AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：AI capabilities | Trump’s judgment | Gardening attire | Death in English literature | Tautologies | Nominative determinism AI may be capable of “taking over the entire internet” (OpenAI boss and Elon Musk back calls to put brakes on ‘reckless’ AI development, 13 September), but it is rubbish at tackling the Guardian cryptic crossword. John Hougham Reading, Berkshire • Donald Trump is downplaying the dangers of AI (Trump facing AI backlash in Congress as push for guardrails intensifies, 15 September). But didn’t he say much the same thing about Covid? Garry Wynne Norley, Cheshire Continue reading...
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Exclusive: Correspondence requests state MP Melissa Horne to lobby on NextDC’s behalf – but contains alleged AI-created errors Get our breaking news email, free app or daily news podcast The Victorian jobs minister has accused one of Australia’s largest datacentre companies of using artificial intelligence while requesting she lobby her colleague to approve a massive expansion of its “hyperscale AI factory”. Correspondence between Victorian cabinet minister Melissa Horne and the chief executive of ASX-listed company NextDC, Craig Scroggie, reveals increasing sensitivity to community concerns about datacentres before the state election. Continue reading...
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：The rise of AI-generated tributes and bots for ‘talking’ to the dead has experts concerned more people will grieve in isolation Tributes rolled in after the death of Dolly Parton last month. Jack White performed Jolene at a London gig. Kesha sang Old Flames (Can’t Hold a Candle to You), a single her mother wrote for the country music titan. Even Pitbull stopped his Madison Square Garden show to memorialize Parton and all the other “powerful women” in the crowd. But one of the strangest – and most viral – eulogies did not come from a celebrity. It did not even come from a person. Run Jolene, at just under five minutes, is an earworm of a country song, containing all the cliches of the genre: twangy singer, banjo licks, corny lyrics. Those lyrics conc…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Across the US, anti-datacenter organizers are harnessing community anger to win local elections After four months of teach-ins and canvassing, Steven Kung helped Monterey Park, just east of Los Angeles, become the first US city to ban datacenter construction. Now, the organizer is running for city council – and he’s taking on an incumbent who supported the development of the sprawling facility. “The datacenter coming to my neighborhood turned my life upside down,” said Kung. “I saw that there’s a dismantling of democracy at a local level.” Continue reading...
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：President has dismissed anxieties over AI’s dangerous potential even as Democrats and some Republicans acknowledge risks Donald Trump is facing a rare backlash from the US Congress as Democrats and some Republicans push for guardrails on the world’s most powerful AI companies. Concerns over the dangerous potential of AI reached fever pitch this week after tech leaders sounded the alarm over the rapid advancement of the technology and its potential threat to humanity. Continue reading...
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：A series of figures in the tech world have been warning about – and even resigning over – the existential threat posed by artificial intelligence. How worried should we be? Today in Focus host Annie Kelly speaks with technology editor Robert Booth Continue reading...
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Beijing hits back after Anthropic CEO calls for US to impede China’s progress in AI China has dismissed what it said were “fearmongering” calls for the US to block Beijing’s AI industry, even as the top Chinese spy chief warned the evolving technology could threaten Communist party rule. The US tech entrepreneur and Anthropic chief executive, Dario Amodei, wrote an essay published over the weekend that called for a global slowdown in AI capabilities, but also said Washington should actively impede Beijing’s advancement in order to keep a technological edge. Continue reading...
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：The characters are dead-eyed waxworks which speak with all the nuance of a satnav. But this AI-created workplace comedy is so bad that even the greatest actors alive couldn’t stop it being unwatchable As you will no doubt be aware, one Anthropic researcher claimed there is a greater than one in 10 chance that AI will end all of humanity as we know it within the next decade. However, now that I’ve given it some thought, I think this statistic might actually be a little conservative. This is because I have just watched an episode of a sitcom created by AI, and if I ever have to do it again I’m genuinely going to die of boredom. The show is No Big Deal, and it premiered on YouTube on Friday. I was apparently only the 376th person to watch it. This is b…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：A mathematical shape famous for covering a surface without ever repeating has revealed an unexpected ability to twist light into unusual chiral patterns. The discovery could lead to new ways of controlling light, polarization, and advanced optical devices.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Three frontier labs have now said out loud that their models help build their models. The interesting part is not the percentage. It is which half of the job got automated, and why.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Is the current furore in mathematics the canary in the coalmine for experimental science and knowledge work? This post was originally published in Vanishing Gradients on September 11, 2026. It’s been updated to address the subsequent declaration by 25 Fields Medalists and the debate about AI, mathematical progress, and research incentives. Science without understanding? “For […]
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：From Stephen Hawking to Jacob Coxon’s viral Anthropic resignation, fears that AI could threaten humanity have shaken the industry without stopping its pursuit Before an Anthropic researcher resigned and declared human extinction imminent last week, tech leaders and scientists had sounded the alarm about a superintelligent AI ending humanity for over a decade. The development of artificial intelligence “could spell the end of the human race”, warned professor and astrophysicist Stephen Hawking in 2014 – a little less than a decade before the public got its hands on the generative AI features of the original version of ChatGPT. Continue reading...
