hardware

DyRA: Dynamic Residual Approximation for Efficient Matrix Multiplication in DNNs

arXiv:2610.02882v1 Announce Type: cross Abstract: Large-scale foundation models achieve strong performance across diverse tasks, but their size makes inference costly, largely due to dense matrix mult

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Efficient Memory Crystallization for Graph Learning under Non-Stationary Distribution Shifts

DGX agent

arXiv:2610.02795v1 Announce Type: new Abstract: Deep graph learning models deployed in real-world systems often need to cope with non-stationary environments, where the underlying graph distribution d

hardwarearxiv-cs-lg

5 Oct 2026

Exclusive: Iterate.ai’s Lifeboat runs up to six times more AI agent sessions per GPU

Enterprise artificial intelligence software company Iterate Studio Inc. today launched Lifeboat, an inference engine for large language models that has confidential computing built in. Iterate.ai says

FlashSinkhorn 2: Block-Sparse Entropic Optimal Transport

arXiv:2610.02395v1 Announce Type: new Abstract: Streaming GPU solvers for entropic optimal transport (EOT), such as FlashSinkhorn, avoid storing the dense kernel but still evaluate all nimes m point p

From Scan to Treatment Plan, AI Helps Close Breast Cancer’s Deadliest Gaps

Breast cancer is the most commonly diagnosed cancer among American women — yet the gaps in care are wide. A majority of women over age 40 skip the recommended annual screening. Radiologists are readin

hardwarenvidia-blog

Ghost, which makes a 3,499 computer designed for AI agents and includes an RTX Pro 4000 SFF Blackwell GPU, emerges from stealth with an 11M seed led by a16z (Dominic-Madori Davis/TechCrunch)

Dominic-Madori Davis / TechCrunch: Ghost, which makes a 3,499 computer designed for AI agents and includes an RTX Pro 4000 SFF Blackwell GPU, emerges from stealth with an 11M seed led by a16z — For mu

Hardware-Native Joint Sparse-Quantization for Trillion-Scale Mixture-of-Experts

arXiv:2610.02241v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures allow frontier language models to scale to trillions of parameters, but their deployment is constrained by mass

I2CD: Direct Image-to-Convex Decomposition for Simulation-Ready Collision Geometry

arXiv:2610.03453v1 Announce Type: cross Abstract: Physics simulators and motion planners require convex collision geometry, yet image-to-3D generative models output dense, frequently non-manifold visu

Lightweight and Resource-Efficient Perception for Robotic Guide Dogs

arXiv:2610.03187v1 Announce Type: cross Abstract: Multi-camera streaming perception is increasingly deployed on heterogeneous edge platforms shared with co-resident workloads, yet accelerator placemen

NetApp’s Novus tackles metadata bottlenecks in AI data infrastructure

AI data infrastructure must support growing GPU clusters while making enterprise data usable for models and agents. NetApp Inc. is tying intelligent data infrastructure to production AI through a unif

Nvidia and CoreWeave tackle the CPU bottleneck in agentic AI infrastructure

Agentic AI infrastructure must support the work between a model’s decisions as agents move from answering questions to executing tasks. Central processing units handle much of that execution, while gr

Practical limit hit. Decoding so fast that tool calls (cpu) starting to become real limit not decode or prefill. Single RTX5090. Porting Kenshi to Godot project.

Hi folks, LIVE PROJECT PAGE TLDR: Moral of the story. You need better CPU to do actual agentic coding doing real work... I've been on a mission to make my RTX5090 go brrr for past 2 months so much so

hardwarer-localllama

Probe the Harness: Setup Checks for Stale-Data RL Comparisons in Language Models

arXiv:2610.02911v1 Announce Type: cross Abstract: Methods for training language models on stale samples are judged by comparisons against importance-corrected baselines. We show that details of the ex

hardwarearxiv-cs-cl

Sources: AI inference-chip startup Etched is in early talks to raise funding at a 40B-50B valuation, up from $21B in August (Marina Temkin/TechCrunch)

Marina Temkin / TechCrunch: Sources: AI inference-chip startup Etched is in early talks to raise funding at a 40B-50B valuation, up from 21B in August — Although it's only been a couple of months sinc

