Search: “nvidia”

Calibrate, Then Route: A Measured Study of Learned Request Routing for Disaggregated LLM Serving

arXiv:2609.16206v1 Announce Type: new Abstract: Disaggregated LLM serving places compute heavy prefill and memory heavy decode on separate GPU pools. Systems such as DistServe, Splitwise, and Mooncake

safetyarxiv-cs-ai

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Carry-Through Checksum: A Lightweight Fault-Detection for CNN Inference at the Edge

DGX agent

arXiv:2609.16742v1 Announce Type: cross Abstract: Convolutional Neural Networks (CNNs) are increasingly deployed in safety-critical edge applications, where soft errors can silently corrupt inference

safetyarxiv-cs-lg

16 Sept 2026

Enhancing Law-Enforcement Audio Transcription: A LoRA-Based Adaptation of Whisper for BWC Footage

arXiv:2607.27245v2 Announce Type: replace-cross Abstract: Modern policing faces a 'visibility paradox' where law enforcement agencies possess petabytes of Body-Worn Camera (BWC) footage that remains l

FlashVector: Agent for Hierarchical Model Serving Stack Optimization

arXiv:2609.17391v1 Announce Type: new Abstract: Model serving is one of the largest cost drivers in production recommender systems. Maximizing its throughput requires navigating a deeply layered hiera

hardwarearxiv-cs-ai

I built a native Vulkan training backend for 143 modern Transformer architectures — no CUDA or PyTorch required

I've been working on something that started as the training backend for my Hierarchos architecture, but it has grown into a much broader project: https://github.com/necat101/Hierarchos-Native Hierarch

Is INT8 Portable? A Cross-Platform Measurement Study of Quantized Inference on Embedded and Automotive Accelerators

arXiv:2609.16085v1 Announce Type: cross Abstract: Eight-bit integer (INT8) post-training quantization is the default recipe for edge deployment, under a widely held assumption: INT8 makes inference fa

The hardest part of and “org harness” or “enterprise ai” (as opposed to personal ai” is auth, and managing auth in a multiplayer channel (li…

model-releasesharrison-chase--x

The hardest part of and “org harness” or “enterprise ai” (as opposed to personal ai” is auth, and managing auth in a multiplayer channel (like slack) We’re thinking a lot about how to do this right fo

BLInD: Learning Driver Intent as a Distribution over Future Ego Trajectories

arXiv:2609.13941v1 Announce Type: new Abstract: We present BLInD (Blind Learned Intent Distribution), a compact network that maps recent vehicle-state history (e.g. speed, curvature, indicator, and ve

safetyarxiv-cs-cv

GGUF-Metadata Prediction of Single-Sequence llama.cpp Throughput Across Three Systems

arXiv:2609.14864v1 Announce Type: new Abstract: We predict single-sequence model throughput from GGUF metadata using roofline-shaped predictors with quantization-specific scale factors fitted on refer

Goal-Oriented Communications for Physical AI: Design and Testbed

arXiv:2609.15895v1 Announce Type: new Abstract: Physical AI relies on frequently-updated, latency-sensitive video stream to perceive, reason, and interact with the physical world, resulting in strict

hardwarearxiv-cs-ro

Is Semantic SLAM Ready for Embedded Systems ? A Comparative Survey

arXiv:2505.12384v2 Announce Type: replace Abstract: Semantic SLAM holds promise for robust robot navigation in complex environments, but its practicality on embedded systems remains uncertain. This pa

hardwarearxiv-cs-ro

Jensen Huang completely destroys Jacob Coxon’s (ex-Anthrpic employee) 10% extinction prediction. no data, no scientific grounding, no defens…

Jensen Huang completely destroys Jacob Coxon’s (ex-Anthrpic employee) 10% extinction prediction. no data, no scientific grounding, no defensible 10%. 'First of all, we shouldn’t [try to explain a 10%

hardwareyann-lecun--x

Jensen Huang took a surprise call from President Trump onstage at the All-In Summit on Monday in LA, where the two dismissed fears of an AI takeover (New York Times)

