AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Credit: Daniel Schwen The White House has published a new National Security Science and Technology strategy. It names 15 critical technology areas the United States intends to lead. Artificial intelligence and autonomy…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Emma McGrath-CohenReporter Updated Aug 20, 2026 – 3.14pm, first published at 5.00am The computer science lecturer who used artificial intelligence to beat Macquarie University in an industrial relations stoush has a gri…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Published July 29, 2026 | Version v1 Preprint Open Cross-Vendor Semantic Void Matrix Authors/Creators Pal, Rayan (Researcher) Description This preprint reports a frozen cross-vendor evaluation of successful zero-visible…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Domain-Driven Design matters more when AI writes your code August 20, 2026 Miłosz Smółka Co-founder of Three Dots Labs. Creator of Watermill. Author of Go With The Domain. Whatever you think of AI coding, the way we bui…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Updating a side project with AI in 275 commits Home Resume/CV Projects Tech Writing Non-Tech Email benhoyt.com [email protected] Updating a side project with AI in 275 commits August 2026 Recently my employer had its mi…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：← sufiyan.cc plainspeak Make AI agents write like a person, not a bot. You know the voice. Every reply opens with "Certainly!" or "Let's dive in". Em dashes land in every other line. Plainspeak turns that off. What shou…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Discussion | Link

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：I used to watch a lot of TV as a kid. I missed the feeling of watching whatever was airing. So, I made Dabba TV. There are multiple channels. Each channel has a theme and all the content being played is according to the…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Free preview available. Sign in and subscribe to unlock the full book. Vizuara AI Labs · advanced Pretraining a Mini Kimi K3 One H200, five billion tokens, $252.35 — the complete worklog of a Kimi K3 replica trained fro…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Sai Gaddam Apr 30, 2026 Our microschool is four years old now! Well, that was a few months ago but we didn’t really get to sit down and reflect on it, because running it continues to be a giant energy wormhole. It’s a b…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Enterprises are racing to deploy AI agents that pull from databases, document repositories, and SaaS platforms to automate workflows. But a quiet risk lurks beneath the convenience: a compromised agent manipulated via p…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Matthew Yglesias Aug 20, 2026 ∙ Paid A pre-chimney household gathered around an open indoor hearth. (Image created with ChatGPT) I’ve been thinking lately about the question of historical realism in dramatic depictions…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Yes, we’re confused too.

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：New Hy3 gets 8× usage limits for a limited time Low cost coding models for everyone Go brings agentic coding to programmers around the world. Offering generous limits and reliable access to the most capable open-source…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：Max Read Nov 22, 2024 Greetings from Read Max HQ! In this week’s edition, we discuss two recent experiments (one non-scientific, one scientific) comparing A.I.-generated and human fashioned art. A reminder: This newslet…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：With less than three months to go until the midterms, voters are thinking about grocery prices, the Iran war – and datacentres. This week, Jonathan Freedland speaks to the historian Jill Lepore about how this latest AI backlash could influence those all-important elections in November. Are we seeing the beginning of the end of the ‘artificial state’? Listen to the Today In Focus episode on the plans for a new datacentre in London’s Brick Lane Read Jill Lepore’s Long Read here Watch Jonathan Freedland on our new Politics Weekly YouTube channel Send your questions and feedback to [email protected] Continue reading...