Sovereign AI: Accelerate innovation with control and choice

Explore how Microsoft and NVIDIA are helping organizations advance sovereign AI with greater control, choice, flexibility, and resilience across cloud, edge, and customer-controlled environments. The

hardwaremicrosoft-cloud

Tailoring the Quantization Space for 1-Bit KV Cache Compression

arXiv:2610.03027v1 Announce Type: cross Abstract: The key-value (KV) cache becomes a major memory bottleneck in long-context LLM inference, placing substantial pressure on memory capacity and bandwidt

The difference in what Anthropic and OpenAI as well as many others give you in value for a subscription is insane. We tested Meta, Minimax, …

The difference in what Anthropic and OpenAI as well as many others give you in value for a subscription is insane. We tested Meta, Minimax, Kimi, Grok, and Cursor subscriptions It doesn't make sense t

hardwaredylan-patel--x

Windfoil: Closed-Form Coverage for Real-Time and Differentiable Vector Graphics

arXiv:2610.02468v1 Announce Type: cross Abstract: We present Windfoil, a GPU-friendly algorithm that treats rasterisation and differentiable vector graphics as two sides of the same problem by evaluat

Yann LeCun's latest talk at ETH Zürich 'You should not work on LLM. At least if you're in academia, you should absolutely not work on LLMs. …

Yann LeCun's latest talk at ETH Zürich 'You should not work on LLM. At least if you're in academia, you should absolutely not work on LLMs. There is nothing you can bring to the table. If you're inter

hardwareyann-lecun--x

Q&A with Google SVP and DeepMind Institute co-director James Manyika on AI risks and why responsibility must be shared across industry, government, and society (Mishal Husain/Bloomberg)

Mishal Husain / Bloomberg: Q&A with Google SVP and DeepMind Institute co-director James Manyika on AI risks and why responsibility must be shared across industry, government, and society — The accord,

4 Oct 2026

Q&A with OpenAI VP of Hardware Richard Ho on its Jalapeño inference chip co-designed with Broadcom, using internal OpenAI models to design the chip, and more (Dr. Ian Cutress/More Than Moore)

Dr. Ian Cutress / More Than Moore: Q&A with OpenAI VP of Hardware Richard Ho on its Jalapeño inference chip co-designed with Broadcom, using internal OpenAI models to design the chip, and more — VP Ha

4 Oct 2026

Sources: several Western open-weight models are set to launch this month, including Reflection AI's first model, which will rival top Chinese open-weight models (Bradley Olson/Axios)

Bradley Olson / Axios: Sources: several Western open-weight models are set to launch this month, including Reflection AI's first model, which will rival top Chinese open-weight models — A closely watc

4 Oct 2026

Anyone else finding it harder to justify a new GPU upgrade lately?

I have been running the same midrange card for a couple of years now, and every model release sends me back to the price sheets. The performance gains are real but they keep landing next to price tags

hardwarer-localllama

3 Oct 2026

Nasdaq-listed neocloud Nebius acquires Inferize, whose tech helps optimize GPU utilization and reduce AI request costs, sources say for 100M to 150M (Meir Orbach/CTech)

Meir Orbach / CTech: Nasdaq-listed neocloud Nebius acquires Inferize, whose tech helps optimize GPU utilization and reduce AI request costs, sources say for 100M to 150M — The Israeli startup, which w

3 Oct 2026

Banger paper from NVIDIA on long running agents. A model can accept 128K tokens of context and still make more mistakes the longer it works …

Banger paper from NVIDIA on long running agents. A model can accept 128K tokens of context and still make more mistakes the longer it works through a task. If your agent loses its place partway throug

hardwaredair-ai--x

CAST: Cost-Aware Speculative Trees from One-Pass Block Drafters

arXiv:2610.00321v1 Announce Type: cross Abstract: Speculative decoding accelerates large language model inference by drafting future tokens cheaply and verifying them with the target model in parallel

Denoising Surface: Modeling and Predicting Inference Cost for Diffusion LLM Serving

arXiv:2610.00499v1 Announce Type: new Abstract: As diffusion large language models (dLLMs) become more capable, they are moving from research settings to real-world extit{serving}, where request manag

DRelay: Global Draft Context for Prefix-Aware Parallel Speculative Decoding Repair

arXiv:2610.01439v1 Announce Type: new Abstract: Parallel drafting reduces the drafting overhead of speculative decoding for large language models (LLMs), but its gains remain limited by the accepted p