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Meta engineering team introduced ZGateway, a proxy tier that now sits between client applications and ZippyDB, the Meta’s most widely used key value store. ZippyDB backs product metadata, counters, and configuration at billions of operations per second. ZGateway started as a fix for connection sprawl across more than a million client hosts and grew into […] The post Meta Introduces ZGateway: A Stateless Proxy Tier That Unifies ZippyDB Traffic and Handles Over 1 Billion Operations Per Second appeared first on MarkTechPost.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13289v1 Announce Type: new Abstract: Achieving high-speed locomotion in quadrupedal robots remains highly challenging, as actuators operate near their physical limits and exhibit pronounced nonlinearities. However, many existing methods neglect actuator nonlinearities and physical constraints during training, leading to a significant sim-to-real gap under highly dynamic motions and limiting achievable performance. To address this issue, we propose a high-speed locomotion framework that reduces sim-to-real discrepancies and stabilizes learning over a wide command distribution. A refined actuator model explicitly captures high-speed voltage coupling and magnetic saturation, enabling a more accurate representation of the torque-speed envelop…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13270v1 Announce Type: new Abstract: In distributed model predictive control for multi-drone collision avoidance, a fixed prediction horizon forces a compromise: a short horizon is inexpensive but reacts late to approaching neighbors, whereas a long one anticipates conflicts at a per-step cost that grows superlinearly with its length. We propose a conflict-predictive variable horizon that each drone sets locally, leaving the distributed model predictive control itself unchanged. From a short history of observed positions, a drone extrapolates the flight lines of its neighbors, tests each against its own using confidence funnels that narrow with prediction range, and obtains each time to conflict in closed form. The horizon is then the sma…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13244v1 Announce Type: new Abstract: We study dark manipulation: after a brief lit Write encodes z0 = Enc(rgb), a policy pi(z) and open-loop dynamics f(z,a) complete contact-rich skills without further pixels (dark_f). On ManiSkill StackCube (n=160; seed packs 0/1000), dark_f attains 68.1% stacked on the five-rung chain (near_A -> grasped -> lifted -> on_B -> stacked), compared with 35.6% for per-step lit_reenc and 0% for freeze/encode_black. On a shared Write->HOLD protocol (n=40), occlusion and camera-aligned GT contact-neighbor masks drive lit lift from 43% to 0%, while dark_f holds 82.5%; shuffling actions inflates dynamics MSE by ~9.4x; write-time appearance shifts break encoding (night: 0% stacked), yet the same shifts during HOLD l…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13236v1 Announce Type: new Abstract: Humanoid robots are becoming an important part of embodied artificial intelligence, driven by advances in reinforcement learning for locomotion, world models for prediction, and vision-language-action models for general control. However, most of these systems remain static after deployment. A policy is trained offline for a fixed objective and then frozen, even though the tasks, environments, and robot bodies keep drifting over time. An emerging paradigm of self-evolving agents aims to address this problem by allowing systems to improve from their own post-deployment experience. Since most existing studies focus on disembodied software agents, this survey examines how self-evolution changes when an age…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13235v1 Announce Type: new Abstract: Networked manipulation endpoints couple perception to actuation across compute- and bandwidth-limited links, yet commonly exchange dense geometric states optimized for fidelity rather than action outcomes. A stochastic representation is learned with a policy-free, action-conditioned outcome bottleneck: marginal outcome log-loss supplies distortion and a KL term regularizes rate. The construction is motivated by the minimal statistic that preserves the outcome distribution of every admissible action, while the implemented finite model is evaluated as a rate-regularized mixture predictor. The same encoder and outcome head support grasp selection, singleton conformal filtering, active viewpoint selection,…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13245v1 Announce Type: new Abstract: Speculative Jacobi Decoding (SJD) is an important approach for accelerating autoregressive image generation. Although SJD has shown superior performance, recent studies point out that it usually suffers from a token ambiguity issue during token verification but its reason can not be well explained. To figure out this reason, in this paper, we conduct a visualization analysis on vision token and find that different from text tokens, vision tokens generally corresponds to some local, small, and unclear vision details, which means only using single token is difficult to accurately express a certain semantic, thereby causing token ambiguity issue. To this end, we propose a novel Speculative Jacobi Decoding…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13233v1 Announce Type: new Abstract: Thin structures such as tree branches are among the hardest cases for stereo matching: a branch is only a few pixels wide, the background is cluttered, and dense ground truth for real branches is nearly impossible to label by hand. We make three contributions. First, EMCStereo integrates three lightweight attention modules into a PSMNet-style cost-volume backbone: Efficient Multi-scale Attention (EMA) on deep semantic features, a Multi-Scale Fusion block (MSFblock) learning spatial pyramid weights instead of concatenating them, and Coordinate Attention (CoordAtt) on final matching features. Because MSFblock collapses four pyramid branches into one, the modules leave the network 2.0% smaller and add onl…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13413v1 Announce Type: new Abstract: We introduce CVSS-X, a large-scale synthetic speech-to-speech translation corpus that extends CVSS by reversing the translation direction. While CVSS translates from 21 languages into English, CVSS-X enables translation from English into 28 target languages spanning 12 language families. The corpus comprises approximately 240,000 parallel speech pairs per language, totaling over 16,000 hours, eight times larger than CVSS. We provide two variants: CVSS-X-C with two canonical voices per language, and CVSS-X-T with cross-lingual voice cloning, both fully generated. Evaluation shows comparable translation quality to CVSS with consistent performance across typologically diverse languages. Combined with CVSS…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13194v1 Announce Type: new Abstract: A large literature builds physical structure into learned dynamics on the premise that models respecting the underlying physics predict better. We test that premise using exact polynomial invariants recovered from trajectories and canonicalised as reduced Gr\"obner bases over $\mathbb{Q}$. On Acrobot, exactness provides little benefit for prediction: a consistency regulariser reduces algebraic residual while leaving rollout fidelity essentially unchanged, and a shaping potential recovered from a system with a 100% mass error accelerates learning as effectively as the correct potential. Exact canonical invariants instead prove valuable for diagnosis. We develop two procedures: screening, which identifie…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13171v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) use