Knowledge catalogue
arXiv:2608.00859v1 Announce Type: new Abstract: Kolmogorov--Arnold Networks (KANs) replace scalar edge weights with learnable univariate functions parameterized by multiple basis coefficients. This in
arXiv:2608.01615v1 Announce Type: cross Abstract: We present a set of tools for mapping general stochastic programs to thermodynamic hardware designed for energy-efficient stochastic sampling. Given a
I've been out of these forums for awhile but I figured I would provide a formal update on how this has been going now that it has some operation time under its belt, just to put the information out th
Ran DeepSeek V4-Flash-0731 — the full official checkpoint, not a re-quant — on commodity used hardware. Sharing because I couldn't find anyone else publishing Ampere results for this engine. Why bothe
arXiv:2607.28848v1 Announce Type: cross Abstract: LLM serving systems are provisioned for peak load to meet strict latency targets, leaving substantial GPU compute idle whenever traffic falls below pe
A combined architecture using KAI Scheduler and vCluster enables multiple teams to run fully isolated Kubernetes tenant clusters on a shared GPU node, each with its own control plane, RBAC, CRDs, and
arXiv:2607.28633v1 Announce Type: cross Abstract: Disaggregated LLM inference creates a datacenter networking problem that no existing system solves correctly. When prefill and decode run on separate
Vivid depiction of a dark scenario for Nvidia. “Indeed, CEO Jensen Huang has been so aggressive in funding the AI ecosystem that the company is functioning almost like a bank; with annual free cash fl
The article shows that dense‑attention performance in long‑context inference is governed by group size (query heads per KV head), head dimension, and sequence length, with prefill being compute‑bound
arXiv:2607.28416v1 Announce Type: new Abstract: Curved tactile fingertips for dexterous manipulation must resolve fine contact geometry, distinguish normal and tangential loads, and capture transient
arXiv:2607.27231v1 Announce Type: cross Abstract: Large language models (LLMs) have significantly increased the demand for efficient accelerator kernels, but kernel development remains a highly specia
arXiv:2607.28422v1 Announce Type: new Abstract: Fault-tolerant quantum computing (FTQC) relies on quantum error correction to suppress physical errors and preserve logical information at scale. In pra
arXiv:2607.28418v1 Announce Type: cross Abstract: Pruning is a promising approach for improving the efficiency of LLMs. Existing static structured pruning methods are hardware-friendly and can deliver
NVIDIA **nvmath‑python v1.0** is a Python library that wraps CUDA‑X and NVPL math libraries (cuFFT, cuBLASLt, cuDSS, cuSPARSE, cuTENSOR, cuBLASMp) to give NumPy, CuPy, and PyTorch users GPU‑accelerate
arXiv:2607.25593v1 Announce Type: new Abstract: Robotic hardware evolves over time, but demonstration data is often tied to a specific sensor and actuator configuration. This raises a practical and un
arXiv:2607.24148v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated strong potential for embodied AI, yet their high inference latency on GPUs limits real-time deploy
arXiv:2607.24741v1 Announce Type: cross Abstract: Dynamic applications, including optimal-transport Flow Matching, repeatedly solve related entropic optimal transport problems, yet conventional distri
arXiv:2607.24313v1 Announce Type: cross Abstract: Marine life monitoring is limited by strict energy constraints, poor underwater connectivity, and the high cost of transmitting raw multimodal data fr
arXiv:2607.22869v1 Announce Type: cross Abstract: Monte Carlo tree search (MCTS) enables artificial intelligence (AI) decision-making, but requires 55-300 W on conventional processors, limiting edge d
arXiv:2607.22714v1 Announce Type: cross Abstract: Real-time perception is a foundational requirement for advanced driver assistance systems (ADAS) and autonomous vehicles, yet embedded automotive plat
arXiv:2607.23389v1 Announce Type: cross Abstract: Conventional CAPTCHAs pose puzzles that modern AI systems increasingly solve, while behavioral and cryptographic-attestation defenses carry privacy or
arXiv:2607.21927v1 Announce Type: new Abstract: Full self-attention in large language models scales as O(N^2), which limits long-context document analysis to 65,536 tokens and requires costly GPU clus
AMD’s AI accelerator software stack has progressed sharply, moving from a 0 % chance of catching Nvidia’s CUDA moat in early 2025 to a “great chance” of success by July 2026 after leadership changes a
arXiv:2607.20940v1 Announce Type: new Abstract: Streaming video diffusion models have made substantial progress toward interactive and dynamic world simulation, but the nested autoregressive and denoi
arXiv:2607.21553v1 Announce Type: new Abstract: We introduce SANA-Video 2.0, a hybrid video diffusion transformer instantiated at 5B and 14B scales under a unified architecture. Designed to generate h
Advanced Micro Devices Inc. is pushing harder than ever to grab even more market share from Nvidia Corp. in the artificial intelligence chip industry. At its Advancing AI 2026 event today in San Franc
arXiv:2607.18349v1 Announce Type: new Abstract: Objective: To develop a low-cost automated cataract severity classification system operating on standard consumer-grade colour photographs of the eye, w
arXiv:2607.19490v1 Announce Type: cross Abstract: Peer-to-peer distributed inference executes a Large Language Model (LLM) on pooled consumer hardware by spreading its layers across many nodes. Every
arXiv:2607.19661v1 Announce Type: cross Abstract: Several edge computing platforms, such as autonomous vehicles and smart sensing devices, need to adapt to dynamic environments in real time by learnin
arXiv:2607.19456v1 Announce Type: cross Abstract: We derive four memory-optimal inference artifacts for transformer attention using the Mathematics of Arrays (MoA), each following directly from the fo
