Knowledge catalogue
Emma Roth / The Verge: Microsoft reports Q3 Xbox hardware revenue fell 33% YoY and Xbox content and services revenue, which includes Game Pass, dropped 5% YoY — Xbox hardware revenue took a 33 percent
arXiv:2604.19993v1 Announce Type: cross Abstract: Complex-Valued Neural Networks (CVNNs) have significant advantages in handling tasks that involve complex numbers. However, existing CVNNs are unable
arXiv:2409.07609v2 Announce Type: replace-cross Abstract: Deploying adversarially robust machine learning systems requires continuous trade-offs between robustness, cost, and latency. We present an au
CNBC: John Ternus, senior VP of Hardware Engineering, will become Apple's next CEO on September 1; Tim Cook will become executive chairman of Apple's board — Apple said on Monday that John Ternus is s
arXiv:2604.12079v1 Announce Type: cross Abstract: Traditional machine learning depends on high-precision arithmetic and near-ideal hardware assumptions, which is increasingly challenged by variability
arXiv:2604.12891v1 Announce Type: new Abstract: Deep learning (DL) compilers rely on cost models and auto-tuning to optimize tensor programs for target hardware. However, existing approaches depend on
arXiv:2604.09565v1 Announce Type: cross Abstract: This paper introduces a unified, hardware-independent baremetal runtime architecture designed to enable high-performance machine learning (ML) inferen
This Reddit thread from r/ollama features a user seeking community recommendations for motherboard, CPU, and RAM components to build a system optimized for running Ollama locally without a dedicated G
(1/5) FP4 hardware is here, but 4-bit attention still kills model quality, blocking true end-to-end FP4 serving. To fix that, we propose Attn-QAT, the first systematic study of quantization-aware trai
arXiv:2609.17491v1 Announce Type: new Abstract: Unauthorized hardware replacement can preserve a wireless device's logical identity while altering its physical implementation, posing a challenge to ha
arXiv:2603.12440v2 Announce Type: replace-cross Abstract: GPU kernel optimization challenges LLMs beyond standard coding tasks, as it requires an understanding of hardware architecture, parallel compu
We all want more tokens per second but I keep seeing confusion on what to expect for given hardware. For the decoding phase (TG/s) to produce one token all the model weights and KV cache needs to be r
Today, we're kicking off the first phase of the research preview for Model Hardware Standard (MHS): a new standard for AI agents to safely operate physical equipment in scientific research and advance
arXiv:2608.25570v1 Announce Type: new Abstract: Hardware kernel optimization requires repeated compilation, correctness testing, profiling, and revision. LLM agents can automate parts of this process,
One of the things I like most about Ollama is how low it makes the barrier to experimenting with local models. The downside is that once you move away from high-end hardware, finding the right informa
arXiv:2608.14709v1 Announce Type: cross Abstract: This demo presents real-time AI-based uplink channel-estimation inference using data collected from a hardware-in-the-loop 5G platform. The data-colle
arXiv:2608.02671v1 Announce Type: cross Abstract: Malware detection using Hardware Performance Counters (HPC) has emerged as a promising solution to improve the security of computing systems as a comp
arXiv:2607.26464v1 Announce Type: cross Abstract: Physical Unified Device Architecture (PUDA) is an AI-native hardware harness for self-driving laboratories (SDLs). Rather than building a human-center
arXiv:2607.01660v1 Announce Type: new Abstract: Hardware impairments in massive multiple-input multiple-output (MIMO) receivers introduce inter-symbol memory and inter-element coupling, severely degra
arXiv:2607.01590v1 Announce Type: new Abstract: Developing high-performance kernels for Neural Processing Units (NPUs) is a critical industry bottleneck, requiring developers to manually navigate impl
arXiv:2606.29636v1 Announce Type: cross Abstract: An important task in quantum computing is unitary circuit synthesis compatible with physical hardware constraints. This problem has a natural hybrid s
arXiv:2512.05402v2 Announce Type: replace-cross Abstract: Bitcoin mining hardware acquisition requires strategic timing due to volatile markets, rapid technological obsolescence, and protocol-driven r
arXiv:2605.04282v1 Announce Type: new Abstract: Visual SLAM is a core component of spatial computing systems, yet deploying learned local feature extractors on microcontroller-class hardware remains c
arXiv:2604.27911v1 Announce Type: new Abstract: Foundation models are deep neural networks (such as GPT-5, Gemini~3, and Opus~4) trained on large datasets that can perform diverse downstream tasks --
300,000 AI builders have already added their hardware to HF to instantly see what model they can run locally. To do so, go to https://huggingface.co/settings/local-apps and add your hardware specs. Yo
arXiv:2511.12340v2 Announce Type: replace Abstract: Efficient machine learning deployment requires models that account for hardware constraints. Because binary logic gates are the fundamental primitiv
arXiv:2604.14709v2 Announce Type: replace Abstract: Existing benchmarks for hardware design primarily evaluate Large Language Models (LLMs) on isolated, component-level tasks such as generating HDL mo
arXiv:2610.07026v1 Announce Type: new Abstract: The Offline AI Modules workstream enables practical, low-power, and community-accessible deployment of voice-first AI systems that operate fully offline
arXiv:2512.04705v3 Announce Type: replace-cross Abstract: The deployment of Early-Exiting Neural Networks (EENNs) on edge accelerators requires optimizing not only the network architecture but also it
arXiv:2610.00207v1 Announce Type: cross Abstract: Due to limited support for intra-tensor heterogeneous precision in conventional accelerators, neural network quantization remains largely restricted t