New York Times: Jensen Huang took a surprise call from President Trump onstage at the All-In Summit on Monday in LA, where the two dismissed fears of an AI takeover — Mr. Trump called Jensen Huang, Nv

safetytechmeme

Netherlands-based inference chip startup Euclyd raised a €200M+ Series A co-led by Samsung, Somerset Capital, Scaleup Europe Fund, and Innovation Industries (Kai Nicol-Schwarz/CNBC)

Kai Nicol-Schwarz / CNBC: Netherlands-based inference chip startup Euclyd raised a €200M+ Series A co-led by Samsung, Somerset Capital, Scaleup Europe Fund, and Innovation Industries — Samsung has bac

hardwaretechmeme

TriCalRAG: A Three-Strategy, Retrieval-Augmented Benchmark for On-Premise LLM-Based Root Cause Analysis in AIOps

arXiv:2609.14762v1 Announce Type: cross Abstract: Cloud-hosted large language models (LLMs) are increasingly used for root cause analysis (RCA) in AIOps pipelines, but they introduce data privacy risk

What Input Resolution Is Required for Bird Species Identification, and What Is Its Latency Cost on an Edge Device? A Study of 14 Input Resolutions and Six Architectures with On-Device Measurements

arXiv:2609.14247v1 Announce Type: new Abstract: Bird-strike mitigation at wind farms requires identifying distant birds that span only tens of pixels, so the classifier's input resolution N is a desig

local-aiarxiv-cs-cv

4D Parallelism Unlocks Exascale Bayesian Neural Networks for High-Fidelity Atmospheric Modeling

model-releasesarxiv-cs-lg

arXiv:2609.12815v1 Announce Type: cross Abstract: We present BEAST, the first-ever Bayesian Swin Transformer for atmospheric forecasting on 0.25^irc global resolution able to accurately quantify both

BRIDGE-EEG: Bridging Self-Supervised Pretraining and Efficient Deployment for Cross-Dataset EEG Classification

arXiv:2609.12218v1 Announce Type: cross Abstract: The growing use of electroencephalography (EEG) motivates automated analysis that is accurate, transferable, and deployable on constrained hardware. R

Curriculum-Based Adversarial Heterogeneous Agent Reinforcement Learning for Autonomous Quad-Copter Landing in Maritime Settings

model-releasesarxiv-cs-lg

arXiv:2609.12758v1 Announce Type: new Abstract: Recovering unmanned aerial vehicles (UAVs) in maritime environments is challenging due to wind turbulence and ship-deck motion, making it a valuable tes

I feel like the data sovereignty movement for firms is going to run headlong into the challenge that maintaining fine-tuned small models in …

model-releasesethan-mollick--x

I feel like the data sovereignty movement for firms is going to run headlong into the challenge that maintaining fine-tuned small models in a way that continually beats larger general-purpose models i

Input Resolution Matters: Real-Time Object Detection Latency

model-releasesarxiv-cs-cv

arXiv:2609.12920v1 Announce Type: new Abstract: We model total latency as the convolution of preprocessing, inference, and postprocessing distributions under a simplifying independence approximation,

LLM Compression by Block Removal with Constrained Binary Optimization

model-releasesarxiv-cs-cl

arXiv:2602.00161v3 Announce Type: replace-cross Abstract: In this paper, we formulate the compression of large language models (LLMs) by optimally deleting transformer blocks (``block removal'') as a

Running Qwen 3.8 next on 16vram+32ram - A useful/fun post for the gpu poors

Hello Reddit. Posting this for fun. I thought it was a lonely and silly journey to set up Qwen 3.8 Next on a system that doesn't really run it properly—it was a challenge that might help the community

UkisAI Swift-Qwen3.8-27B / -58.3% thinking, x1.95 speed while keeping the accuracy of xhigh