The NVIDIA GB300 NVL72 platform set a world record by delivering 1,648 TFLOPs per GPU during the pre‑training of DeepSeek‑V3 671B, a mixture‑of‑experts (MoE) model. This achievement leveraged fifth‑ge
The first Vera Rubin clusters are here! Yesterday, @IneffableLabs took delivery of their Vera Rubin NVL72 cluster from @googlecloud @nvidia The AI frontier jumps forward by yet another generation of h
NVIDIA’s sixth‑generation NVLink is a purpose‑built scale‑up network that delivers up to 3.6 TB/s per GPU and 260 TB/s rack‑level bandwidth with 130 TFLOPS in‑network compute—outperforming off‑the‑she
arXiv:2607.13808v1 Announce Type: new Abstract: Recent extensions of 3D Gaussian Splatting (3DGS) capture fine color details using hash-grid-based appearance parameterization but incur high computatio
BREAKING: Dylan Patel (@dylan522p) of @SemiAnalysis_ says 'chips in Europe have less seasoning than chips in America & Mexico.' Plus: › Data centers & France’s nuclear power › AI infrastructure over-o
arXiv:2304.03388v2 Announce Type: replace Abstract: Deep Neural Networks (DNNs) have become ubiquitous for their ability to solve problems across various domains, including computer vision, natural la
arXiv:2607.06922v1 Announce Type: cross Abstract: Deep learning applications have been widely adopted on edge devices, to mitigate the privacy and latency issues of accessing cloud servers. Deciding t
As organizations scale modern workloads — from high-throughput databases and network/security appliances to real-time analytics and AI/ML inference — network and block storage performance can quickly
arXiv:2607.03131v1 Announce Type: cross Abstract: Modern video surveillance systems generate far more video streams than human operators can effectively monitor, making automated analysis essential fo
arXiv:2607.04440v1 Announce Type: cross Abstract: Seismic wavefield simulation is fundamental to seismology, but conventional finite-difference (FD) methods remain limited by numerical dispersion and
arXiv:2607.03012v1 Announce Type: cross Abstract: Video Diffusion Transformers (VDiTs) have demonstrated significant capabilities in high-fidelity video generation. However, their ability to produce l
arXiv:2607.02603v1 Announce Type: cross Abstract: The stable coloring of the Weisfeiler-Leman (1-WL) test is a cornerstone of Graph Neural Networks because it provides an upper bound to the expressive
arXiv:2607.03411v1 Announce Type: cross Abstract: Jamming and spoofing threaten wireless and satellite navigation by disrupting or manipulating radio frequency (RF) signals, undermining availability,
arXiv:2607.04443v1 Announce Type: cross Abstract: We present Wan-Streamer v0.2, a latency-preserving upgrade of the native-streaming, end-to-end audio-visual interaction model. v0.2 keeps the v0.1 mod
183/365 of GPU Programming This 4.5 hour lesson on CUDA + ThunderKittens by @bfspector (TK co-author, Stanford PhD student) is one of the best educational videos on kernels out there (think @karpathy
arXiv:2607.01646v1 Announce Type: new Abstract: State-of-the-art large language model (LLM) training takes tens of thousands of graphics processing units (GPUs) for months and encounters failures acro
arXiv:2607.01409v1 Announce Type: cross Abstract: GPU training jobs fail often, roughly two in five on large production clusters, yet the operator typically learns of a failure only by reconnecting ho
Ahmad Osman stated at AI World's Fair that within 18 months, GLM 5.2-equivalent AI intelligence will be deployable locally on a single RTX 5090 GPU, indicating rapid progress toward running advanced l
arXiv:2606.30949v1 Announce Type: new Abstract: High-Level Synthesis (HLS) provides a fast path from concepts to silicon, but converting real-world software into synthesizable HLS code remains challen
arXiv:2606.30709v1 Announce Type: cross Abstract: Hierarchical Global Attention (HGA) is a drop-in replacement for dense causal attention in pretrained long-context transformers. HGA preserves the ori
America is about to lose the AI race, and it will not happen at the frontier. It will happen at the floor. Everyone is watching who ships the smartest model. The actual war is over the 80% of tokens n
arXiv:2606.26758v1 Announce Type: new Abstract: High-performance GPU kernels are critical for reducing the exponentially growing computational costs of large language models (LLMs), but their developm
NVIDIA's GLM-5.2-NVFP4 is a quantized version of a large language model optimized for inference efficiency using NVIDIA's proprietary quantization format. The model is hosted on Hugging Face and repre
“If there is a deflation of the AI bubble, the optimists say that the new infrastructure will remain even if the companies do not — just as railways survived the 19th-century railway bust. However, th
arXiv:2606.26383v1 Announce Type: cross Abstract: How fast could a deep-learning model run on target hardware, and how far is today's implementation from that limit? These questions are central to sof
arXiv:2606.24369v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a dominant post-training paradigm, driving the emergence of high-performance RL systems such as veRL for autoregr
arXiv:2606.24075v1 Announce Type: cross Abstract: Although deep learning-based methods can achieve high accuracy in automatic modulation recognition (AMR) tasks, their high computational cost makes it
OpenAI and Broadcom announced a collaboration on a specialized inference chip designed to optimize the performance and efficiency of large language model deployments. The chip, referred to as 'Jalapen
arXiv:2606.24039v1 Announce Type: new Abstract: Robotics increasingly relies on GPUs for parallel simulation, large-scale learning, and neural-network inference. For model predictive control (MPC) to
arXiv:2606.22939v1 Announce Type: cross Abstract: Radio frequency jamming poses a critical threat to the availability of wireless Industrial Internet of Things (IIoT) networks. Existing detection and