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：For a decade, identity and access management meant one thing: governing the humans who log in. Employee joins, gets provisioned, gets a manager, gets a departure date, gets offboarded. That loop is well understood. What changed is that the fastest-growing population inside enterprise environments is no longer human, and the governance playbook written for people […]

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：Bindago - AI Message Personalisation for LinkedIn Outreach How It Works Write Once. Personalise for Everyone. You write one base message. AI generates a unique section for each lead using their real LinkedIn profile dat…

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：GLM 5.3 Flash | Model APIs | RunInfra RunInfraby RightNow © 2026 RunInfra. All rights reserved. Join the communitySystem status Backed by Combinator AICPA Type II SOC 2 Ask AI about RunInfra Part of RightNow RunInfraby…

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：Senior Product Engineer ($220k-$300k + Equity) - NYC at Conveo | Y Combinator Conveo Confident decisions in days with AI-led interviews. Senior Product Engineer ($220k-$300k + Equity) - NYC $220K - $300K•New York Job ty…

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：As the US president struggles to end his Iran war, and approval ratings hit new lows, he leans on a familiar gambit Donald Trump knows the power of an image – of himself, with everyone from Vladimir Putin and Kim Jong-un to Kim Kardashian. How about George Washington? As the US president struggles to end his war with Iran, and with his approval ratings hitting the lowest levels of his second term, he has in recent weeks posted a series of AI-generated images of himself alongside key historical American figures. 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：People are becoming convinced AI chatbots have helped them make scientific breakthroughs, cure diseases or invent new technologies. What does this reveal about a technology used by more than a billion people? A new series from The Guardian Investigates, coming soon 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：China & AI | WireScreen Briefings CareersProduct WWIRESCREEN · SPECIAL REPORT · CHINA AND ARTIFICIAL INTELLIGENCE WS-2026-034 · AUGUST 2026 Built and Owned The people, the money and the ownership behind China’s leading…

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 factories must support increasingly large models and more complex reasoning workloads. To keep up with the insatiable compute demands of AI workloads, hyperscalers and AI-native companies are developing custom AI acc…

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 humpbacks learning the latest songs to sperm whales’ ‘clan codas’, drones and AI learning are helping reveal another dimension to the concept of culture In 2015, the whale researcher Valeria Vergara pitched a small tent at the icy water’s edge on Somerset Island in the remote Canadian high Arctic, shrouded in a freezing fog so thick she struggled to see her own hands. She trailed a cord out to the coast and plopped a hydrophone into the water to record the calls of belugas. As many as 1,000 of the whales, accompanied by their newborn calves, frequented the surrounding bay. Belugas’ ceaseless chatter, made up of dozens of unique sounds, is crucial to keeping these creatures connected in the dim, turbid waters of the Arctic. 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 right case can take your iPad Air to the next level. These are our favorite iPad Air cases from brands like Apple, Burga, and Logitech.

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 randomized study of more than 1,000 students examines ChatGPT, critical thinking, originality, and student performance on a real-world university assignment.

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：All-new TaskShell 2.0 as a first-class MCP platform Agent-first task management No more app-switching to keep up with your todos. You and your agents now completely in sync with your work, exactly where you work. Sync 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：Two German airport workers die of malaria after 'mosquito arrives on plane' - BBC News Image source, Getty Images Image caption, Frankfurt is Germany's busiest airport ByAndré Rhoden-Paul and Joe Coughlan Published 26 A…

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：Discussion | Link

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：Agents that interact with a traditional OLTP database often create bottlenecks at the storage layer. New deployments...

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：Uh oh! There was an error while loading. Please reload this page. Notifications You must be signed in to change notification settings Fork 0 Star 1 BranchesTags Open more actions menu Latest commit History 18 Commits 18…

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：Disclosure: These views are my own and do not represent my current or any former employers. Executive summary The COVID-19 pandemic forced a large part of the North American knowledge workforce to work from home. The ch…

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：Discussion | Link

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：Discussion | Link

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：Aug 27, 2026 Your AI Generated Menu Triggered my Trypophobia Quite a few restaurants are switching to using AI-generated food photos for their menus. The idea to use completely synthetic photos is pretty problematic 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：Hello HN! There is an abundance of choice when it comes to text editors, but they all seem to be either too simplistic and minimal, or overly complex, distracting and difficult to use. Kraa is trying to strike the right…

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：Howcomet — the app that asks your kid a question back Howcomet Grown-ups → How a question becomes a star 💬 Ask the real question Volcanoes, black holes, why your ears pop. Say it or type it. The answer is written for y…

