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Gary Marcus corrected a previous statement about power consumption, clarifying that the figure was 300 megawatts rather than 30 megawatts. This appears to be a technical correction posted on X regardi

Apple dominate local inference 6/10 This is completely opposite to enterprise/data-center adoption where Nvidia is king. Huge market Nvidia is letting slip. High VRAM + mid bandwidth + working kernels

Apple's rumored AirPods with cameras are nearing a stage where the company will test early mass production, Bloomberg's Mark Gurman reports. Currently, Apple testers are 'actively using' prototypes th

arXiv:2605.04177v1 Announce Type: new Abstract: As LLMs enter conflict monitoring, understanding systematic distortions in their outputs is critical for humanitarian accountability. We evaluate four v

arXiv:2605.04098v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have demonstrated promise on publicly available dermatology benchmarks. However, benchmark performance may not

arXiv:2605.03149v1 Announce Type: new Abstract: Humans typically use natural language to update teammates on task states. Since not all updates are communicated, discrepancies arise between the team m

arXiv:2605.03042v1 Announce Type: cross Abstract: This report describes ARIS (Auto-Research-in-sleep), an open-source research harness for autonomous research, including its architecture, assurance me

arXiv:2605.03117v1 Announce Type: cross Abstract: Repository-level fault localization (FL) and automated program repair (APR) require an agent to identify the relevant code units across files, follow

Simon Sharwood / The Register: Arm expects the AGI CPU, its own AI chip for data centers, to drive 2B in sales in FY2027 and FY2028, doubling its March 2026 sales guidance for the period — Someone oth

arXiv:2605.04225v1 Announce Type: cross Abstract: Coordinating multi-agent systems over spatially distributed areas requires solving a complex hierarchical problem: first distributing areas among agen

Shares of Arm Holdings plc surprisingly lost ground in extended trading today after the chip design firm reported fourth-quarter financial results that surpassed Wall Street’s expectations. Arm also r

arXiv:2603.25956v2 Announce Type: replace Abstract: Time-series anomaly detection (TSAD) is a critical component in monitoring complex systems, yet modern deep learning-based detectors are often highl

arXiv:2603.00492v2 Announce Type: replace Abstract: Per-scene optimization methods such as 3D Gaussian Splatting provide state-of-the-art novel view synthesis quality but extrapolate poorly to under-o

Sam Altman notes an observed generational preference pattern in AI interaction methods, where younger users tend to favor voice interfaces while older and middle-aged users prefer typing. The post app

AI factory security begins at the hardware layer — a fact that is taking on new urgency as enterprises scramble to secure the infrastructure powering the next computing era. The rise of agentic AI and

arXiv:2605.04857v1 Announce Type: new Abstract: This paper presents the development and validation of an eye-tracking dataset designed to investigate how second-language (L2) learners process idiomati

arXiv:2605.04083v1 Announce Type: new Abstract: Much of the focus in RL today is on evaluation design: building meaningful evals that serve simultaneously as benchmarks and as well-defined reward sign

arXiv:2605.04985v1 Announce Type: new Abstract: Deep learning models for medical image classification usually achieve promising results but typically rely on large, annotated datasets or standard tran

arXiv:2603.17771v2 Announce Type: replace Abstract: Attention sinks and massive activations are recurring and closely related phenomena in Transformer models. Existing explanations have largely focuse

arXiv:2605.04472v1 Announce Type: new Abstract: Automating formal proofs of combinatorial identities is challenging for LLM-based provers, as long-horizon proof planning is required and unconstrained

arXiv:2605.03339v1 Announce Type: new Abstract: Solving large-scale CVRP (LSCVRP) with hundreds to thousands of nodes remains difficult for even state-of-the-art solvers. Divide-and-conquer can scale

arXiv:2605.05090v1 Announce Type: new Abstract: We present an automated, contrastive evaluation pipeline for auditing the behavioral impact of interventions on large language models. Given a base mode

arXiv:2605.04408v1 Announce Type: new Abstract: Laparoscope-holding robots can provide surgeons with a stable laparoscopic field of view (FOV) and reduce the burden on human assistants. To maintain an

