Knowledge catalogue
arXiv:2604.24331v1 Announce Type: new Abstract: Research on video-based eye-tracking has long explored stereo and glint-based methods, yet existing wearable eye trackers - both commercial and open-sou
B8960 is a build release of llama.cpp, an open-source C/C++ project for running large language models locally with minimal setup and optimized performance across various hardware platforms. It is one
B8963 is a build release of llama.cpp, the C/C++ implementation of LLM inference. Llama.cpp is an open-source project that enables efficient language model execution on consumer hardware with minimal
arXiv:2604.24447v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are promising for generalist robot control, but on-robot deployment is bottlenecked by real-time inference under t
arXiv:2603.10926v1 Announce Type: cross Abstract: Time-series anomaly detectors are commonly compared on workstation-class hardware under unconstrained execution. In-vehicle monitoring, however, requi
arXiv:2509.00747v2 Announce Type: replace-cross Abstract: Learning with physical systems is an emerging paradigm that seeks to harness the intrinsic nonlinear dynamics of physical substrates for learn
arXiv:2604.23205v1 Announce Type: cross Abstract: Deploying proprietary Deep Neural Networks (DNNs) on commodity edge devices demands hardware-backed Digital Rights Management (DRM) capable of withsta
This post documents a technical demonstration of running the large Qwen3.5-397B-A17B model across distributed hardware using llama.cpp with advanced networking protocols. The approach leverages 4-bit
Release b8934 of llama.cpp was released on April 26, 2026, and includes improvements to hexagon hardware support, specifically guarding HMX clock requests for v75+ platforms. The release provides bina
Simon Willison inquires about running DeepSeek-V4-Flash on Mac hardware, specifically asking about feasibility across different RAM configurations from 512GB down to smaller amounts. This reflects dis
b8931 is a release version of llama.cpp published on April 25, 2026 . llama.cpp is an LLM inference framework in C/C++ that enables running large language models efficiently on various hardware. The r
r/LocalLLaMA is a subreddit community dedicated to discussing and sharing resources about running large language models locally on personal computers, covering topics like model optimization, hardware
The Qwen 3.6-27B and 35B models are designed as open-weight models that developers can run locally on their own hardware without requiring cloud services. Alibaba released a separate cloud-only produc
B8924 is a release build number from the llama.cpp project, a C/C++ framework for efficient large language model inference on consumer hardware. The llama.cpp project publishes multiple releases in a
Cloud-hosted models will become more niche/seldom-used as much cheaper local models fulfill that which 90% of consumers need from AI. Lots of models to buy/use, but very few hardware options upon whic
arXiv:2604.21280v1 Announce Type: new Abstract: On-device continual learning (CL) is critical for edge AI systems operating on non-stationary data streams, but most existing methods rely on backpropag
arXiv:2604.21026v1 Announce Type: new Abstract: Deploying large language models to heterogeneous hardware is often constrained by memory, not compute. We introduce MCAP (Monte Carlo Activation Profili
arXiv:2604.21231v1 Announce Type: cross Abstract: Efficient inference for on-device Large Language Models (LLMs) remains challenging due to limited hardware resources and the high cost of the prefill
B8902 is a release build of llama.cpp, an open-source C/C++ framework for running large language model inference on consumer hardware with minimal dependencies. As an intermediate build release from t
arXiv:2407.09577v4 Announce Type: replace Abstract: Normalization layers are ubiquitous in large language models (LLMs) yet represent a compute bottleneck: on hardware with distinct vector and matrix
arXiv:2604.19832v1 Announce Type: cross Abstract: In a global derivatives market with notional values in the hundreds of trillions of dollars, the accuracy and efficiency of pricing models are of fund
Hugging Face and AMD have collaborated to quantize the Kimi-K2.6 model to MXFP4 format, enabling efficient inference on AMD hardware. MXFP4 is a low-precision floating-point quantization technique tha
b8882 is a release of llama.cpp, a C/C++ implementation for LLM inference . The project follows a rapid release cycle with frequent updates to support multiple hardware architectures and platforms. Th
llama.cpp is a C/C++ implementation that enables LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware locally and in the cloud. Release b8884 is a build/versio
arXiv:2505.16968v4 Announce Type: replace-cross Abstract: Cross-architecture GPU code transpilation is essential for unlocking low-level hardware portability, yet no scalable solution exists. We intro
arXiv:2602.12851v3 Announce Type: replace-cross Abstract: Deploying expressive learning models directly on programmable dataplanes promises line-rate, low-latency traffic analysis but remains hindered
Flux 2-Klein-9B NVFP4 is a quantized image generation model that runs on mid-range GPUs like the RTX 3050. On this hardware, the model produces 1024-resolution images but with relatively slow inferenc
This article explores the implementation of Internet of Things technology in manufacturing environments, covering strategic approaches, key hardware and software components, practical applications acr
Today at Google Cloud Next, we’re announcing new capabilities in Google Distributed Cloud (GDC) that bring Gemini and our advanced AI stack to wherever your data is, so you don’t need to compromise be
arXiv:2508.18025v4 Announce Type: replace-cross Abstract: Autonomous planetary exploration demands real-time, high-fidelity environmental perception. Standard deep learning models require massive comp
arXiv:2604.17277v1 Announce Type: new Abstract: Physical neural networks offer a transformative route to edge intelligence, providing superior inference speed and energy efficiency compared to convent
arXiv:2604.17862v1 Announce Type: new Abstract: As deep learning-based AI technologies gain momentum, the demand for general-purpose AI computing architectures continues to grow. While GPGPU-based arc
arXiv:2604.18001v1 Announce Type: new Abstract: Super-resolution (SR) models are attracting growing interest for enhancing minimally invasive surgery and diagnostic videos under hardware constraints.