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19574v1 Announce Type: new Abstract: World action models jointly predict future visual observations and actions, whereas existing tactile-aware variants typically represent future touch as an image or latent stream without modeling the physical dependencies that organize tactile states hierarchically. We present HiTac-WAM, a hierarchical tactile world action model that forecasts a sequence of future tactile states for each candidate action chunk before execution. The forecast factorizes into contact state, a 3D deformation field, and slip risk, organized as a directed hierarchy in which each downstream stage is conditioned on stop-gradient signals from preceding stages. A directed attention mask allows tactile queries to attend to the video-action co…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19537v1 Announce Type: new Abstract: This paper presents a guide path-free multimodal trajectory planning framework for autonomous surface vehicles operating in dynamic environments. The proposed method integrates model predictive control (MPC) with a turning circle-based control barrier function (TC-CBF). Unlike conventional Euclidean distance-based CBFs (ED-CBFs), which evaluate safety solely based on proximity, the TC-CBF accounts for the nonholonomic motion and finite turning capability of a surface vehicle. Its geometric formulation identifies feasible avoidance regions according to the vehicle's turning circles and generates distinct left- and right-turning avoidance modes. These modes allow the optimization solver to explore and select topolog…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19522v1 Announce Type: new Abstract: Scan-to-map LiDAR odometry drifts unboundedly along the unobservable axes of geometrically degenerate environments like tunnels and corridors, and existing degeneracy handling requires environment-specific parameter tuning. This paper presents a parameter-free approach. We show that in voxelized GICP the Gauss--Newton (GN) Hessian masks translational degeneracy, because covariance regularization keeps the translation block artificially well-conditioned. We bypass this with a regularization-free voxel-normal localizability field and two of its statistics: a normalized fraction $f_0$ detecting directional anisotropy, and an absolute per-voxel mass $\lambda_0$ distinguishing information absence (tunnels) from dilutio…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19490v1 Announce Type: new Abstract: State-of-the-art vision-language-action (VLA) models such as $\pi_{0.5}$ exhibit strong semantic understanding, instruction following and task behavior. However, when deployed on new robots, even minor mismatches in hardware configuration relative to pretraining can cause severe performance drops. Finetuning the VLA on in-domain expert data from the new embodiment improves performance on the expert task but leads to a loss in its original instruction following and behavioral priors. In this paper, we propose a self-supervised method that generates online interaction rollouts from the zero-shot VLA as additional training data for finetuning. Our experiments show this finetuning scheme yields strong multi-task polic…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19453v1 Announce Type: new Abstract: Stream-based robotics Task and Motion Planning (TAMP) integrates discrete symbolic planning with dynamically generated continuous geometric parameters, such as poses, grasps, and trajectories. However, stream-based planners typically reason only about goal reachability, whereas long-horizon tasks also demand adherence to temporal specifications, such as safety-critical ordering, invariance, and liveness constraints. No methods currently exist to enforce such temporal constraints for stream-based solvers because streams generate an expanding geometric object set via iterative stream refinement loops during planning, rendering existing temporal-logic compilation techniques incompatible. We therefore present Synchron…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19443v1 Announce Type: new Abstract: Thanks to its parallelizability and flexibility, sampling-based Model Predictive Control (MPC) has become widely popular for controlling real-world robotic systems. However, for high-dimensional and open-loop unstable dynamical systems, the required number of samples to improve the control sequence will grow exponentially with the horizon, leading to poor sample efficiency and numerical instability. This paper investigates the instability of shooting methods in sampling-based MPC and shows that the optimal sampling proposal distribution can be realized by sampling with an optimized feedback policy. We refer to this algorithm as Feedback Sampling MPC (FS-MPC). FS-MPC involves a hybrid sampling design which balances…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19425v1 Announce Type: new Abstract: Reliable performance evaluation is a central bottleneck for deploying robot-learning policies in real-world conditions. Real-world testing is faithful but costly and difficult to scale, whereas simulation-based testing scales easily but is inevitably biased by the sim-to-real gap. Existing simulation-augmented methods combine limited real-world rollouts with abundant simulation proxies, but focus on performance averaged over initial conditions and deployment settings. Such population-level averages obscure scenario-specific variation and provide limited guidance about when and where a policy can be safely deployed. We propose SCAPE, a scenario-conditioned simulation-augmented policy evaluation framework that