Agentic artificial intelligence-powered hardware systems design platform Flow Engineering Inc. announced Wednesday it has raised 50 million in early-stage funding to change how engineers develop and i
arXiv:2609.36134v1 Announce Type: new Abstract: Functional Kolmogorov-Arnold Networks (FunKAN) achieve state-of-the-art accuracy on MRI Gibbs artifact removal and anatomical segmentation, but their 11
arXiv:2609.37107v1 Announce Type: new Abstract: We present Waypoint 1.5, a real-time diffusion world model for interactive video generation on consumer-grade hardware. Unlike general video diffusion m
arXiv:2609.35587v1 Announce Type: new Abstract: GPU libraries such as CUTLASS expose tens of thousands of semantically equivalent kernels for a single operation, making exhaustive autotuning expensive
Delos Data Inc., a startup that develops hardware for artificial intelligence clusters, has raised more than 100 million in funding. The capital was provided by Matrix, Playground, Socratic Partners,
arXiv:2609.13551v1 Announce Type: new Abstract: Static-image benchmarks do not capture the computational and temporal requirements of practical orchard video analytics. This study presents an end-to-e
arXiv:2601.08856v3 Announce Type: replace-cross Abstract: Unit tests are critical in the hardware design lifecycle to ensure that component design modules are functionally correct and conform to the s
arXiv:2608.09914v1 Announce Type: cross Abstract: Hardware assurance relies on scanning electron microscopy (SEM) to verify nanoscale structures, but assembling the large, high-quality datasets requir
arXiv:2608.01648v1 Announce Type: new Abstract: Hardware error logs in high-performance computing (HPC) systems provide early signals of abnormal behavior, yet there remain challenges in effectively f
arXiv:2607.26016v1 Announce Type: cross Abstract: Recently, photonic transformer accelerators (PTAs) have successfully achieved significant speedup and energy efficiency improvements over electronic a
OpenAI is finally releasing some hardware. No, it isn't the mysterious AI-powered device the company is developing with former Apple designer Jony Ive, a project already tangled up in a messy lawsuit.
arXiv:2607.06760v1 Announce Type: new Abstract: Autonomous systems under partial observability act on beliefs, not raw sensor events. QANTIS treats the quantum processor as a calibrated belief-update
arXiv:2607.04531v1 Announce Type: cross Abstract: Low-precision neural networks are attractive for resource-constrained hardware, but fixed-point arithmetic introduces failure modes that are often hid
arXiv:2606.28279v1 Announce Type: cross Abstract: We present HORIZON, a self-evolving agent framework that treats hardware design as repository-level code evolution. A Markdown harness is compiled int
arXiv:2606.27612v1 Announce Type: cross Abstract: Silicon photonics enables integration of optical components using standard semiconductor processes, greatly improving data communication bandwidth and
This IBM Research article discusses optimizing AI inference performance and costs by leveraging mixed hardware configurations, combining different types of processors and accelerators rather than rely
arXiv:2606.12112v1 Announce Type: new Abstract: This paper presents the design, development, and experimental verification of PEBRE, an open-hardware add-on for fast software development on the Pepper
arXiv:2606.07666v1 Announce Type: cross Abstract: Noisy intermediate-scale quantum (NISQ) processors are entering an early fault-tolerance regime where full quantum error correction carries prohibitiv
arXiv:2511.07046v4 Announce Type: replace-cross Abstract: Deploying continuous-control reinforcement learning policies on embedded hardware requires meeting tight latency and power budgets. Small FPGA
arXiv:2605.17653v1 Announce Type: cross Abstract: Sub-billion-parameter Transformer language models are increasingly deployed on edge devices, where the privacy, latency, and operating-cost advantages
arXiv:2506.00982v3 Announce Type: replace Abstract: Deep multi-agent reinforcement learning (MARL) has been demonstrated effectively in simulations for multi-robot problems. For autonomous vehicles, t
arXiv:2601.15127v3 Announce Type: replace-cross Abstract: Deploying federated learning across heterogeneous IoT device fleets requires tailored neural network architectures for each device class, yet
arXiv:2605.01931v1 Announce Type: cross Abstract: Channel estimation is crucial in 5G communication networks for optimizing transmission parameters and ensuring reliable, high-speed communication. How
A Reddit post in the r/ollama community seeking volunteers with diverse hardware setups to participate in a collaborative effort to benchmark the **behavioral reliability** of locally-run large langua
arXiv:2610.10580v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being integrated into hardware verification to automate specification interpretation, verification-artif
Aisha Malik / TechCrunch: AI hardware startup Natura unveils Interface, a 99 smart ring that connects to AI agents and apps, including Claude, ChatGPT, Muse, Grok Bot, and Instinct — Meet Interface, a
arXiv:2610.09274v1 Announce Type: new Abstract: The Visual Geometry Grounded Transformer (VGGT) marks a significant leap forward in 3D scene reconstruction, as it is the first model that directly infe
When Sakeena Fiza describes her work as a validation engineer at NVIDIA, she does so in terms more befitting a detective story than a world-class engineering lab. “Validation engineers look in the sha
arXiv:2609.21114v1 Announce Type: new Abstract: Robots carrying out tasks in dark environments need to localize from a single RGB camera, in light so low that the per-pixel signal approaches the senso
arXiv:2609.19189v1 Announce Type: cross Abstract: Design verification remains one of the most resource-intensive stages of hardware development, often consuming up to 70% of the total design effort. W