automatic differentiation to impose differential-equation residuals, but good agreement in function values does not necessarily imply accurate derivatives. This paper formulates derivative fidelity as a failure mode of PINNs and tests it with one-dimensional benchmarks. Multilayer perceptrons are trained only on function values for sin(x) and exp(x), while second derivatives obtained by automatic differentiation are evaluated separately. The hypothesis is strengthened by additional tests over training-point density, activation functions, endpoint-dense evaluation, and both L2 and maximum-error diagnostics. The results show that visually accurate function app…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13396v1 Announce Type: new Abstract: Multi-objective Bayesian optimisation (MOBO) is a sample-efficient approach for optimising expensive black-box functions with multiple objectives. In MOBO, the goal is to adequately approximate the Pareto front; that is, to obtain a high-quality solution set with 1) good convergence (closeness to the Pareto front) and 2) good diversity (spread across the Pareto front). Existing MOBO methods typically aim to accomplish these two tasks simultaneously, i.e., driving the search towards the Pareto front while maintaining a diverse set of nondominated solutions, such that the solutions, ideally, can gradually approach the entire front. When sufficient search budgets are available, this approach is effective.…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Sakana AI researchers Jeffrey Seely and Julian Gould introduce Augmented Lagrangian Predictive Coding (PC-ALM), a local-learning alternative to backpropagation. By attaching a Lagrange multiplier to each layer constraint, PC-ALM keeps predictive coding's layer-local updates while recovering exact backprop gradients in linear networks. It matches BP across widths and depths from 8 to 128 at an inference budget of T = 2L, lifts gradient cosine to BP from 0.604 to 0.909 in the reference cell, and trains 1000-layer residual MLPs within about 2 points of backprop on MNIST. MIT-licensed JAX code is available. The post Sakana AI Researchers Introduce PC-ALM, a Layer-Local Alternative to Backpropagation That Trains 1000-Layer Networks appeared first on Mark…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Christina Koch sits down with James Manyika, Google’s Senior Vice President of Research, Labs, Technology & Society.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Shortly after launching its new do-everything AI assistant Muse, Meta's launching subscription bundles that pair its standalone app subscriptions with extra AI usage. Some of the new Meta One bundles were in testing earlier this year, but are now available globally starting today, with several tiers for individual users, creators, and businesses. Meta says the "core experience" on its apps and Meta AI will still be free, and users can still get its subscriptions for Facebook, Instagram, and WhatsApp without a bundle. It also says it plans to expand the bundles to include "Edits, AI glasses, and more over time." There are two bundles for in … Read the full story at The Verge.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Opal is Google Labs' no-code tool for turning natural language into working AI mini-apps, built on top of an internal framework called Breadboard. Here's how I learned to use it best.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Agent programs in healthcare and life sciences are being built under a different set of constraints than those in most industries. There’s plenty of upside if the constraints can be resolved. Success can mean hours of manual review compressed into minutes, data spread across a dozen systems finally queryable in one place, and clinicians getting time back from documentation. At the same time, the cost of a wrong answer can be higher here than almost anywhere else, which changes how teams build.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：The new SimpliSafe Video Doorbell Series 2 adds 2K resolution and dual band Wi-Fi. | Image: Simplisafe DIY home security company SimpliSafe is bringing its AI-powered proactive security feature to the front door. The new SimpliSafe Video Doorbell Series 2 launches today for $199.99 and works with the company's Active Guard Outdoor Protection (starting at $49.99 a month). This combines AI analysis with live agents to detect potential threats and respond proactively. When the camera detects suspicious activity - using a combination of on-device AI, cloud-based computer vision, and facial recognition - a SimpliSafe monitoring agent can drop in on the camera to "see, speak to, and attempt to deter potential intruders and package thieves," accord … Read…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Cloudflare is giving site owners a way to stay discoverable while disallowing AI training. New controls and an Accountable designation establish a shared model with Apple, Google, and Microsoft.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Explore five free Microsoft GitHub courses covering data science, machine learning, artificial intelligence, generative AI, LLMs, RAG, fine-tuning, and AI agents.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：A year ago, terminal AI mostly meant asking a model to explain errors, generate commands, or edit small functions. In 2026, leading coding CLIs have become full agent runtimes that can inspect repositories, plan work, modify files, run tests, use external tools, and verify results. In this article, we compare five standouts agentic coding CLIs: Claude Code, Codex CLI, […] The post Top 5 Agentic Coding CLI Tools Developers Should Know in 2026 appeared first on Analytics Vidhya.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Children’s Hospital Uses Open Source NVIDIA AI for Cardiac Care | NVIDIA Blog Skip to content Heart of the Matter: How a Major Children’s Hospital Uses Open Source NVIDIA AI for Cardiac Care September 15, 2026 by Isha S…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Agent-net, the team building an agent-to-agent marketplace where AI agents discover, trust, and pay each other, has released Webagent, an open source harness for standing up public-facing business agents. So, basically you give it your website, get an agent, and let it talk to other agents. Instead of writing orchestration code, a business fills in […] The post Agent-net Open Sources Webagent: A Go Harness That Turns Any Website into a Guarded AI Agent appeared first on MarkTechPost.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13240v1 Announce Type: new Abstract: The AffectiveArt Multidimensional Art Emotion Understanding task asks to jointly predict an artwork's fine-grained emotion (12 classes, 1549:1 head-to-tail ratio), binary valence/arousal, and five attribute-grounded descriptions -- sub-tasks that exhibit strong empirical trade-offs, so the single-model solutions we tried do not jointly optimize all of them well. We present ArtSociety, a multi-agent framework that assembles heterogeneous multimodal experts -- a DINOv2-Giant vision agent (A1), a scene-grounded CoT fine-tuned MLLM (A2), and three closed-source reasoning agents (A3-A5) -- and coordinates them with two training-free controllers: (i) a rare-class-aware voting arbiter that lowers the agreemen…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13149v1 Announce Type: new Abstract: For local large language model agents, active context is a scarce resource: memory capacity, prefill latency, cache growth, and service objectives all constrain how many input tokens each call can afford. We present BudgetBench, an active-budget protocol and reference harness that treats the per-call input-token budget as the independent variable when comparing memory strategies. Holding