Search: “hardware”

B9008 is a build release of llama.cpp from May 2, 2026. Llama.cpp is a C/C++ implementation of LLM inference designed to enable large language model inference with minimal setup and high performance a

Build b9009 is an incremental release of llama.cpp from May 2026, continuing the rapid development cycle that characterized April 2026's updates with tensor parallelism, 1-bit quantization, and expand

b9010 is a build release of llama.cpp, an open-source project for LLM inference in C/C++ . As a numbered build tag in the llama.cpp release system, it represents a specific development build containin

arXiv:2211.06762v2 Announce Type: replace Abstract: Omnidirectional micro aerial vehicles (OMAVs) are more capable of doing environmentally interactive tasks due to their ability to exert full wrenche

arXiv:2604.27089v1 Announce Type: new Abstract: Large-language-models (LLMs) demonstrate enormous utility in long-context tasks which require processing prompts that consist of tens to hundreds of tho

arXiv:2604.27092v1 Announce Type: new Abstract: Scientific research has long been human-led, driving new knowledge and transformative technologies through the continual revision of questions, methods

arXiv:2604.27807v1 Announce Type: new Abstract: The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by

arXiv:2604.27969v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are increasingly used to translate visual artifacts into code, from UI mockups into HTML to scientific plots

arXiv:2604.27643v1 Announce Type: cross Abstract: Integrated Circuit (IC) verification consumes nearly 70% of the IC development cycle, and recent research leverages Large Language Models (LLMs) to au

arXiv:2604.27206v1 Announce Type: new Abstract: Semantic segmentation in remote sensing is commonly addressed using classical deep learning architectures such as U-Net, which require a large number of

arXiv:2604.27032v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become an integral part of many real-world workflows. However, LLMs consume a lot of energy, which becomes a large c

arXiv:2604.26979v1 Announce Type: cross Abstract: In-memory computing (IMC) enables energy-efficient neural network inference by computing analog matrix-vector multiplications (MVM) in memory crossbar

A user reported experiencing a false positive from their vehicle's driver monitoring system, which incorrectly detected their eyes as closed when they were actually open, prompting a humorous reaction

arXiv:2604.28197v1 Announce Type: cross Abstract: Human-robot collaboration has been studied primarily in dyadic or sequential settings. However, real homes require multiadic collaboration, where mult

arXiv:2511.17176v2 Announce Type: replace-cross Abstract: Accurate prediction of extreme weather events remains a major challenge for artificial intelligence-based weather prediction systems. While de

arXiv:2506.08332v3 Announce Type: replace Abstract: Machine learning has been widely used to optimize complex engineering workflows across numerous domains. In integrated circuit design, modern flows

arXiv:2604.27721v1 Announce Type: cross Abstract: This paper presents a physically-informed fuzzy clustering of vertical sounding ionograms for automatically separating the ionogram into tracks suitab

arXiv:2604.27193v1 Announce Type: new Abstract: Automatic Emergency Braking (AEB) systems represent a safety-critical national interest, with the National Highway Traffic Safety Administration (NHTSA)

A seasoned developer seeking advice on selecting an Apple product to locally host large language models in the 27-36 billion parameter range, discussing the trade-offs and specifications of different

arXiv:2504.18902v2 Announce Type: replace-cross Abstract: In the forthcoming era of 6G networks, characterized by unprecedented data rates, ultra-low latency, and ubiquitous connectivity, effective ma

The search did not return specific details about release b8982. Based on the llama.cpp project context from the search results, b8982 is a build/release version from the llama.cpp repository that foll

b8983 is a release of llama.cpp, a C/C++ implementation for LLM inference. The release represents a specific build/commit version in the active development of the llama.cpp project, which supports run

B8984 is a build/release version of llama.cpp, an open-source C/C++ library for large language model inference. Llama.cpp enables LLM inference with minimal setup and state-of-the-art performance on a

Release b8987 of llama.cpp updates cpp-httplib to version 0.43.2 . This is a minor maintenance release from the llama.cpp project, which provides C/C++ inference for large language models. The release

b8992 is a build release from the llama.cpp project, which publishes multiple releases in a single day . llama.cpp enables LLM inference with minimal setup and state-of-the-art performance on a wide r

