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as a side note, young people seem to prefer to interact with AI via voice, and old people, and people in the middle like to type. i wonder i…

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

industrysam-altman--x

Content type

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Agents

As agentic AI moves on-prem, Intel puts hardware trust at the center of enterprise security

DGX agent

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

agentssiliconangle

7 May 2026

Assessing Cognitive Effort in L2 Idiomatic Processing: An Eye-Tracking Dataset

model-releasesarxiv-cs-cl

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

AsymmetryZero: A Framework for Operationalizing Human Expert Preferences as Semantic Evals

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

Tutorials

Attention-Based Chaotic Self-Supervision for Medical Image Classification

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

tutorialsarxiv-cs-cv

Attention Sinks Induce Gradient Sinks: Massive Activations as Gradient Regulators in Transformers

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

Automated Formal Proofs of Combinatorial Identities via Wilf-Zeilberger Guidance and LLMs

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

Automated Large-scale CVRP Solver Design via LLM-assisted Flexible MCTS

model-releasesarxiv-cs-ai

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

Automatically Finding and Validating Unexpected Side-Effects of Interventions on Language Models

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

applicationsarxiv-cs-cl

Agents

Autonomous Laparoscope Control through Unified Mechanics-Based Representation of Multimodal Intraoperative Information

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

agentsarxiv-cs-ro

Available now on local and 1-2 hours on cloud 🫡

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

local-aicomfyui--x

Average Attention Transformers and Arithmetic Circuits

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

Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation

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

researcharxiv-cs-cl

AWS and Atlassian reframe AI as an organizational challenge, not an IT one

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

applicationssiliconangle

AWS unveils Amazon Bedrock AgentCore Payments and partners with Coinbase and Stripe to enable AI agents to execute transactions using stablecoins (RT Watson/The Block)

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

industrytechmeme

AxMoE: Characterizing the Impact of Approximate Multipliers on Mixture-of-Experts DNN Architectures

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

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

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

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

b9058

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

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

b9061

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

b9063

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

b9066

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

Back to Blackwell: Closing the Loop on Intransitivity in Multi-Objective Preference Fine-Tuning

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

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

industryelon-musk--x

Balanced Aggregation: Understanding and Fixing Aggregation Bias in GRPO

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

safetyarxiv-cs-cl

Bayesian Parameter Shift Rule in Variational Quantum Eigensolvers

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

model-releasessimon-willison

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

Benchmarking LLMs on the Massive Sound Embedding Benchmark (MSEB)

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

Benchmarking POS Tagging for the Tajik Language: A Comparative Study of Neural Architectures on the TajPersParallel Corpus

model-releasesarxiv-cs-cl

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

BenCSSmark: Making the Social Sciences Count in LLM Research

model-releasesarxiv-cs-cl

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

Beyond Exponential Decay: Rethinking Error Accumulation in Large Language Models

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

researcharxiv-cs-cl

Beyond Fixed Thresholds and Domain-Specific Benchmarks for Explainable Multi-Task Classification in Autonomous Vehicles

arXiv:2605.04299v1 Announce Type: new Abstract: Scene understanding is a vital part of autonomous driving systems, which requires the use of deep learning models. Deep learning methods are intrinsical

safetyarxiv-cs-cv

Beyond Public Access in LLM Pre-Training Data

arXiv:2505.00020v2 Announce Type: replace Abstract: Using a legally obtained dataset of 34 copyrighted O'Reilly Media books, we apply the DE-COP membership inference attack method to investigate wheth

safetyarxiv-cs-cl

Beyond Rigid Geometries: The Spline-Pullback Metric for Universal Diffeomorphic SPD Representation Learning

arXiv:2605.04406v1 Announce Type: new Abstract: The integration of Symmetric Positive Definite (SPD) matrices into deep learning has historically relied on fixed algebraic Riemannian metrics. Analogou

Beyond Semantics: An Evidential Reasoning-Aware Multi-View Learning Framework for Trustworthy Mental Health Prediction

arXiv:2605.05121v1 Announce Type: new Abstract: Automated mental health prediction using textual data has shown promising results with deep learning and large language models. However, deploying these

applicationsarxiv-cs-cl

Beyond Variance: Prompt-Efficient RLVR via Rare-Event Amplification and Bidirectional Pairing

arXiv:2602.03452v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) is effective for training large language models on deterministic outcome reasoning tasks. Prio

Tools

Big Words

Tool: Big Words I'm using my vibe coded macOS presentations tool to put together a talk, and I wanted to add a slide with some text on it. The tool only accepts URLs, so I put together a quick page th

toolssimon-willison

Bilinear Mamba-Koopman Neural MPC for Varying Dynamics

arXiv:2605.04793v1 Announce Type: new Abstract: Koopman-based neural MPC models generate time-varying dynamics from historical data, but preserve convexity by enforcing that the system operator is ind

Block raises 2026 outlook after first-quarter earnings beat, accelerating gross profit growth

Shares of Block Inc. rose more than 8% in late trading today after the financial services company beat earnings expectations, accelerated gross profit growth and raised its full-year outlook on the ba

industrysiliconangle

Block reports Q1 revenue up 5% YoY to 6.1B, vs. 5.9B est., and raises its 2026 gross profit forecast above estimates; XYZ jumps 7%+ after hours (Isabelle Lee/Bloomberg)

Isabelle Lee / Bloomberg: Block reports Q1 revenue up 5% YoY to 6.1B, vs. 5.9B est., and raises its 2026 gross profit forecast above estimates; XYZ jumps 7%+ after hours — Block Inc. offered a sunnier

industrytechmeme

BOOOM: Loss-Function-Agnostic Black-Box Optimization over Orthonormal Manifolds for Machine Learning and Statistical Inference

arXiv:2605.04087v1 Announce Type: cross Abstract: Optimization over the Stiefel manifold St(p,d), the set of p imes d column-orthonormal matrices, is fundamental in statistics, machine learning, and s

Brainrot: Deskilling and Addiction are Overlooked AI Risks

arXiv:2605.03512v1 Announce Type: cross Abstract: The scope of AI safety and alignment work in generative artificial intelligence (GenAI) has so far mostly been limited to harms related to: (a) discri

safetyarxiv-cs-ai

Breaking the Quality-Privacy Tradeoff in Tabular Data Generation via In-Context Learning

arXiv:2605.04911v1 Announce Type: new Abstract: Tabular data synthesis aims to generate high-quality data while preserving privacy. However, we find that existing tabular generative models exhibit a c

applicationsarxiv-cs-lg

Bridging Input Feature Spaces Towards Graph Foundation Models

arXiv:2605.04834v1 Announce Type: new Abstract: Unlike vision and language domains, graph learning lacks a shared input space, as input features differ across graph datasets not only in semantics, but

Bridging Modalities: Joint Synthesis and Registration Framework for Aligning Diffusion MRI with T1-Weighted Images

arXiv:2601.11689v2 Announce Type: replace-cross Abstract: Multimodal image registration between diffusion MRI (dMRI) and T1-weighted (T1w) MRI images is a critical step for aligning diffusion-weighted

researcharxiv-cs-cv

Hardware

Budget-aware Auto Optimizer Configurator

arXiv:2605.04711v1 Announce Type: cross Abstract: Optimizer states occupy massive GPU memory in large-scale model training. However, gradients in different network blocks exhibit distinct behaviors, s

hardwarearxiv-cs-lg