Search: “hardware”

I let Gemma4-31b run on my laptop for like almost a day using a heavily altered pi to do a deep dive on our beloved Llama tangentially related Subreddit, and this was the conclusion. Feels pretty accu

arXiv:2607.26661v1 Announce Type: new Abstract: Ascend C operator optimization is critical for NPU (Neural Processing Unit) inference performance but requires deep hardware expertise.While large langu

arXiv:2504.03772v3 Announce Type: replace-cross Abstract: Respiratory diseases account for a significant portion of global mortality. Affordable and early detection is an effective way of addressing t

arXiv:2607.20162v1 Announce Type: new Abstract: The growing demand for intelligent processing at the edge of IoT networks is constrained by the severe computational and memory limitations of microcont

arXiv:2607.14021v1 Announce Type: new Abstract: Dexterous manipulation remains a critical bottleneck in industrial automation; tasks such as cable routing, connector insertion, and precision assembly

arXiv:2607.13897v1 Announce Type: new Abstract: The broadcast nature of wireless channels exposes radio-frequency (RF) networks to anomalous and malicious transmissions, making anomaly detection a fun

arXiv:2607.06915v1 Announce Type: new Abstract: Scaling down the resolution of input images can greatly reduce the computational overhead of convolutional neural networks (CNNs), which is promising fo

arXiv:2607.02753v1 Announce Type: cross Abstract: Neuromorphic controllers for size, weight, and power-constrained systems require neural architectures that are both energy-efficient and interpretable

OpenAI is releasing some sort of device related to its AI-powered coding tool, Codex, on July 15th. In a video posted to X on Monday, OpenAI shows a square-shaped device with several buttons, alongsid

Protecting sensitive data used with AI is a critical part of our commitment to providing advanced and secure cloud infrastructure. Confidential Computing cryptographically protects data in use in hard

arXiv:2606.21868v1 Announce Type: new Abstract: Modern Mixture-of-Experts (MoE) models place most of their parameters in expert layers, yet only a small fraction of those experts are used for any toke

arXiv:2605.26118v1 Announce Type: cross Abstract: Porting deep learning algorithms to new hardware accelerators requires developers to repeatedly apply the same low-level optimizations -- quantization

arXiv:2605.09848v1 Announce Type: new Abstract: Electrocardiogram (ECG) interpretation is essential for diagnosing a wide range of cardiac abnormalities. While deep learning has shown strong potential

arXiv:2505.13741v2 Announce Type: replace Abstract: Direct training of Spiking Neural Networks (SNNs) on neuromorphic hardware can greatly reduce energy costs compared to GPU-based training. However,

Less than a year ago, Apple made headlines for a lack of AI announcements at its annual WWDC event. Ten months later, the company has announced that hardware executive John Ternus will succeed longtim

arXiv:2603.07053v2 Announce Type: replace Abstract: Scientists face significant visualization challenges as time-varying datasets grow in speed and volume, often requiring specialized infrastructure a

arXiv:2604.02811v2 Announce Type: replace-cross Abstract: Functional verification consumes over 50% of the IC development lifecycle, where SystemVerilog Assertions (SVAs) are indispensable for formal

The math behind reinforcement learning (RL) post-training for large language models (LLMs) is notoriously unforgiving. As frontier AI labs push the boundaries of reasoning and coding models using RL p

arXiv:2606.10294v1 Announce Type: cross Abstract: Deploying neural networks on unconventional hardware demands architectures that co-optimize task accuracy and platform-specific constraints such as en

arXiv:2510.16028v4 Announce Type: replace-cross Abstract: Neural networks increasingly run on hardware outside the user's control (cloud GPUs, inference marketplaces). Yet ML-as-a-Service reveals litt

arXiv:2602.07518v2 Announce Type: replace-cross Abstract: Kolmogorov-Arnold Networks (KANs) shift neural computation from linear layers to learnable nonlinear edge functions, but implementing these no

arXiv:2605.07782v1 Announce Type: new Abstract: LLMs can generate hardware descriptions from natural language specifications, but the resulting Verilog often contains width mismatches, combinational l

arXiv:2604.24492v1 Announce Type: cross Abstract: Designing deep networks that meet strict latency and accuracy constraints on edge accelerators increasingly relies on hardware-aware optimization, inc

