Search: “hardware”

Synthetic Sociality: How Generative Models Privatize the Social Fabric

arXiv:2605.14090v1 Announce Type: cross Abstract: We put forth a critical theoretical framework for analyzing generative models both descriptively and normatively. Our thesis is that generative models

15 May 2026

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Towards Resource-Efficient LLMs: End-to-End Energy Accounting of Distillation Pipelines

DGX agent

arXiv:2605.13981v1 Announce Type: cross Abstract: The rise in deployment of large language models has driven a surge in GPU demand and datacenter scaling, raising concerns about electricity use, grid

hardwarearxiv-cs-ai

15 May 2026

Woodelf++: A Fast and Unified Partial Dependence Plot Algorithm for Decision Tree Ensembles

arXiv:2605.14578v1 Announce Type: new Abstract: Partial Dependence Plots (PDPs) visualize how changes in a single feature affect the average model prediction. They are widely used in practice to inter

15 May 2026

almost all LLM “thought” is derivative. below just sounds like hype to me

almost all LLM “thought” is derivative. below just sounds like hype to me 📁 Jensen Huang, CEO of NVIDIA, says GPT was never just about generating images or text but about generating thought itself. Th

hardwaregary-marcus--x

British inference chip startup Fractile bags $220M to accelerate token consumption

U.K.-based artificial intelligence inference chip startup Fractile Ltd. said today it has closed on a 220 million Series B round of funding. The company was founded in 2022 by the Oxford University-tr

DIVER:Diving Deeper into Distilled Data via Expressive Semantic Recovery

arXiv:2605.12649v1 Announce Type: new Abstract: Dataset distillation aims to synthesize a compact proxy dataset that is unreadable or non-raw from the original dataset for privacy protection and highl

Elon Musk with NVIDIA CEO Jensen Huang, Apple CEO Tim Cook, President Trump, Chinese President Xi Jinping, and members of the U.S. delegatio…

This post appears to show Elon Musk in a photo with NVIDIA CEO Jensen Huang, Apple CEO Tim Cook, U.S. President Trump, Chinese President Xi Jinping, and members of a U.S. delegation, though the specif

hardwareelon-musk--x

EMO: Frustratingly Easy Progressive Training of Extendable MoE

arXiv:2605.13247v1 Announce Type: new Abstract: Sparse Mixture-of-Experts (MoE) models offer a powerful way to scale model size without increasing compute, as per-token FLOPs depend only on k active e

FlashSampling: Fast and Memory-Efficient Exact Sampling

arXiv:2603.15854v2 Announce Type: replace-cross Abstract: Sampling from a categorical distribution is mathematically simple, but in large-vocabulary decoding, it often triggers extra memory traffic an

Flow Augmentation and Knowledge Distillation for Lightweight Face Presentation Attack Detection

arXiv:2605.13108v1 Announce Type: new Abstract: Face presentation attack detection (FacePAD) remains challenging under diverse spoofing representation, including 2D print and replay, 3D mask-based spo

How the NVIDIA Vera Rubin Platform is Solving Agentic AI’s Scale-Up Problem

The NVIDIA Vera Rubin Platform is a rack-scale AI supercomputer designed to power agentic AI and reasoning models at scale by eliminating bottlenecks in communication and memory movement for efficient

hardwarenvidia-developer

Made a simple utility to share your GPU profile traces. `uvx trace-tuil <local traces> -b <hf bucket name>`

A utility tool was created to streamline sharing GPU profile traces by uploading them to Hugging Face buckets using the command `uvx trace-tuil -b `. This simplifies the process of distributing perfor

hardwareclem-delangue--x

OP4KSR: One-Step Patch-Free 4K Super-Resolution with Periodic Artifact Suppression

arXiv:2605.13457v1 Announce Type: new Abstract: Diffusion-based real-world image super-resolution (Real-ISR) has achieved remarkable perceptual quality; however, directly super-resolving images to 4K

Sea You in the Cloud: ‘Subnautica 2’ Early Access Dives Onto GeForce NOW

Dive masks on — Subnautica 2 is making a splash on GeForce NOW day-and-date with launch, so members can plunge into the title’s brand-new alien ocean from almost any device. It leads 11 new games join

hardwarenvidia-blog

Since going on @creatine_cycle podcast 1.5 months ago, I have lost 4.8 pounds of fat and gained 4.6 pounds of muscle. Swole as a service wor…

Since going on @creatine_cycle podcast 1.5 months ago, I have lost 4.8 pounds of fat and gained 4.6 pounds of muscle. Swole as a service works. on today's episode of Swole as a Service i brought my go

hardwaredylan-patel--x

Together AI STT models now hold the top two spots for transcription speed on the @ArtificialAnlys Speech to Text leaderboard. NVIDIA Parakee…