Welcome to the second Cloud CISO Perspectives for April 2026. Today, Francis deSouza, COO Google Cloud and President, Security Products, explains why Google is multicloud and multi-AI, straight from N

arXiv:2604.26920v1 Announce Type: new Abstract: The task of capturing and rendering 3D dynamic scenes from 2D images has become increasingly popular in recent years. However, most conventional cameras

arXiv:2510.26841v2 Announce Type: replace-cross Abstract: Federated Learning (FL) enables collaborative model training without data sharing, yet participants face a fundamental challenge, e.g., simult

arXiv:2604.26294v1 Announce Type: new Abstract: We present tensor and sequence parallelism (TSP), a parallel execution strategy that folds tensor parallelism and sequence parallelism onto a single dev

arXiv:2509.23410v4 Announce Type: replace-cross Abstract: Large language models (LLMs) deliver impressive performance but incur prohibitive memory and compute costs at deployment. Model pruning is an

arXiv:2604.26039v1 Announce Type: cross Abstract: The optimal kernel configuration for Mixture-of-Experts (MoE) inference depends on both batch size and the expert routing distribution, yet production

arXiv:2604.26582v1 Announce Type: cross Abstract: Reliable celestial attitude determination is a critical requirement for autonomous spacecraft navigation, yet traditional 'Lost-in-Space' (LIS) algori

arXiv:2507.12549v4 Announce Type: replace Abstract: While machine learning has advanced through massive parallelization, we identify a critical blind spot: some problems are fundamentally sequential.

These folks are trying to ban open source. They're looking to take away your freedom to choose. They're also looking to take away the rights of businesses like Cursor to fine tune and make their produ

arXiv:2508.07852v2 Announce Type: replace-cross Abstract: Recent research on learnable neural representations has been widely adopted in the field of 3D scene reconstruction and neural rendering appli

b8969 is a release build of llama.cpp (commit bdc9c74), published on April 29, 2026. Llama.cpp is a C/C++ implementation designed to enable LLM inference with minimal setup and state-of-the-art perfor

b8972 is a release of llama.cpp, a C/C++ implementation for LLM inference . The release identifier follows llama.cpp's development versioning scheme with frequent builds published to the GitHub releas

b8973 is a release of llama.cpp that added SVE tuned code for the gemm_q8_0_4x8_q8_0() kernel and changed arrays to static const in repack.cpp . The llama.cpp project enables LLM inference with minima

arXiv:2604.25176v1 Announce Type: new Abstract: The digitization of multi-domain retail billing documents remains a challenging task due to variability in scan quality, layout heterogeneity, and domai

arXiv:2512.12087v3 Announce Type: replace Abstract: The growing demand for long-context inference capabilities in Large Language Models (LLMs) has intensified the computational and memory bottlenecks

OpenAI outlines the computational infrastructure requirements and strategies necessary to support advanced AI systems in the emerging Intelligence Age. The piece likely discusses scaling challenges, h

arXiv:2604.24912v1 Announce Type: cross Abstract: We introduce HAML (Hamiltonian Adaptation via Meta-Learning), a framework for fast online adaptation of effective Hamiltonian models of superconductin

arXiv:2604.25073v1 Announce Type: new Abstract: Deploying machine learning models under production constraints requires joint optimization over model family, quantization scheme, runtime backend, and

Wen-Yee Lee / Reuters: Filing: TSMC sold its remaining 1.11M Arm shares at 207.65 per share for a total of ~231M this week; TSMC invested ~100M in Arm's 2023 IPO at 51 per share — Taiwan Semiconductor

arXiv:2604.25067v1 Announce Type: cross Abstract: Forecasting when AI systems will become capable of meaningfully accelerating AI research is a central challenge for AI safety. Existing benchmarks mea

arXiv:2604.24827v1 Announce Type: new Abstract: Closed-source frontier labs do not disclose parameter counts, and the standard alternative -- inference economics -- carries 2imes+ uncertainty from har