision mitigation. Using DINOv2-L (304M parame

Research

Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities

arXiv:2505.01043v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved impressive performance across various domains. However, the substantial hardware resources required for t

researcharxiv-cs-lg

NVIDIA Exemplar Cloud: Lessons for Unlocking Full Performance on AI Infrastructure

NVIDIA’s Exemplar Cloud study shows that identical H100‑based clusters can yield 8–12 % lower training throughput when configuration gaps—at the kernel, hypervisor, BIOS or NCCL levels—prevent reachin

hardwarenvidia-developer

PolygMap: A Perceptive Locomotion Framework for Humanoid Robot Stair Climbing

arXiv:2510.12346v2 Announce Type: replace Abstract: Recently, biped robot walking technology has been significantly developed, mainly in the context of a bland walking scheme. To emulate human walking

hardwarearxiv-cs-ro

Protopia and Rafay deliver multi-tenancy for shared GPU AI factories

Enterprise AI infrastructure providers are turning to multi-tenancy paired with upstream data protection to convert idle GPU capacity into secure, token-metered services that enterprises will actually

Q&A with CuspAI's Max Welling on its AI Materials Foundry, partnerships with Nvidia and others, Geoff Hinton and Yann LeCun joining its advisory board, and more (John Thornhill/Financial Times)

John Thornhill / Financial Times: Q&A with CuspAI's Max Welling on its AI Materials Foundry, partnerships with Nvidia and others, Geoff Hinton and Yann LeCun joining its advisory board, and more — The

hardwaretechmeme

unsloth/Qwen3.6-27B-NVFP4 vs. Intel/Qwen3.6-27B-int4-AutoRound vs. nvidia/Qwen3.6-27B-NVFP4 -- which one to choose?

Are there any benchmarks on these 4 bit quants, like how Artificial Analysis runs a slew of various benchmarks? If not, how can I run one (5x over for consistency) on them? I'm also very interested in

hardwarer-localllama

Visko Orbis 1.0: A Live Model for Real-Time Interactive Long Video Generation

arXiv:2607.26694v1 Announce Type: new Abstract: We present Visko Orbis 1.0, a Live Model for real-time, interactive long-video generation. Users can change the prompt at any moment during generation,

What to expect during Black Hat USA: Join theCUBE Aug. 5-6

Artificial intelligence has propelled the cybersecurity world into a new phase, driven by startlingly advanced autonomous attacks and an urgent need to adopt technology to defend against them. This we

agreed. which is part of why coating the world in data centers is a profound mistake.

agreed. which is part of why coating the world in data centers is a profound mistake. AI will get so ridiculously efficient that we will look back at GPU clusters the way we now look at these first ro

hardwaregary-marcus--x

It's a drop-in. One program_id field and it plugs into your existing engine configs such as KV offloading + speculative decoding. Format-agn…

It's a drop-in. One program_id field and it plugs into your existing engine configs such as KV offloading + speculative decoding. Format-agnostic by design, with OpenAI chat completions supported toda

hardwaretogether-ai--x

Agents

Lowering the implementation barrier of neutral-atom quantum computing with agentic workflows

arXiv:2607.25834v1 Announce Type: cross Abstract: Quantum computers are moving from research laboratories to industrial machines accessible via the cloud and integrated into high-performance computing

agentsarxiv-cs-ai

Quasi-SVD: Learning a Lie-constrained matrix factorisation for real-time imaging

arXiv:2607.25967v1 Announce Type: new Abstract: Singular Value Decomposition (SVD) underlies matrix factorisation tasks across computational imaging, with medical applications increasingly demanding r

Super interesting new work from NVIDIA. (bookmark it) They suggest building agents as Python objects. Very cool idea and I think it could a …

Super interesting new work from NVIDIA. (bookmark it) They suggest building agents as Python objects. Very cool idea and I think it could a lot with agent reliability. More below: Agent development to

hardwaredair-ai--x

Towards Embodied Cognition in Robots via Spatially Grounded Synthetic Worlds

arXiv:2505.14366v2 Announce Type: replace Abstract: We present a conceptual framework for training Vision-Language Models (VLMs) to perform Visual Perspective Taking (VPT), a core capability for embod

A didactical-driven teacher assistant for a dimensional modeling course

arXiv:2607.22598v1 Announce Type: cross Abstract: Educational chatbots powered by large language models (LLMs) show promising effects on learning outcomes, yet most systems delegate pedagogical decisi

AMD calls its shot, but the real race is engineering velocity

At AMD’s Advancing AI event, Lisa Su called her shot – just like Babe Ruth. The question now is whether AMD has built the engineering machine to hit it. Last week, we argued that AMD’s next reinventio

Model Releases

An MLIR-Based Compilation Method for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2607.15865v2 Announce Type: replace Abstract: Large Language Models (LLMs) have become the dominant workload on modern AI accelerators, yet deploying them on specialized hardware still faces two

Anthropic and Nvidia come out against blanket bans on open-weight AI models

As the United States government debates new artificial intelligence rules and regulations, Anthropic PBC and Nvidia Corp. are drawing a line against blanket bans on open-weight models, urging regulato

Anthropic faces backlash from Silicon Valley partners, founders, and researchers for competitive tactics, guardrails, and lack of support for open-weight models (Wall Street Journal)