Together AI STT models now hold the top two spots for transcription speed on the @ArtificialAnlys Speech to Text leaderboard. NVIDIA Parakeet TDT 0.6B V3 on Together AI ranks #1, transcribing 303 seco

hardwaretogether-ai--x

A profile of California Rep. Ro Khanna, who spent years cheering on the tech industry and now supports a 5% billionaire wealth tax and stricter AI regulations (Bloomberg)

Bloomberg: A profile of California Rep. Ro Khanna, who spent years cheering on the tech industry and now supports a 5% billionaire wealth tax and stricter AI regulations — Ro Khanna spent years cheeri

Accelerated X-Ray Analysis for Nanoscale Imaging (XANI) of Novel Materials

XANI (X-ray Analysis for Nanoscale Imaging) is an accelerated computing pipeline developed by NVIDIA engineers for rapid X-ray data analysis. NVIDIA's accelerated computing enables real-time experimen

hardwarenvidia-developer

AutoLLMResearch: Training Research Agents for Automating LLM Experiment Configuration -- Learning from Cheap, Optimizing Expensive

arXiv:2605.11518v1 Announce Type: cross Abstract: Effectively configuring scalable large language model (LLM) experiments, spanning architecture design, hyperparameter tuning, and beyond, is crucial f

BOOST: BOttleneck-Optimized Scalable Training Framework for Low-Rank Large Language Models

arXiv:2512.12131v2 Announce Type: replace Abstract: The scale of transformer model pre-training is constrained by the increasing computation and communication cost. Low-rank bottleneck architectures o

ChunkFlow: Communication-Aware Chunked Prefetching for Layerwise Offloading in Distributed Diffusion Transformer Inference

arXiv:2605.11335v1 Announce Type: cross Abstract: Layerwise offloading reduces the GPU memory footprint of large diffusion transformer (DiT) inference by prefetching upcoming layers from host memory,

CME Group and Silicon Data to launch AI compute futures market

Silicon Data, the startup that provides market intelligence for artificial intelligence compute infrastructure, will provide the price indexes for a new futures market that will allow investors to hed

Efficient Remote KV Cache Reuse with GPU-native Video Codec

arXiv:2602.09725v3 Announce Type: replace-cross Abstract: Remote KV cache reuse fetches KV cache for identical contexts from remote storage, avoiding recomputation, accelerating LLM inference. While i

Fast MoE Inference via Predictive Prefetching and Expert Replication

arXiv:2605.11537v1 Announce Type: new Abstract: The Mixture of Experts (MoE) architecture has become a fundamental building block in state-of-the-art large language models (LLMs), improving domain-spe

How the 'Facebook House' in Los Altos, Mark Zuckerberg's former residence, became a hub for Chinese AI talent, who are a key part of Silicon Valley's AI boom (Viola Zhou/Rest of World)

Viola Zhou / Rest of World: How the “Facebook House” in Los Altos, Mark Zuckerberg's former residence, became a hub for Chinese AI talent, who are a key part of Silicon Valley's AI boom — Chinese-born

NVIDIA, Ineffable Intelligence Team Up to Build the Future of Reinforcement Learning Infrastructure

Reinforcement-learning agents — AI systems that learn by trial and error — can convert computation into new knowledge. That’s the focus of a new engineering-level collaboration between NVIDIA and Inef

hardwarenvidia-blog

Recursive Superintelligence raises $650M to build self-improving AI models

Recursive Superintelligence Inc., a startup that hopes to develop self-improving artificial intelligence models, launched today with 650 million in funding. Alphabet Inc.’s GV fund and Greycroft led t

Red Hat and Intel spotlight scalable AI inference as enterprises move beyond the GPU gold rush

As companies move from testing AI to broader adoption, the biggest challenge is building scalable AI inference systems that perform without breaking the budget. The next wave of AI won’t be won on raw

Richard Socher's Recursive Superintelligence raised 650M+ from GV, Greycroft, Nvidia, AMD, and others at a 4B valuation to pursue 'recursive self-improvement' (Cade Metz/New York Times)

Cade Metz / New York Times: Richard Socher's Recursive Superintelligence raised 650M+ from GV, Greycroft, Nvidia, AMD, and others at a 4B valuation to pursue “recursive self-improvement” — Recursive S

The Illusion of Power Capping in LLM Decode: A Phase-Aware Energy Characterisation Across Attention Architectures

arXiv:2605.11999v1 Announce Type: cross Abstract: Power capping is the standard GPU energy lever in LLM serving, and it appears to work: throughput drops, power readings fall, and energy budgets are m

To Err Is Human; To Annotate, SILICON? Toward Robust Reproducibility in LLM Annotation

arXiv:2412.14461v4 Announce Type: replace Abstract: Unstructured text data annotation is foundational to management research. LLMs offer a cost-effective and scalable alternative to human annotation,

Transform Video Into Instantly Searchable, Actionable Intelligence with AI Agents and Skills