the model, task, sampler, and decoding fixed, it sweeps budgets over 2K, 4K, 8K, 16K, and 32K tokens and records quality, budget utilization, latency, and, as a first-class outcome, budget-violation rates. The core contribution is this reusable measurement surface: a swappable MemoryStrategy contract, explicit budget e…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13463v1 Announce Type: new Abstract: The increasing deployment of AI agents in long-horizon tasks yields massive execution logs. Diagnosing failures within these records is crucial for reliability, as it transforms outcome-level signals into actionable interventions. The sheer scale of the data renders human review impractical, driving the need for automated root-cause attribution (RCA). However, automated RCA methods using LLMs suffer from low diagnostic accuracy, especially as execution traces grow larger. They struggle because relevant information is often sparse, distributed across distant actions, and disconnected from the visible failure, reducing root-cause attribution to a massive search problem. Existing RCA methods typically rel…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13437v1 Announce Type: new Abstract: Scientific research is a continuous process that emphasizes inheritance. Methods developed by predecessors are often expanded upon by new researchers to explore more novel and in-depth scientific questions. However, the change of lab staff, such as student graduation, leads to a lack of personnel capable of replicating methods. Methods that have been developed with significant effort and resources cannot be continued. To address these limitations, we propose LabAgent, a reproduce and discovery harness tailored for a lab's continuous work. LabAgent employs two mechanisms to guarantee that all skills can be executed and verified and to record the corrective methods and experiences, allowing for direct co…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13436v1 Announce Type: new Abstract: Large Language Model (LLM) agents offer a promising path toward autonomously managing long-term physical tasks without human intervention. However, physical tasks require agents to continuously observe the environment, make consequential actions, and remain effective as the environment changes. Existing approaches either require substantial data and retraining, or primarily focus on agents operating in the virtual world. In this work, we explore the feasibility of building a self-adaptive physical AI agent that manages long-term physical tasks in a zero-shot manner and adapts to environmental changes without human intervention. We design a multi-agent framework that integrates planning, tool calling, o…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13422v1 Announce Type: new Abstract: LLM judges are increasingly used to evaluate and improve AI-generated outputs, yet their reliability for complex professional work remains unclear. We study this problem through Vibe Patenting, an end-to-end patent-drafting testbed for AI-agent evaluation. A separately-invoked LLM judge evaluates generated patent drafts and provides structured feedback for iterative revision. Across multiple inventions and drafting-agent configurations, judge-guided revision consistently improves judge-assessed quality, while unguided revision tends to saturate. Notably, iterative judge feedback enables a low-reasoning agent to approach the performance of a substantially more expensive high-reasoning agent. Stronger mo…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13406v1 Announce Type: new Abstract: When we speak of recursive self-improvement (RSI), are we speaking of a phenomenon, a mechanism, or a prospect? Towards autonomous and evolving intelligence, RSI is being claimed at many scales, while no single framework that formally describes these emerging instances exists. Its counterpart in the classical realm, iterative policy improvement, is characterized by generalized policy iteration (GPI), a framework of broad applicability with well-understood theoretical properties, but only where the update principle and the evaluation base lie outside the agent. In this paper, we propose Generalized Agent Iteration (GAI), a formal framework that describes iterative policy improvement and RSI as two cases…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13356v1 Announce Type: new Abstract: In this work, we present ZGCM-1, a fully open 7B dense foundation model trained from scratch with extreme data, system, and algorithmic efficiency. ZGCM-1 is founded on a core premise: compact models cannot passively memorize the open web, but can overcome parametric capacity limits by coupling deliberate internal thinking with active external tool use. To support this paradigm across a 256K context, we develop an end-to-end, high-efficiency open training recipe: Architecture & System Co-design: interleaved gated sliding-window and full attention, and a stable FP8 Muon optimizer; Progressive Curriculum & MDP Mid-Training: context scaling across 16K, 64K, and 256K, and the reformulation of interaction t…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：A practitioner's map of the 3 layers in a modern agent stack, with verified sources and an overlap analysis. The post Agent Harness vs Agent Framework vs MCP: Which Layer Owns the Loop, State, Tools, Permissions, and Recovery appeared first on MarkTechPost.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Learn how Abnormal AI deployed Amazon Bedrock AgentCore Code Interpreter as an ephemeral compute scratch pad for the agents behind its real-time email threat detection at billion-message scale, plus the sandbox design decisions and practical lessons for builders deploying Code Interpreter in production.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Reward AI has released OM-1 (Omnibody Model 1), a general-purpose manipulation policy trained entirely on human demonstrations captured with a 7-DoF wearable glove, with no teleoperation or on-robot data. The policy runs on industrial arms and humanoids at human speed, learns a new task from under 30 minutes of data, and pairs electromagnetic hand tracking (60% lower overshoot than visual-inertial at 67 cm/s) with an RL-trained control layer that runs on its own clock. No weights, code, or API are public yet. The post Reward AI Releases OM-1: A Robot Policy Trained on Human Demonstrations Only, With No Teleoperation or On-Robot Data appeared first on MarkTechPost.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Amazon Bedrock AgentCore Identity now offers a Consent portal, a managed web experience and session binding endpoint for AgentCore Gateway. This post walks through provisioning a portal, configuring GitHub and Slack 3LO targets, and the end-user consent flow, and shows how to review activity in AWS CloudTrail.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要： My comment on What blog posts influenced your thinking the most? — Lobste.rs. An early Joel Spolsky one for me was The Law of Leaky Abstractions. I read that near the start of my career and it's encouraged me to always be looking for improved understanding of the layers under where I'm working, just in case one of those abstractions leaks. A more recent one, from 2018, is Migrations: the sole scalable fix to tech debt by Will Larson. I absolutely love his idea that migrations (e.g. replacing one service with a new one, or switching database engines, or whatever) are part and parcel of software engineering and are a skill that you should invest in and get good at, not avoid or treat as special one-offs. The Engineer/Manager Pendulum by Charity…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Richard Socher is an NLP OG and CEO of You.com, who has now spun out an even more ambitious startup focused on RSI — already worth $5B!