Hi everybody, we post-trained Qwen 3.8 27B to be more efficient by figuring out which tokens were linked to overthinking and penalizing them without 'attacking' the reasoning length directly then fixe

Agents

Vera Rubin NVL72 Agentic Inference: 67x better Performance per Dollar

**Summary for AI knowledge base** Vera Rubin NVL72 is a co‑designed platform combining the Rubin GPU, Vera CPU, NVLink 6 Switch, ConnectX‑9, BlueField‑4, and Spectrum‑6, targeting agentic inference wo

agentssemianalysis

What are the current best retail GPUs for max VRAM at a reasonable price?

I am considering dumping my ChatGPT Plus subscription and go full local, but to do so I would first need to reach a decent result for quality (and reasonable speed). My 4090 fried itself out of nowher

3k$ 128GB VRAM + 256GB RAM DDR4 Server

I finished my home inference server. First I tried Lenovo p620 workstation and while it’s a good value overall it pissed me off with a ton of proprietary Lenovo shit to deal with and I return it in th

13 Sept 2026

Wild 24 hours for AI and lots of different proposals have been made. TLDR; the only tangible new fact is that OpenAI and Anthropic are goi…

model-releaseselon-musk--x

Wild 24 hours for AI and lots of different proposals have been made. TLDR; the only *tangible* new fact is that OpenAI and Anthropic are going to have embedded 3rd party evaluators from unknown organi

13 Sept 2026

For those of you forced to only use open models from Western labs in production, what are you deploying?

First off, I know that GLM, Qwen, and DeepSeek absolutely dominate in terms of SOTA Open Source models, and that’s what I use in my personal projects and for school, however, I’m also responsible for

12 Sept 2026

It's now clear that: - alignment is critical to making AI safe - alignment won't be solved behind the closed doors of a handful of frontier …

It's now clear that: - alignment is critical to making AI safe - alignment won't be solved behind the closed doors of a handful of frontier labs So we're taking two steps: - launching the Open Alignme

safetyclem-delangue--x

12 Sept 2026

THE CURE IS THE PITCH Dario’s 'Pacing' Essay Is Quiet-Period Illegal Stock Promotion Wrapped in Regulatory Capture Dario Amodei's 'We Must P…

model-releasesyann-lecun--x

THE CURE IS THE PITCH Dario’s 'Pacing' Essay Is Quiet-Period Illegal Stock Promotion Wrapped in Regulatory Capture Dario Amodei's 'We Must Pace the Frontier' is not a safety paper. It is a pre-roadsho

12 Sept 2026

7900 XTX + 32/64GB RAM for Qwen 3.8 Flash Next?

Planning to build a PC mainly for local LLMs/coding agents. I keep seeing 3090 + Qwen 3.8 Flash Next benchmarks, but could not find enough info for the 7900 XTX 24GB. 3090s are hard to find where I li

CodeFinetuner: Fine-tune a local code autocomplete model on your own codebase

Hi everyone, I was interested in learning LoRA fine-tuning, and ended up building CodeFinetuner over the past few months, a full pipeline that fine-tunes a small code autocomplete model (e.g. Qwen2.5-

Does YOLO26 Truly Offer Advantages Over Its Predecessors for Edge Deployment? A Benchmark Study in Aquaculture

model-releasesarxiv-cs-cv

arXiv:2607.09835v2 Announce Type: replace Abstract: The recently introduced YOLO26 architecture incorporates NMS-free end-to-end inference and is optimized for deployment on resource-constrained CPU-b

Improving 5G AI-RAN MCS Selection by Predicting Retransmissions

arXiv:2609.09324v1 Announce Type: cross Abstract: Link Adaptation (LA) in 5G NR is inherently reactive, relying on channel measurements and HARQ feedback that may become quickly obsolete when the chan

Introducing Fugu Max and Fugu Ultra v2: the next evolution of Sakana Fugu’s multi-agent orchestration system. Try: https://sakana.ai/fugu Bl…

model-releasesdavid-ha--x

Introducing Fugu Max and Fugu Ultra v2: the next evolution of Sakana Fugu’s multi-agent orchestration system. Try: https://sakana.ai/fugu Blog: https://sakana.ai/fugu-max-release/ The frontier that ac

Is a ZIMA Board 2 + RTX 2000 ADA the cheapest path to a decent Qwen-3.8 27b self-contained endpoint?