ComfyUI announced the availability of a feature or service that can be accessed locally immediately and on cloud infrastructure with a 1-2 hour latency or deployment time. This post likely refers to a

arXiv:2605.04683v1 Announce Type: cross Abstract: We analyse the computational power of transformer encoders as sequence-to-sequence functions on vectors. We show that average hard attention can be us

arXiv:2605.04128v1 Announce Type: cross Abstract: We present JoyAI-Image, a unified multimodal foundation model for visual understanding, text-to-image generation, and instruction-guided image editing

Enterprises racing to achieve true AI-native status are discovering that the technology gap is often the smaller obstacle. Instead, the harder challenge is reshaping the people, processes and organiza

RT Watson / The Block: AWS unveils Amazon Bedrock AgentCore Payments and partners with Coinbase and Stripe to enable AI agents to execute transactions using stablecoins — Quick Take — Amazon Web Servi

arXiv:2605.04754v1 Announce Type: new Abstract: Deep neural network (DNN) inference at the edge demands simultaneous improvements in accuracy, computational efficiency, and energy consumption. Approxi

B9050 is a release build of llama.cpp, an open-source C/C++ project that enables LLM inference with minimal setup and high performance on diverse hardware platforms. The project provides LLM inference

B9055 is the latest version of llama.cpp, released on May 7, 2026. Llama.cpp is an LLM inference framework implemented in C/C++ that enables efficient large language model execution with broad hardwar

b9056 is a release of llama.cpp, a C/C++ implementation for LLM inference . The project enables users to run LLaMA models on consumer hardware without expensive GPUs or cloud infrastructure . This rel

I was unable to find specific details about the b9058 release. Based on the context, b9058 is a build version from the llama.cpp project, which is an open source software library that performs inferen

b9060 is a release build identifier for llama.cpp, an open-source LLM inference framework implemented in C/C++. This build represents a snapshot in the project's ongoing development, containing bug fi

Release b9061 is a build version of llama.cpp, a C/C++ implementation designed to enable LLM inference with minimal setup and state-of-the-art performance across various hardware platforms . As a spec

Release b9063 is a build of llama.cpp, a project for LLM inference in C/C++. llama.cpp enables efficient large language model execution on consumer hardware through optimized implementations and quant

llama.cpp b9066 is a release of a C/C++ implementation for large language model (LLM) inference . Based on the release repository structure, b9066 represents a specific build or commit version of the

arXiv:2602.19041v2 Announce Type: replace Abstract: A recurring challenge in preference fine-tuning (PFT) is handling extit{intransitive} (i.e., cyclic) preferences. Intransitive preferences often ste

Badass tank that beats your sports car in a drag race Only when you drive the Cybertruck do you realize how incredible it is: a bulletproof tank that moves like a million dollar sports car! Reason for

arXiv:2605.04077v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a central paradigm for improving reasoning and code generation in large language mode

arXiv:2502.02625v2 Announce Type: replace Abstract: Parameter shift rules (PSRs) are key techniques for efficient gradient estimation in variational quantum eigensolvers (VQEs). In this paper, we prop

Behind the Scenes Hardening Firefox with Claude Mythos Preview Fascinating, in-depth details on how Mozilla used their access to the Claude Mythos preview to locate and then fix hundreds of vulnerabil

arXiv:2605.04556v1 Announce Type: cross Abstract: The Massive Sound Embedding Benchmark (MSEB) has emerged as a standard for evaluating the functional breadth of audio models. While initial baselines

arXiv:2605.04576v1 Announce Type: new Abstract: This paper presents the first benchmark for the task of automatic part-of-speech (POS) tagging for the Tajik language. Despite the existence of multilin

arXiv:2605.04886v1 Announce Type: new Abstract: This position paper argues that the under-representation of social science tasks in contemporary LLM benchmarks limits advances in both LLM evaluation a

arXiv:2505.24187v2 Announce Type: replace Abstract: The prevailing assumption of an exponential decay in large language model (LLM) reliability with sequence length, predicated on independent per-toke