Search: “nvidia”

Engrams Embedding Entendre: Codesign for Efficient DRAM/SSD Offloading

model-releasessemianalysis

Engram Embedding Entendre is a model‑architecture optimization that extends standard token embeddings with learned multi‑token lookups, enabling recurring local patterns to be retrieved directly from

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

DGX agent

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

hardwarearxiv-cs-cv

18 Sept 2026

GR2PO: Group Relative Return Policy Optimization for Continuous Robot Control

arXiv:2609.19850v1 Announce Type: new Abstract: Actor-critic architecture has been widely used in continuous robot control. However, they rely on learning a value network, introducing additional compu

safetyarxiv-cs-ro

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

model-releasesarxiv-cs-lg

arXiv:2609.19657v1 Announce Type: cross Abstract: Repeated prompt prefixes are increasingly common in LLM serving workloads, appearing in system prompts, templated retrieval-augmented generation pipel

Still on the Jev waitlist? I hosted OpenJev. It's free, go play with it

TypeSafe announced Jev on Tuesday: you give it data plus typed questions (yes/no, pick-one, 0–N scale) and it returns a probability for every option, crazy fast. I signed up and then refreshed my inbo

local-air-localllama

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

Video DeltaNet: A Video-Native Hybrid Attention for Livestream Video Generation

arXiv:2609.20744v1 Announce Type: new Abstract: Video diffusion models repeatedly process long spatiotemporal token sequences during denoising, making attention a major computational bottleneck. Linea

safetyarxiv-cs-lg

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

CALOS: Control-Affine Lyapunov On-manifold Safety Layer for Safe Deep Reinforcement Learning for Quadrotors

arXiv:2609.17758v1 Announce Type: cross Abstract: Deep Reinforcement Learning has demonstrated remarkable capability in quadrotor control, yet learned policies offer no guarantee of respecting safety

safetyarxiv-cs-ai

FIVE-VLA: Fast and EffectIVE Autonomous Driving with Recurrent Action Memory

model-releasesarxiv-cs-ro

arXiv:2609.18623v1 Announce Type: cross Abstract: State-of-the-art vision-language-action models (VLA) for autonomous driving face critical limitations: excessive parameter counts, inefficient high-re

Learning to Stack: Cube-Stacking Imitation Learning from Virtual Reality Demonstrations

arXiv:2609.19040v1 Announce Type: new Abstract: Imitation learning is attractive for robot manipulation, but collecting demonstrations remains a bottleneck for multi-stage tasks requiring repeated sce

safetyarxiv-cs-ro

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

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

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

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

VLM-MPPI: Grounding Natural Language in Behaviorally Diverse Trajectories for Aerial Navigation

arXiv:2609.18451v1 Announce Type: new Abstract: We present a hierarchical UAV navigation framework that aligns natural-language intent with dynamically feasible flight behaviors in cluttered indoor en

safetyarxiv-cs-ro

Where Should Agents Live? Energy-Memory Characterization of Agentic AI for the Edge-Cloud Continuum

arXiv:2609.18283v1 Announce Type: new Abstract: As telecommunication networks evolve toward autonomous 5G-Advanced and 6G operations, agentic artificial intelligence (AI) workflows, where large langua

“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

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

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

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

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

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

hardwarearxiv-cs-lg

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

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

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

hardwarearxiv-cs-lg

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

local-air-localllama

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

local-air-localllama

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 …