predi…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19375v1 Announce Type: new Abstract: High-fidelity embodied AI simulators provide realistic evaluation of complex robotic systems, but their computational cost limits their direct use for large-scale reinforcement learning campaigns. We advocate the use of less accurate but more expeditious simulations, which might draw on data-driven, e.g., neural dynamics, models. This contribution argues that the practical value of a neural dynamics model for complex robot control lies in learning the \emph{right abstraction}: a reduced state that preserves the control-relevant physics of the high-fidelity system while enabling high-throughput policy learning. We develop a neural reduced dynamics (NRD) framework that separates the state the model propagates from w…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19372v1 Announce Type: new Abstract: A fundamental challenge in robotic teleoperation is enabling an operator to control a remote robot as effortlessly and intuitively as their own hands. Despite the growing use of teleoperation to collect demonstration data for training autonomous robot policies, teleoperated robot performance still falls significantly short of human dexterity, even for basic tasks. Here, we present evidence that a key factor contributing to this performance gap is the absence of spatially distributed tactile feedback. Using a two-degree-of-freedom (DoF) bilateral force-feedback telemanipulator paired with a 32-DoF tactile fingertip display, we show that operator performance improves significantly when localized deformations on the…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19281v1 Announce Type: new Abstract: Programming robots remains challenging for non-experts, as traditional methods require expert knowledge and even block-based interfaces often lack flexibility. Recent work has explored Large Language Models (LLMs) to automatically generate robot programs from natural language, but these systems remain limited by a lack of transparency, missing mechanisms to ensure alignment with user intent, and little support for reuse. We present APPROVE (AI-Powered Programming for Robots with Visual End-User Feedback), an LLM-based multi-modal end-user programming framework that integrates natural language input with a block-based interface and an explicit user confirmation step. Generated programs are visualized using a block-…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19553v1 Announce Type: new Abstract: Vision--language models can identify the correct referent while returning an imprecise bounding box. We study whether a frozen direct-answer model can use its own prediction to allocate one additional localized observation without accessing target annotations at inference. Label-free precision refinement (LFPR) routes predicted-small regions to a higher-resolution pass, re-grounds the expression inside a context crop, admits a candidate only under fixed geometric guards, and returns a fixed coordinate-wise midpoint. We report results across three evidence tiers. On 31,921 retrospective Ref-L4 expressions, LFPR raises mAcc$_{0.5:0.95}$ from 72.947\% to 76.013\% ([email protected] 88.531\%$\to$89.725\%, [email protected] 55.788\%$\to$6…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19536v1 Announce Type: new Abstract: Learning-based global point cloud registration has achieved remarkable progress, yet its reliance on geometric representations makes existing methods sensitive to variations in point density, scan pattern, viewpoint, and sensor characteristics. We propose CVSD-Reg, a robust global LiDAR registration framework that distills visual semantic priors from a vision foundation model into LiDAR representations. In Stage 1, a Point Transformer V3 student learns from a frozen DINOv2 teacher through contrastive distillation and spherical-manifold alignment, which preserves the hyperspherical geometry of the teacher embedding space. Self-supervised InfoNCE consistency and soft $\mathrm{SE}(3)$ invariance further encourage vie…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19504v1 Announce Type: new Abstract: We propose a conditioning mechanism for diffusion models based on multi-speed joint diffusion of the target and the condition. The mechanism learns an unconditional joint score network and enforces conditioning at inference via a plug-in correction term. The plug-in term separates the conditioning contribution from the learned unconditional dynamics, offering a transparent view of how the condition steers generation of the target distribution. Building on this, we derive explicit conditional reverse-time SDEs and approximate probability-flow ODEs, enabling principled and directly comparable conditional samplers. To reduce the induced ODE--SDE discrepancy, we introduce a log-Fokker--Planck residual regularization t…

AI 服務暫時不可用，以下為來源摘要，待恢復後補全翻譯：arXiv:2608.19480v1 Announce Type: new Abstract: Human pose estimation has advanced significantly due to the development of deep learning models, increased data availability, and improved computing resources. These developments have led to highly accurate body tracking systems with direct applications in sports analysis and performance evaluation. The VideoRun2D Demo performs a biomechanical analysis during sprints using different human pose estimators. The proposed framework was evaluated using human pose trackers and expert manual annotations. The tested framework uses 314 sprints from 44 professional runners, focusing on two key joint angles in sprint biomechanics: 1) hip flexion/extension and 2) knee flexion/extension. The framework also includes a post-proc…