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：DevFest 2026 is back and here’s how you can connect with one of the more than 800 global events to build, secure, and scale in the agentic AI era.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Last week, researcher Jacob Coxon announced his resignation from Anthropic, stating that AI ‘could kill us all by the end of the decade’ Hello, and welcome to TechScape. I’m Blake Montgomery, US tech editor at the Guardian. Today in tech, we’re discussing the past week’s all-consuming apoplexy over AI safety. AI CEOs say they need to slow the pace of development. But will they? OpenAI urges UK lawmakers to rein in technology amid growing safety fears Europe must build own AI or risk getting cut off by US or China, says ECB’s Lagarde Trump attacks ‘sick conspiracy’ against AI as tech stocks slide Microsoft proposes limits on its AI with code of conduct amid safety debate I worked at Google DeepMind. You should listen to the warnings about AI We greet…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Comments come after court on Monday rejected the president’s mail ballot restrictions ahead of the November midterm elections Supreme court rejects Trump’s mail ballot restrictions for midterm elections Hello and welcome to the US politics live blog. Lawmakers have given their support to the supreme court’s rejection of Donald Trump’s bid to restrict mail ballots for the midterm elections. Mitch McConnell, the 84-year-old former Senate majority leader from Kentucky, was seen in Washington for the first time in months on Monday, minutes before his office released a statement saying that he was back at work. With a slip of the tongue reminiscent of Joe Biden, Gavin Newsom, California’s Democratic governor, told CNN that he would not run for president…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Party leader claims proposed new retrospective laws are unfair and Reform would retaliate with a crackdown on union funding if elected Jonathan Reynolds has said that people should not get “hyperbolic” about the risks posed by AI. Speaking ahead of Louise Haigh’s speech to the TUC later, which will address the topic (see 9.31am), and in the light of the ongoing concerns expressed by AI experts about the risk of AI models posing a threat to humanity, Reynolds told the Today programme: This is extremely powerful technology, and I think we should never be complacent or naive about the impact it might have. People will be worried by some of the things they’ve heard in the last few weeks, and I think we’ve got to be careful not to get hyperbolic about th…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Safety requirements are non-negotiable. They depend on meeting concrete goals, not just adjusting a timeline It has been a week of high drama in AI, precipitated by the resignation of the AI safety researcher Jacob Coxon from Anthropic. This followed several weeks of increasingly lurid and disturbing revelations about the OpenAI/Hugging Face incident. My inbox yesterday included a message from Business Insider with the subject line: “AI doomsday debate reaches boiling point”. Continue reading...
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Louise Haigh will set out benefits of AI to TUC conference while vowing government will take safety seriously Ministers must “heed the warnings” from industry leaders about the threat posed by AI as it looks to capitalise on the technology, the first secretary, Louise Haigh, will say on Tuesday. Labour MPs and peers have called for the government to further cooperate with international partners to build regulation for the technology, after three Anthropic researchers warned that artificial intelligence could kill off humanity within the decade. Continue reading...
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13466v1 Announce Type: new Abstract: Enterprise AI adoption has reached 78% of organizations globally, yet the infrastructure to govern that adoption has not kept pace. This paper identifies and characterizes the attestation deficit, a structural condition in which organizations maintain governance policies but cannot produce auditable, tamper-evident evidence of enforcement within regulatory timelines. Drawing on empirical data from the Stanford 2026 AI Index Report (362 documented incidents), the IBM/Ponemon 2026 Cost of a Data Breach study (USD 4.99M average cost, 92% lacking access controls), and the EY/AIUC-1 Consortium survey (38% end-to-end monitoring, 17% agent-to-agent coverage), this paper demonstrates that the governance failur…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Dario Amodei kicked off a flood of statements over the past few days about AI safety by publishing a long essay titled "We Must Pace the Frontier" detailing why AI development should be slowed down. Other AI leaders and politicians are speaking out in favor of or opposing his points, and we've compiled some of them here. Anthropic CEO Dario Amodei Amodei's Saturday morning essay outlined three steps for pacing AI development: embedded third-party evaluators that can verify if a company is adhering to safety practices and commitments and report incidents, coordination between frontier AI companies in democratic countries on standards and li … Read the full story at The Verge.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Firm publishes AI guidelines with Microsoft AI CEO saying: ‘AI must be subordinate and always in service of people’ Microsoft published a provisional “code of conduct” Monday to apply to the training of new artificial intelligence models, taking a step towards limiting the capabilities of the company’s AI as anxiety rises over the prospect that technology companies could lose control of AI products. Mustafa Suleyman, the CEO of Microsoft AI, published the code on social media early Monday, writing: “AI must be subordinate and always in service of people. Continue reading...
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：In this article, you will learn how to treat prompt templates as tunable hyperparameters for a language model, using scikit-learn's grid search to find the...
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13243v1 Announce Type: new Abstract: We present GzDRL, a novel single-process reinforcement learning (RL) framework for Gazebo that overcomes longstanding bottlenecks in scalable, reproducible robotics experimentation. Unlike conventional middleware-based RL-Gazebo integrations that suffer from nondeterminism and irreproducibility, GzDRL introduces a systematic, middleware-free environment-stepping mechanism that directly synchronizes agent actions and physics updates. This design enables deterministic, high-throughput data collection, efficient vectorization, and reproducible RL training and evaluation. Comprehensive benchmarks demonstrate that GzDRL achieves the highest workstation throughput among the evaluated frameworks while remaini…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13234v1 Announce Type: new Abstract: Industrialized construction imposes stringent precision requirements on robotic assembly of modular components such as prefabricated window units. In tolerance-critical operations, the central bottleneck is not only mechanical clearance but also converting tacit installer expertise into data-efficient autonomy under sparse acceptance feedback, contact variability, and millimeter-scale constraints. We present an installer-in-the-loop interactive reinforcement learning framework that acquires expertise through offline teleoperated demonstrations, sparse event-driven binary takeovers at contact-failure boundaries, and acceptance-aligned terminal rewards, logged under a unified schema for traceable offline…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13231v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models demonstrate strong generalization in robotic manipulation and navigation, but existing fine-tuning methods provide limited safety guarantees. Current approaches primarily rely on Lagrangian optimization that enforces safety through soft penalties on expected cumulative cost, often resulting in residual constraint violations or overly conservative behavior. Moreover, learning safety in