I just watched a YouTube from Luke’s Dev Lab where he literally just plugged a RTX 2000 ADA Into the side of the Zima Board 2’s PCIE socket and it just friggin worked and had great token speed despite

Orukeet, new ASR model based on Parakeet

I haven't seen this mentioned yet, so I thought it deserves a post. I was trying out OpenWhispr when this model came up as the recommendation. So I don't have personal experience yet, but it's suppose

Phase-Decoupled, Model-Calibrated Power Control for Disaggregated LLM Serving

arXiv:2609.11133v1 Announce Type: new Abstract: Datacenter GPU power is the binding constraint on LLM serving capacity, and production serving has shifted to prefill/decode (PD) disaggregation. Deploy

Reification as a Transferable Vocabulary: Zero-Shot Link Prediction with Vanilla GNNs

arXiv:2609.11347v1 Announce Type: new Abstract: Knowledge graph foundation models such as ULTRA achieve zero-shot link prediction on unseen graphs through dedicated architectures that hard-code a tran

This is why we need open-source harnesses + local models

i've been thinking about this more after trying different agent setups. the model isn't the only thing that determines how well an agent performs. The harness around the model matters a lot too. With

Characterizing Contention-Induced Reliability Collapse in KV-Cache Timing Side Channels for Multi-Tenant LLM Serving

arXiv:2609.06853v1 Announce Type: cross Abstract: Shared key--value (KV) cache reuse improves large language model (LLM) serving, but it can also create a timing side channel that reveals whether a pr

Learning Terrain-Adaptive Humanoid Locomotion on Granular Terrain

arXiv:2609.10286v1 Announce Type: new Abstract: Humanoid locomotion on granular terrain remains a significant challenge due to its complex foot-terrain interaction dynamics that are difficult to model

safetyarxiv-cs-ro

RedKnot-MLA: Multi-Head Offline-Online Reuse for DeepSeek-V4 Long-Context Serving

arXiv:2609.07008v1 Announce Type: new Abstract: Multi-head latent attention (MLA) exposes many logical query heads through one packed latent KV stream. This representation is memory efficient, but it

Sources: Sam Altman told OpenAI employees that the company is considering slowing cutting-edge AI development, and he hopes other AI companies will do the same (Bloomberg)

Bloomberg: Sources: Sam Altman told OpenAI employees that the company is considering slowing cutting-edge AI development, and he hopes other AI companies will do the same — OpenAI is considering slowi

local-aitechmeme

A Measurement Study of LLM Inference Trade-offs Across Edge Continuum Hardware

model-releasesarxiv-cs-lg

arXiv:2609.08307v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as backends for intelligent web services, but serving them across the edge continuum requires balan

9 Sept 2026

CoSA: Correlation-Guided Change A ttention with Learnable Residual Gating for Remote Sensing Change Detection

model-releasesarxiv-cs-cv

arXiv:2609.08914v1 Announce Type: new Abstract: Pixel-level annotation of fixed traffic-camera imagery is expensive, while crosswalk models trained from street-level imagery face a substantial viewpoi

9 Sept 2026

FALCON-S: Fixed-wing ground-effect Aerodynamics Simulator and Flight Control Learning Suite

arXiv:2609.06046v1 Announce Type: cross Abstract: We present a modular, high-fidelity simulation framework for the development and benchmarking of flight control strategies in fixed-wing aerial robots