Apple announced that Tim Cook will step down as CEO on September 1, 2026, ending his 15-year tenure, with John Ternus, the senior vice president of hardware engineering, succeeding him as chief execut

Securing infrastructure and services against a future cryptographically-relevant quantum computer has been a goal for Google for a decade, and we’ve dedicated ourselves to help developers by advancing

This article from SemiAnalysis tracks the performance evolution of DeepSeek V4, a 1.6 trillion parameter model, over its first 43 days of training on Huawei and NVIDIA hardware including GB300 NVL72,

arXiv:2606.01339v1 Announce Type: cross Abstract: Long-term time-series forecasting needs models that are accurate yet efficient enough for commodity hardware. Lightweight linear forecasters are remar

arXiv:2512.01678v5 Announce Type: replace Abstract: Graph Neural Networks (GNNs) present a fundamental hardware challenge by fusing irregular, memory-bound graph traversals with regular, compute-inten

torch-nvenc-compress is a Python library that leverages GPU NVENC (NVIDIA's hardware video encoding) to optimize PCIe bandwidth utilization by compressing data during transfer. The project implements

John Gruber / Daring Fireball: Tim Cook reshaped Apple in his own image and exits as CEO on his own terms, seemingly picking the right successor in John Ternus, much like Jobs did with Cook — It's a p

arXiv:2604.10306v1 Announce Type: new Abstract: As Earth-observation workloads move toward onboard and edge processing, remote-sensing segmentation models must operate under tight latency and energy c

Editor’s note: This blog post outlines Google Cloud’s GPU AI/ML infrastructure reliability strategy, and will be updated with links to new community articles as they appear. As we enter the era of mul

I'm trying to figure out GPU Kernel optimization on older hardware like SM80(ampere) . Is there tools you guys use? Or frameworks? Im waiting for this framework https://www.reddit.com/r/LocalLLaMA/com

arXiv:2603.10711v3 Announce Type: replace Abstract: Real-time solution of nonlinear optimal control problems remains challenging on embedded robotic hardware, where conventional solvers often rely on

arXiv:2608.04173v1 Announce Type: new Abstract: Deep neural networks (DNNs) deployed on resource-constrained neuromorphic hardware face three concurrent challenges: the need for model compression thro

arXiv:2608.02606v1 Announce Type: new Abstract: Fault tolerance in classical computing has traditionally relied on static strategies like hardware redundancy and error-correcting codes. Biological sys

arXiv:2608.02229v1 Announce Type: new Abstract: Classical neural networks frequently produce overconfident predictions on ambiguous or out-of-distribution (OOD) data, a liability that grows with each

It's more accurate to say that many highly engaged online gamers are hostile to AI, not that 'gamers' as a whole are. Gaming is a huge community with hundreds of millions of people, and opinions vary

arXiv:2607.29266v1 Announce Type: cross Abstract: Artificial Intelligence (AI) and Deep Learning (DL) have notably advanced medical image analysis, yet many health- care organizations struggle to adop

Written by: Kelli Vanderlee, Stuart Carrera For years, the cybersecurity industry's understanding of software supply chain compromise has been anchored by a few watershed events, including Russian cyb

arXiv:2607.26855v1 Announce Type: new Abstract: Many scientific fields rely on standard benchmarks and shared platforms to improve review and reproducibility, but autonomous systems research still lac

AI hardware competition entered a sharper phase this week as Advanced Micro Devices Inc. used its flagship AI event to argue it isn’t merely chasing Nvidia Corp. — it intends to lead the market outrig

Devin Outposts are now available on NVIDIA Brev. Write and profile kernels, run experiments, serve and fine-tune OSS models, and test against real hardware. Try it out: https://brev.nvidia.com/launcha

Run Devin Outposts on @nvidia Brev to give Devin access to GPU infrastructure for debugging training runs, inspecting GPU state, reproducing failures, and validating fixes on the hardware where the wo

CUDA 13.3 introduces **clmad**, a hardware‑accelerated carryless multiply‑accumulate instruction available on all NVIDIA Ampere and newer GPUs (SM 80+), filling a long‑standing gap in GPU‑native binar

Integrated circuit and electronic hardware design company Cadence Design Systems Inc. today announced a new artificial intelligence agent that assists with packaging and system design, the step after