visual domains is challenging due to the absence of dense per-step safety annotations. We propose ShieldVLA, a safety-aligned fine-tuning framework for VLA models based on Hamilton-Jacobi (HJ) reachability. ShieldVLA learns a model-free approximation of the HJ reachability value functio…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13239v1 Announce Type: new Abstract: Diffusion models represent one of the most advanced paradigms in generative modeling. Leveraging their development, a growing number of style transfer methods based on diffusion models have been proposed. However, among these methods, multi-image style transfer approaches that require at least five to ten style examples tend to achieve more satisfactory results. Single-image methods, by contrast, often struggle with either insufficient content preservation or inadequate style fidelity. This greatly limits style extraction from scarce artworks and undermines their artistic value. To address this, we propose Abstract-LoRA, a method that pushes the boundaries of single-image style transfer through lightwe…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13237v1 Announce Type: new Abstract: Orthodontic report generation from intraoral data is normally cast as multimodal captioning, yet the released Bite2Text scan pairs are supplied already registered in occlusion, which makes several core occlusal quantities directly measurable rather than inferable. The system reported here exploits that property: an anatomical frame is recovered per case from arch taper and arch closure instead of the stated RAS convention, which does not hold across the release, and each arch is reduced to an occlusal ridge profile in arch-angle coordinates yielding overbite, overjet, midline deviation, transverse overlap, crossbite extent, cusp interdigitation lag, and the occlusal curves in closed form. Gradient boos…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13232v1 Announce Type: new Abstract: A robot pruning trees needs two facts per pixel: whether it belongs to a tree, and its distance. Both are usually obtained via task heads attached to a vision backbone chosen by reputation rather than measurement. Holding dataset, decoders, losses, schedule, and evaluation fixed, we ask: how much does the encoder choice change joint semantic segmentation and stereo depth on thin vegetation? We build a hard parameter-sharing network with one encoder feeding both branches, swapping only the encoder without downstream retuning. We evaluate [N] encoders across [M] architecture families (CNNs, transformers, hybrids, MLP-mixers, state-space models) near a ~25M budget, trained from scratch. Depth is evaluated…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13228v1 Announce Type: new Abstract: Vision Language Models (VLMs) should rely on visual evidence that directly determines the correct answer, but supervision for grounding visual reasoning is often expensive to obtain manually or tied to dataset-specific annotation primitives. We instead introduce model-causal visual evidence as an annotation target, defined as the set of image regions whose counterfactual intervention changes a model's answer distribution for a given image-question pair. Based on this principle, we introduce Counterfactual Search for Grounding Regions (CSGR). CSGR is a scalable pipeline that proposes candidate regions, perturbs them, measures their effect on answer sensitivity, and aggregates this evidence across multip…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13226v1 Announce Type: new Abstract: Machine learning for neglected tropical diseases is limited by data, not algorithms: public annotated image sets for leprosy (Hansen's disease) number in the hundreds, orders of magnitude below what generative models require. We ask whether a model trained on abundant chronic wound photography transfers to this low-data regime. We build a three-stage pipeline. First, a DeepLabV3-ResNet50 segmentation network (validation Dice 0.876, IoU 0.799) supplies lesion masks for two wound datasets that ship without them. Second, we assemble a mask-conditioned latent diffusion model from Stable Diffusion 1.5 components and train it on 3,280 region-of-interest wound crops, widening the UNet input convolution from 4…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13225v1 Announce Type: new Abstract: Benchmarks agree that vision-language models reason poorly about low-level manipulation, but an aggregate accuracy score does not say which step fails. We separate two steps that affordance questions conflate: identifying which part of an object to act on, and knowing what action that part requires. Across 19 articulated objects we asked eight models, spanning three developers, what motion a robot should apply. Under an open prompt, push was produced once in 64 evaluations where it was correct, despite being correct for 8 of 19 objects and appearing in the offered label set every time. Inspecting the outputs showed why: models described a different part than the one being scored, e.g. explaining how to…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13190v1 Announce Type: new Abstract: Continuous cuffless blood pressure (BP) monitoring using photoplethysmography (PPG) offers a promising solution for personalized healthcare. However, existing methods have two major limitations. Handcrafted feature-based approaches rely on precise fiducial point detection and are limited to short-term analysis, while deep learning models, despite their accuracy, often operate as black boxes with limited physiological interpretability. To address these challenges, we propose a physiology-guided hybrid framework for personalized BP estimation that couples a convolutional neural network (CNN) branch capturing global and local waveform dynamics with a morphology-prior branch that explicitly encodes person-…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13481v1 Announce Type: new Abstract: Large language models have made abstractive summarization remarkably fluent, but generated summaries can hallucinate facts, posing serious risks in biomedical and clinical domains. We address this by removing generation from the pipeline and framing summarization as extractive sentence selection. Our Hybrid Hierarchical CNN-LSTM Summarizer uses stacked multi-kernel convolutions to compose sentence-level embeddings into richer inter-sentence representations, followed by a bidirectional LSTM to model long-range dependencies across the document. A lightweight scoring head assigns per-sentence importance scores and is trained end-to-end with binary cross-entropy against oracle extractive labels. At inferen…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13454v1 Announce Type: new Abstract: Clinical decisions are prospective, but clinical language models are often evaluated on retrospective records that reveal the final diagnosis, treatment response, and outcome. Such evaluations may reward the use of future information rather than reasoning under the uncertainty present at the decision point. We introduce a paired benchmark for measuring outcome-conditioned shifts consistent with hindsight bias in clinical temporal reasoning. It contains 171 case reports from the PubMed Central Open Access Subset---40 sepsis and 131 GLP-1/diabetes cases---represented as both textual narratives and human-annotated and LLM-generated textual time series (TTS). For each case, questions are tied to a clinical…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13445v1 Announce Type: new Abstract: Speech-to-speech LLMs like Moshi, and its derivative PersonaPlex, can listen and speak concurrently through full-duplex generation. However, they can begin speaking inappropriately during prolonged user silence: under digital-zero input, Moshi and PersonaPlex initiate speech in 12/40 and 11/40 five-minute continuations, respectively. What causes this spurious speech? We investigate two hypotheses: either repeated sampling selects speech despite persistently low onset probabilities, or conditioning on the model's nonspeech outputs causes an abrupt spike in onset probability. We find that, at every observed onset, speech probability spikes by over nine orders of magnitude in one 80-ms frame, supporting