Release b8859 is a version of llama.cpp, an open-source project that enables LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware. The llama.cpp project uses a
arXiv:2604.15638v1 Announce Type: new Abstract: Continuum robots are well suited for navigating confined and fragile environments, such as vascular or endoluminal anatomy, where contact with surroundi
arXiv:2604.15388v1 Announce Type: cross Abstract: Recent advances in large language models have improved code generation, but their use in hardware description languages is still limited. Moreover, tr
IBM Quantum's Q1 2026 updates likely cover recent advances in quantum computing hardware, software, and applications, including announcements about processor improvements, new quantum algorithms, or e
b8840 is a release version of llama.cpp, a C/C++ implementation for large language model inference. This release build includes compiled binaries and updates for various platforms and hardware acceler
Ollama is a local model-serving engine that enables users to run large language models on their own hardware without relying on cloud services. The post appears to highlight Ollama's integration with
The European Space Agency's Rosalind Franklin Mars rover finally secured its launch mission when NASA approved the ROSA project in April 2026, providing launch vehicle and hardware support to the ESA-
b8832 is a recent build release of llama.cpp from April 17, 2026 . Llama.cpp is a C/C++ implementation for running large language model inference efficiently on consumer hardware with minimal setup. T
arXiv:2604.15272v1 Announce Type: cross Abstract: This paper presents Prism, the first symbolic superoptimizer for tensor programs. The key idea is sGraph, a symbolic, hierarchical representation that
arXiv:2604.13251v1 Announce Type: new Abstract: Analog optical computers promise large efficiency gains for machine learning inference, yet no demonstration has moved beyond small-scale image benchmar
llama.cpp is a C/C++ library for LLM inference that enables running large language models on consumer hardware. Release b8814 is a specific version in the project's continuous release cycle, which fol
arXiv:2604.12765v1 Announce Type: new Abstract: Marker-based motion capture (MoCap) systems have long been the gold standard for accurate 4D human modeling, yet their reliance on specialized hardware
arXiv:2602.11236v2 Announce Type: replace-cross Abstract: Building general-purpose embodied agents across diverse hardware remains a central challenge in robotics, often framed as the ''one-brain, man
Speculative decoding is a technique used to accelerate the slow, sequential token generation (decode stage) in LLM inference. This method significantly reduces latency and improves hardware utilizatio
This r/StableDiffusion Reddit thread discusses community recommendations for photorealistic image generation models that can run within a 16GB VRAM constraint, a common hardware limit for consumer GPU
Build b8790 is an incremental automated release of llama.cpp, the open-source C/C++ library for efficient LLM inference on local hardware. Like other builds in the project's continuous release cycle,
arXiv:2604.11535v1 Announce Type: new Abstract: Solving an NP-hard optimization problem often requires reformulating it for a specific solver -- quantum hardware, a commercial optimizer, or a domain h
As the fifth annual World Quantum Day gets underway on April 14, researchers say the focus of their efforts is shifting from hardware experimentation to integrating quantum systems into broader comput
arXiv:2604.11465v1 Announce Type: new Abstract: Large language model (LLM) agents show promise on realistic tool-use tasks, but deploying capable agents on modest hardware remains challenging. We stud
arXiv:2507.04736v2 Announce Type: replace Abstract: Large Language Models have emerged as powerful tools for automating Register-Transfer Level (RTL) code generation, yet they face critical limitation
LogLens with local AI 'Ollama' is a Reddit post on r/ollama discussing the integration of LogLens — a log analysis tool — with Ollama to perform AI-powered log inspection entirely on local hardware, w
Starlink Mini is a compact, portable version of SpaceX's Starlink satellite internet hardware designed for mobile and on-the-go connectivity. It offers high-speed internet access in a smaller, more tr
arXiv:2604.09048v1 Announce Type: cross Abstract: While the large energy consumption of Large Language Models (LLMs) is recognized by the community, system operators lack guidance for energy-efficient
This r/ollama Reddit thread addresses a common question among the local AI community about whether reliable, self-hosted AI systems are genuinely achievable. Community members in this space typically
KIV is a project shared on r/MachineLearning presenting a drop-in replacement for HuggingFace's `DynamicCache` that enables up to 1 million token context windows on consumer hardware with only 12GB of
A Reddit thread on r/StableDiffusion where a user reports poor output quality when using the ACE-Step 1.5 XL SFT model variant for AI music generation. The SFT (Supervised Fine-Tuning) variant of ACE-
llama.cpp release **b8752** is a tagged build of the [ggml-org/llama.cpp](https://github.com/ggml-org/llama.cpp) project — a C/C++ framework for efficient LLM inference on a wide range of hardware....