Wall Street Journal: Anthropic faces backlash from Silicon Valley partners, founders, and researchers for competitive tactics, guardrails, and lack of support for open-weight models — The AI pioneer f

hardwaretechmeme

Apple overtakes Nvidia to become the world's most valuable publicly traded company, two years after it lost the crown, closing at a $4.9T market cap on Monday (Kalley Huang/New York Times)

Kalley Huang / New York Times: Apple overtakes Nvidia to become the world's most valuable publicly traded company, two years after it lost the crown, closing at a $4.9T market cap on Monday — The comp

hardwaretechmeme

Are single GPU research still published in ML/DL and its applications nowadays? Which are the most notable recent ones? [D]

hardwarer-machinelearning

ML research is progressing at breakneck speed where frontier labs in both academia and industry have access to considerably large computes (GPUs). Where do small labs or independent researchers go in

Model Releases

Benchmarking LLMs for Verilog Design Flows

model-releasesarxiv-cs-lg

arXiv:2607.22759v1 Announce Type: cross Abstract: Large language models (LLMs) show promise in code generation, but their capabilities to produce correct, synthesizable hardware description language (

Beyond Block Boundaries: Multi-Block Editing for Diffusion Large Language Models

arXiv:2607.22663v1 Announce Type: new Abstract: Block diffusion has emerged as the dominant paradigm for scaling discrete diffusion language models (dLLMs), because decoding text in fixed-size blocks

Causal-TS: A Python Library for Causal Discovery in High-Dimensional and Nonstationary Time Series

arXiv:2607.24673v1 Announce Type: new Abstract: We describe Causal-TS, an open-source Python library for causal discovery in high-dimensional and nonstationary multivariate time series. Causal-TS prov

hardwarearxiv-cs-lg

CHS-SQL: A Text-to-SQL approach based on Confidence-Guided Heuristic Search Schema Linking process

arXiv:2607.22624v1 Announce Type: new Abstract: Recently, there have been several works in the Text-to-SQL domain that utilize Small Language Models (SLMs) for training. These approaches achieve perfo

CSV-Decode: Certifiable Sub-Vocabulary Decoding for Efficient Large Language Model Inference

arXiv:2511.21702v2 Announce Type: replace-cross Abstract: Large language models face significant computational bottlenecks during inference due to the expensive output layer computation over large voc

Developing Healthcare Robotics with GPU-Native Medical Physics Simulation

Healthcare robotics struggles with data scarcity, limited generalization to rare clinical scenarios, and slow prototyping due to the need for annotated demonstrations and costly experimental setups. N

hardwarenvidia-developer

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training

arXiv:2607.22614v1 Announce Type: new Abstract: RL-based LLM post-training increasingly disaggregates Rollout and Training across separate GPU resources, but static GPU partitioning suffers from sever

Evo-DKD: Dual-Knowledge Decoding for Autonomous Ontology Evolution in Large Language Models

arXiv:2507.21438v2 Announce Type: replace Abstract: Ontologies and knowledge graphs require continuous evolution to remain comprehensive and accurate, but manual curation is labor intensive. Large Lan

Hybrid Semantic and Spectral Ensemble for Robust Synthetic Image Source Attribution

arXiv:2607.22808v1 Announce Type: cross Abstract: The rapid advancement of text-to-image (T2I) models has necessitated robust Synthetic Image Source Attribution (SIA) methodologies. A critical challen

InnerGS: Internal Scenes Reconstruction and Segmentation via Factorized 3D Gaussian Splatting

arXiv:2508.13287v3 Announce Type: replace-cross Abstract: 3D Gaussian Splatting (3DGS) has recently gained popularity for efficient scene rendering by representing scenes as explicit sets of anisotrop

Kalypso: Relational LLM Serving

arXiv:2607.23815v1 Announce Type: cross Abstract: Large language models are increasingly used as semantic operators for filtering, extracting, ranking, joining, and transforming unstructured data. Exi

netflix’s stack

hardwareyohei-nakajima--x

netflix’s stack In-House LLM Serving at Netflix Netflix built an in-house LLM serving platform using vLLM and NVIDIA Triton, integrating self-hosted models into its existing production infrastructure

Omni-Prune: Query-Aware Unified Token Pruning for Efficient Omnimodal Large Language Models

arXiv:2607.23445v1 Announce Type: cross Abstract: Omnimodal large language models (OmniLLMs) are rapidly extending multimodal reasoning to cover synchronized audio and video. However, the resulting au

hardwarearxiv-cs-cl

OmniScope: Modality-Decoupled Token Compression for Omnimodal Large Language Models

arXiv:2607.23193v1 Announce Type: new Abstract: Existing token compression methods for omnimodal large language models typically rely on one modality to determine what to retain in the other. We show

OpenWiki supports 12 LLM providers: - @OpenAI API & @ChatGPT sub login - @AnthropicAI - @GeminiApp AI Studio & Enterprise Vertex - @awscloud…

hardwareharrison-chase--x

OpenWiki supports 12 LLM providers: - @OpenAI API & @ChatGPT sub login - @AnthropicAI - @GeminiApp AI Studio & Enterprise Vertex - @awscloud Bedrock - @OpenRouter - @FireworksAI_HQ - @baseten - @nebiu