t…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13389v1 Announce Type: new Abstract: Mapping textual specifications into formal representations is essential for ensuring the correctness of protocol designs and implementations. LLM-generated mappings, used for networking security or testing, are assumed to capture a perfect understanding of the specification, which may not hold in practice. The goal of this paper is to assess the extent to which LLMs can interpret the specification correctly. We examine the degree to which an LLM's implicit representation of a finite-state transition system-defined via natural language descriptions-aligns with a manually generated ground-truth model. We designed 4 tasks and 1482 task queries for 16 protocols. We evaluated different judge biases, observe…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13238v1 Announce Type: new Abstract: Maxillofacial report generation from cone beam computed tomography is scored here by a composite objective placing 80% of its weight on a large language model judgement of factual entailment and 20% on lexical overlap, of which only the lexical fifth is visible during development. The grader's BLEU-4 and METEOR routines are reproduced in pure Python and match the reference to machine precision, and an offline entailment surrogate, which tells a report written for one patient from one written for another at an area under the curve of 0.987, makes the composite objective cheap enough to optimise directly. Over the 622-case public release, a report selected against the visible lexical ranking scores 0.290…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13158v1 Announce Type: new Abstract: Large Vision--Language Models (LVLMs) are increasingly expected to perform visual question answering (VQA) over planar media. However, existing planar VQA benchmarks typically emphasize isolated challenges: some emphasize long-document understanding with limited reasoning depth, while others require complex visual reasoning but remain restricted to single-page, noise-free settings. Moreover, through theoretical analysis, we identify the impact of irrelevant visual tokens, which leads to measurable performance degradation but has received little attention with respect to systematic quantification. To address these limitations, we introduce TestHallVQA, a multi-image VQA benchmark that simultaneously emb…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13154v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have made prompts increasingly large and complex. Techniques such as chain-of-thought reasoning (Wei et al., 2022) and in-context learning (Brown et al., 2020) frequently push real-world prompts past several thousand tokens, increasing inference cost and latency. Learned compression methods such as LLMLingua (Jiang et al., 2023) and Selective Context (Li et al., 2023) achieve high compression ratios but require auxiliary language models and are non-deterministic. We ask a complementary question: how far can a training-free, fully deterministic, CPU-only pipeline based on classical lexical NLP be pushed before output quality degrades significantly? Eleven…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13152v1 Announce Type: new Abstract: Large language models (LLMs) perform strongly on static science benchmarks, yet their ability to reason about the physical world through active experimentation remains poorly understood. We introduce PhysMent, a benchmark that evaluates LLM physical reasoning via iterative, toolmediated interaction with a MuJoCo physics simulator. Unlike static benchmarks that supply all quantities upfront, PhysMent requires models to discover information by applying forces, querying object states, advancing time, and modifying scene geometry before answering. The benchmark comprises 105 scenes of classical mechanics, organized across four difficulty regimes (Easy/Hard and Single/Multi), three scene modalities (standar…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13151v1 Announce Type: new Abstract: Leading multilingual speech recognition models like Whisper transcribe diverse, low-resource languages without language-specific training but are computationally expensive to deploy. Token merging mitigates this inefficiency by dynamically combining redundant features, shortening the sequence length during inference without requiring retraining. In this paper, we systematically evaluate token merging on the Whisper model family across sixteen diverse languages and three different model sizes. We also test how token merging interacts with fine-tuning (DoRA) on low-resource languages. Our findings show that merging tokens increases computational efficiency with almost no loss in transcription accuracy ac…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13198v1 Announce Type: new Abstract: One of the pivotal recent challenges in neural network interpretability is polysemanticity, where a single neuron is activated by multiple, often unrelated concepts, hindering clear functional understanding. Although prior work has explored this phenomenon, existing approaches remain architecture-specific and depend on manual heuristics such as a fixed number of concept clusters ($K$), limiting their generality and scalability--especially for modern Transformer-based models. To address these limitations, we introduce SPICE (\textbf{S}imple \textbf{P}olysemantic Feature \textbf{I}nterpretation via \textbf{C}lustering-based \textbf{E}xplanation), a generalizable framework for analyzing polysemanticity in…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13197v1 Announce Type: new Abstract: Algorithmic Information Dynamics (AID) studies systems by perturbing them and measuring changes in algorithmic complexity, but its usual estimator, the Block Decomposition Method, is piecewise constant, restricting the calculus to finite differences. We use $K^{\mathrm{CDM}}_{\mathrm{s}F}$, a certified, differentiable estimator, to bring the calculus into learning dynamics: grokking, where a complexity order parameter is known but has not been made to act. A\empts a transient loss kick, the estimator becomes a controller that accelerates grokking in Levin's description-length--versus-time sense, within a data-dependent Occam boundary whose finite-size trend, $f_c\sim\ln p/p$, is consistent with a coupo…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13195v1 Announce Type: new Abstract: Large Audio-Language Models (LALMs) have recently shown strong capabilities in speech understanding and question answering (QA), but they also inherit privacy risks from large-scale training data, including the unintended memorization of sensitive information. In this work, we study machine unlearning for speech QA in LALMs, a setting that is more challenging than prior work on text-based Large Language Models (LLMs) or Automatic Speech Recognition (ASR) due to the tight coupling between acoustic perception and factual knowledge. We present and evaluate multiple unlearning strategies, including gradient ascent, task arithmetic, and alignment-based fine-tuning methods that enforce safe refusal responses…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13192v1 Announce Type: new Abstract: This study compares traditional machine learning models and Large Language Model (LLM)-generated rule-based systems for heart disease prediction using the UCI Heart Disease dataset. Several classifiers, including Logistic Regression, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Naive Bayes, Decision Tree, and Random Forest, were evaluated alongside rule-based systems generated using GPT-4o and Claude Sonnet 4.6. Model performance was assessed using accuracy, precision, recall, and F1-score metrics. Experimental results show that traditional machine learning models consistently outperform LLM-generated rule-based systems in predictive performance. Random Forest achieved the best overall perf…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13191v1 Announce Type: new Abstract: The rapid expansion of operational satellites and orbital debris has increased the frequency of close approach events in low Earth orbit (LEO), creating a higher operational burden for satellite operators. This problem is especially critical for