NVIDIA's video analytics AI agents analyze and process large volumes of video data through natural language tasks to provide critical insights , powered by vision language models, large language model

hardwarenvidia-developer

TriBand-BEV: Real-Time LiDAR-Only 3D Pedestrian Detection via Height-Aware BEV and High-Resolution Feature Fusion

arXiv:2605.12220v1 Announce Type: new Abstract: Safe autonomous agents and mobile robots need fast real time 3D perception, especially for vulnerable road users (VRUs) such as pedestrians. We introduc

AAAC: Activation-Aware Adaptive Codebooks for 4-bit LLM Weight Quantization

arXiv:2605.08692v1 Announce Type: cross Abstract: Post-training weight-only quantization to 4 bits is widely used to reduce the memory and compute costs of large language model inference. Existing PTQ

After studying 300 Leetcode Hards, solving every Jane Street puzzle from the Dwarkesh ads, and watching one Horace He lecture, he finally la…

After studying 300 Leetcode Hards, solving every Jane Street puzzle from the Dwarkesh ads, and watching one Horace He lecture, he finally landed the $400k annualized Jane Street internship. Unfortunat

hardwaredylan-patel--x

CellDX AI Autopilot: Agent-Guided Training and Deployment of Pathology Classifiers

arXiv:2605.10362v1 Announce Type: new Abstract: Training AI models for computational pathology currently requires access to expensive whole-slide-image datasets, GPU infrastructure, deep expertise in

Cluster magicians and GPU whisperers, come join us! We’re looking for supercomputing engineers to build the infrastructure behind real-time …

hardwaresoumith-chintala--x

Cluster magicians and GPU whisperers, come join us! We’re looking for supercomputing engineers to build the infrastructure behind real-time interactive models, Tinker, and large-scale training: schedu

CME Group and Silicon Data announce a futures market for computing capacity, with contracts based on daily GPU benchmarks for on-demand rental rates (Tobias Burns/CNBC)

Tobias Burns / CNBC: CME Group and Silicon Data announce a futures market for computing capacity, with contracts based on daily GPU benchmarks for on-demand rental rates — A new futures market for sem

Did Jensen Huang catch conflict of interest disease from Sam?

Did Jensen Huang catch conflict of interest disease from Sam? HUANG FOUNDATION SIGNS GPU COMPUTE DEAL WITH COREWEAVE $NVDA proxy says the charitable foundation tied to Jensen and Lori Huang entered an

hardwaregary-marcus--x

Efficient Dataset Distillation for Pre-Trained Self-Supervised Models via Statistical Flow Matching

arXiv:2602.05391v2 Announce Type: replace Abstract: Dataset distillation seeks to synthesize a highly compact dataset that achieves performance comparable to the original dataset on downstream tasks.

Energy Consumption of Dataframe Libraries for End-to-End Deep Learning Pipelines:A Comparative Analysis

arXiv:2511.08644v3 Announce Type: replace-cross Abstract: This paper presents a detailed comparative analysis of the performance of three major Python data manipulation libraries - Pandas, Polars, and

FlashSVD v1.5: Making Low-Rank Transformers Inference Actually Fast

arXiv:2605.08314v1 Announce Type: cross Abstract: SVD-based Low-rank compression reduces transformer parameters and nominal FLOPs, but these savings often translate poorly into real LLM serving speedu

Forcing-KV: Hybrid KV Cache Compression for Efficient Autoregressive Video Diffusion Models

arXiv:2605.09681v1 Announce Type: new Abstract: Autoregressive (AR) video diffusion models adopt a streaming generation framework, enabling long-horizon video generation with real-time responsiveness,

Geometric 4D Stitching for Grounded 4D Generation

arXiv:2605.09984v1 Announce Type: cross Abstract: Recent 4D generation methods complete scene-level missing information using generative models and reconstruct the scene into radiance-based representa

GPU-Accelerated Synthesis of Mixed-Boolean Arithmetic: Beyond Caching

arXiv:2605.08243v1 Announce Type: cross Abstract: Synthesizing Mixed-Boolean Arithmetic (MBA) expressions from input-output examples is central to program deobfuscation and also useful for compiler op

Leveraging LLMs to Automate Energy-Aware Refactoring of Parallel Scientific Codes

arXiv:2505.02184v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used for generating parallel scientific codes, with a primary focus on generating functionally correct

mHC-SSM: Manifold-Constrained Hyper-Connections for State Space Language Models with Stream-Specialized Adapters

arXiv:2605.08300v1 Announce Type: cross Abstract: Manifold-Constrained Hyper-Connections (mHC) introduce a stability-motivated variant of multi stream residual mixing by constraining residual stream m

Model-Aware Tokenizer Transfer

arXiv:2510.21954v2 Announce Type: replace Abstract: Large Language Models (LLMs) are trained to support an increasing number of languages, yet their predefined tokenizers remain a bottleneck for adapt