Fast Polynomial Transcendentals for LLMs

arXiv:2610.00049v1 Announce Type: new Abstract: Graphics processing unit (GPU) generations scale matrix, special-function, and memory pipelines at different rates, so kernel bottlenecks move as hardwa

FastCI: Efficient GPU-Intensive CI for LLM Training Frameworks

arXiv:2610.01967v1 Announce Type: new Abstract: As large language models (LLMs) keep growing in size and complexity, their training frameworks evolve at a rapid pace as well. Therefore, continuous int

ibUMAP: Coherent and Scalable Field Evaluation for UMAP Optimization

arXiv:2610.01445v1 Announce Type: new Abstract: UMAP achieves scalable layout optimization through stochastic negative sampling. However, this stochasticity can lead to unstable embeddings across reru

LESS: Lightweight Evolutionary Supernet Search in Minutes

arXiv:2610.01468v1 Announce Type: cross Abstract: Low-cost NAS must both explore high-performing architectures and identify them reliably, yet reducing evaluation cost often weakens the fidelity of ca

Leto: Fast In-Place Recovery for LLM Training on Surviving Hardware

arXiv:2610.00687v1 Announce Type: cross Abstract: Hardware-operable failures (HOFs) interrupt large language model (LLM) training but permit recovery on the same hardware without reset, repair, or rep

MINCE: Shrinking LLM Evaluation Datasets via Few-Model Monte Carlo Calibration

arXiv:2606.22826v2 Announce Type: replace Abstract: Evaluating LLMs across many model variants---quantized, fine-tuned, or deployment-specific---requires running large benchmarks repeatedly, a process

ORBIT-FMIB: Tracking Order-Resolved Epistatic Information Through ESM-2

arXiv:2610.00672v1 Announce Type: new Abstract: Protein foundation models support mutation-effect and structural prediction, but predictive performance alone does not reveal which forms of biological

Qwen3.8-Flash-Next (5.05bpw + ngram at bf16) exl3 on one r9700: 863 t/s prefill and 35 t/s decode at 230k context (256k max), is that ok or am i missing something?

Hi, i got QFN running on my single r9700 but im not sure if i did everything right to get the best quality and speed out of this setup. Dont want to annoy anybody, maybe someone with the same card can

hardwarer-localllama

TensorCommitments: A Lightweight Verifiable Inference for Language Models

arXiv:2602.12630v2 Announce Type: replace-cross Abstract: Most large language models (LLMs) run on external clouds: users send a prompt, pay for inference, and must trust that the remote GPU executes

The Comfy Dev Platform Challenge is open! Partners: @ltx_io & @bfl_ai For two weeks (10/5–10/19), we're challenging the community to open-so…

The Comfy Dev Platform Challenge is open! Partners: @ltx_io & @bfl_ai For two weeks (10/5–10/19), we're challenging the community to open-source a paid AI feature. 🏆 $10K grand prize 🖥️ 3x NVIDIA RTX

hardwarecomfyui--x

Towards Automatic Video Annotation with ASH: Zero-Shot Open-Vocabulary Multi-Object Tracking and Segmentation

arXiv:2610.01022v1 Announce Type: new Abstract: Memory-attention-based Video Instance Segmentation (VIS) methods have demonstrated strong zero-shot tracking capability, yet their substantial memory re

Training-Free Diffusion Planning with Analytical Local Scores

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

Wiring and powering GPUs differently can swing AI latency by orders of magnitude, says CoreWeave

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

A Pre-trained Variational Autoencoder for Gyrokinetic Plasma Turbulence Surrogate Modeling

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

Bongard: Training Machine Intuition

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

hardwarearxiv-cs-cl

Build agent memory with NVIDIA NeMo Agent Toolkit and Amazon S3 Vectors

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

hardwareaws-ml-blog

Build Applications on NVIDIA BlueField Faster with NVIDIA DOCA Agent Skills

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

hardwarenvidia-developer

Data-Efficient Adaptation of a Driving VLA to Class 8 Trucks

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

hardwarearxiv-cs-ro

Dense Temporal Motion Retargeting for Legged Robots

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,

hardwarearxiv-cs-ro

DynaFlow: Transparent and Flexible Intra-Device Parallelism via Programmable Operator Scheduling

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