satellites using electric propulsion, where low-thrust maneuver capability imposes additional time constraints on collision avoidance planning. In current practice, Conjunction Data Messages (CDMs) provide relative state, covariance, miss distance, time of closest approach, and probability of collision (PoC) information for conjunction assessment. However, the nonlinear propagation of orbital uncertainties and the sensitivity of PoC to covariance evolution make…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13185v1 Announce Type: new Abstract: Large language models (LLMs) prompt a recurring question in research computing: should classical methods like Naive Bayes (NB) be retired? We benchmark Complement Naive Bayes against zero-shot and few-shot LLMs spanning four model families and a 37x range in scale (27B to a 1T-parameter mixture-of-experts) across text classification tasks. LLMs dominate only in zero-data regimes (98.0% vs 88.2% on Amazon Polarity sentiment), and even that win is contamination-prone: on a low-contamination sentiment task NB beats the zero-shot LLM (81.7% vs 73.0%). However, once labeled data is available (e.g., AG News), NB reaches 89.1% accuracy, statistically indistinguishable from the zero-shot 27B LLM (89.0%) and be…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13182v1 Announce Type: new Abstract: Robert Smithson's 1970 land artwork Spiral Jetty, located in the north arm of Utah's Great Salt Lake, has alternated between submergence and exposure during severe lake decline. We analyze 1,744 co-registered Landsat 4-9 and Sentinel-2 image chips spanning every year and calendar month from 1984 to 2025. A 14-feature complexity signature combines Shannon entropy, multiscale permutation entropy, fractal dimension, lacunarity, gray-level co-occurrence texture, intensity statistics, and ImageNet-pretrained ResNet50 features. These measurements are compared with a 42-year monthly climate and hydrology panel from NASA GISTEMP, USGS NWIS, Open-Meteo, and the Global Carbon Budget. Bootstrap analysis shows tha…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13470v1 Announce Type: new Abstract: Although large language models (LLMs) have demonstrated remarkable capabilities, their reliance on cloud-scale infrastructure poses fundamental challenges for deployment in agentic pipelines, including latency, privacy, connectivity, and substantial computational cost. Small language models (SLMs) offer a compelling alternative: recent studies suggest that many repetitive and narrowly scoped subtasks in agentic workloads may be better served by specialized SLMs than by monolithic LLMs. However, the limited capacity and context windows of SLMs can constrain long-horizon reasoning and interaction-heavy orchestration strategies such as iterative verification and debate. This motivates a complementary, non…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13457v1 Announce Type: new Abstract: Timeseries multimodal large language models (TS-MLLMs) have recently begun leveraging the reasoning capabilities of large language models (LLMs) for question-answering tasks. However, these models often fail to capture dynamic temporal patterns, providing only implicit reasoning that lacks the underlying explanations critical for high-stakes applications like healthcare. While reinforcement learning (RL)-based timeseries language models aim to address this, they often fall short because they are trained on narrow, in-distribution data and struggle with out-of-distribution compositional questions. To address these challenges, we present TimeThink, a synthetic framework for eliciting compositional timese…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：When OpenAI CEO Sam Altman, Anthropic CEO Dario Amodei, Google DeepMind cofounder Demis Hassabis, and SpaceX head Elon Musk loosely agreed over the weekend to slow down AI development, skeptics spotted an ulterior motive immediately. The AI titans had declared that their aim was to "pace the frontier," signing on at least partially to a proposal for embedding third-party auditors, regulating domestic labs, and reaching a global slowdown agreement. Their critics, however, argued they simply wanted to stop would-be competitors, kneecap the open-source movement, and avoid real legal safeguards - some dubbed it an outright "cartel." The truth … Read the full story at The Verge.
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要： The contagion of fear Bryan Cantrill responds to the tweet by former Anthropic employee Jacob Coxon confirming that many Anthropic researchers believe AI "could kill us all by the end of the decade". Bryan shares a story of his own youthful mistakes causing unjustified panic among less technical peers, and warns against doing the same: These ghoulish claims strike brazenly at the hearth, and given the obvious importance of AI, it is unsurprising that they have leapt into the mainstream, with people asking the natural question: how would that happen? The answers always rely on hand-wavy extrapolation into the future; for example, Jacob Coxon cites "hacking critical infrastructure" and "extinction-level bioweapons" without further elaboration. But Co…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：Central bank chief says continent’s AI dependency could give trade partners unprecedented leverage in negotiations Europe must develop its own AI technology and build more datacentres in order to nullify the threat of being cut off by the US or China, according to the president of the European Central Bank. Christine Lagarde said the continent needed AI models – the technology that powers AI tools such as chatbots – that were “good enough” to carry out most tasks and run from domestic datacentres. If Europe invests in its own AI tech, said Lagarde, “the threat of being cut off loses its force”. Continue reading...
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13290v1 Announce Type: new Abstract: Achieving biological-level running speeds has largely been pursued through advances in control algorithms, which improve the utilization of existing hardware. However, the ultimate speed limits remain governed by the underlying force and torque requirements of rapid locomotion, which are typically addressed through increased actuator capacity. Inspired by Huygens' coupled pendulums, we demonstrate that superior locomotion can emerge from principled exploitation of intrinsic dynamics rather than brute-force hardware scaling. Inter-limb inertial coupling redistributes energy across the gait cycle and reduces peak joint torque required for rapid periodic motion, thereby expanding the achievable speed with…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：arXiv:2609.13224v1 Announce Type: new Abstract: Autonomous vehicles are expected to improve road safety and efficiency, but passengers often remain uncertain about what the vehicle perceives and why it acts as it does. Virtual reality (VR) offers a safe and repeatable medium for presenting this information, yet most passenger-facing VR studies rely on fully simulated vehicles or pre-scripted scenarios, so the motion and perception shown to the user do not originate from a physically operating autonomous system. This paper presents a video-augmented VR framework that couples a physical ROS 2 autonomous robot vehicle to a Unity 6 application deployed on a Meta Quest 3S headset. The vehicle state and live onboard camera stream are transmitted over two…
AI サービスが一時的に利用できないため、復旧後に翻訳を補完します。ソース概要：NVIDIA CEO Jensen Huang speaks during the G20 Innovation Ministerial in Chapel Hill, North Carolina, on September 2, 2026. (Photo by Matt RAMEY / AFP via Getty Images) | AFP via Getty Images Nvidia CEO Jensen Huang took a call from President Trump on Monday while onstage at the All-In Podcast's All-In Summit. It's not the first time Huang has taken a call from the president during work, but this time he put Trump on speakerphone before a big crowd. During the call, the president launched into his take on recent fears about AI development, which he called a "hoax," and told the crowd that "the robots will not be taking over." It's already a frothy week for AI news. The call with the president followed Anthropic CEO Dario Amodei's long essay published…