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：Discussion | Link

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：Google Research and UNSW Sydney released GlucoFM, a self-supervised foundation model that splits a CGM trace into a slow physiological stream and a transient event stream instead of encoding it as one sequence. At 0.72M parameters it reached 58.8 task-averaged PR-AUC across 14 cohort–task evaluations, beating a 135M GluFormer and a 385M MOMENT. It remains a research prototype with no regulatory clearance. The post Google Research Introduces GlucoFM: A 0.72M-Parameter Dual-Stream Foundation Model for Continuous Glucose Monitoring 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：AI companies have promised us world-shifting technology. But there’s a cost: loud, unsightly datacentres that drain environmental resources. As the government pushes their rapid growth, can local communities do anything to push back? Madeleine Finlay speaks to the Guardian’s global technology reporter Aisha Down about the backlash to datacentres across the UK and around the world For tickets to the Science Weekly live event at the London podcast festival on the future of AI, visit the event page at kingsplace.co.uk Support the Guardian: theguardian.com/sciencepod 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:2608.25284v1 Announce Type: new Abstract: Physical human-robot collaboration requires a robot to provide assistance when human intention is clear while remaining compliant when several future motions are plausible. We present an adaptive stiffness framework based on generative action-chunk sampling. Conditioned on an RGB image and external joint-torque estimates, the policy samples multiple future action chunks from an observation-conditioned prior. Variation among the sampled action chunks is used to continuously adapt joint stiffness and damping. Greater variation makes the robot more compliant to facilitate human guidance, whereas lower variation provides firmer assistance. In a real-world collaborative transport task with four possible directions, the proposed method achieved an average success rate of 0.95, compared with 0.83 for a fixed-stiffness ablation and 0.69 for a deterministic baseline. Near direction determination, variation among the sampled action chunks increased and the controller accordingly reduced stiffness. These results suggest that variation among actions sampled by a generative policy can serve as an online control signal for balancing assistance and compliance in physical human-robot interaction.

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:2608.25222v1 Announce Type: new Abstract: The impairment of the hands can seriously affect the abilities of every individual to perform the every-day activity, so the design of stable and controllable support devices is a significant field of study. This paper is about the design and implementation of an automated bionic hand which is dedicated to the coordinated finger movement through the simplified and efficient actuation mechanism. The method that the proposed system was designed on is the tendon-based method whereby the servo motors generate the movement of the fingers, with assistance of the angular control which is calibrated. An actuation is controlled by a microcontroller that will be programmed by use of an Arduino-based microcontroller to carry out programmed gestures that include open hand, fist, pinch and half flexion. It has an interface that is voice command enabled to make it easy to interact with a Bluetooth based sender receiver architecture which offers an option of executing trained commands which are immediately converted to finger actions. To explore the motions behavior, finger coordination and control response to the input, the behavior of the experiment system is tested. The actuation of the fingers was found to take a total of about 7-8 seconds to achieve full flexion of all fingers in a sequence. The system showed repetitive and constant motion throughout several actuation cycles without loss of any apparent tension or precision of control. There was a stable grasp of objects of different shapes and sizes, which implied consistent coordination between the fingers. These findings indicate that the proposed system offers predictable and steady control behavior and has a simple and efficient mechanical and control architecture.

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:2608.25196v1 Announce Type: new Abstract: Learning from demonstration (LfD) methods enable non-expert end users to teach robots novel skills without explicit programming. However most evaluations of the usability of LfD with non-experts has been conducted in controlled laboratory environments with a robotics experimenter present. In this work we identify non-expert end users' key barriers when teaching robots via demonstration without live robotics expert feedback in a home environment. In our human subjects experiment we support the non-expert end users through two forms of demonstrator guidance developed in prior work: pre-training and adaptive feedback. Towards the ecological validity of the evaluation, we conduct this experimentation over multiple visits, with a population of care providers. Finally, we propose to open source the resulting LfD dataset of care providers teaching a robot assistive tasks over multiple visits to a home environment.

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:2608.25192v1 Announce Type: new Abstract: We introduce CRESSim-Neo, a batched GPU simulation engine for surgical robotics and robot learning. CRESSim-Neo combines position-based simulation of rigid bodies, deformable tissues, fluids, and strands with batched rendering, surgery-specific sensing, and a GPU-resident data pipeline. The engine supports applications including tissue manipulation, fluid suction, suturing, cable-driven robots, and ultrasound image synthesis. Direct access to physics and rendering buffers enables GPU-resident robot learning and zero-copy PyTorch integration using DLPack. We demonstrate CRESSim-Neo across rigid-body, deformable-body, and fluid simulation tasks, including vision-based and surgical robot-learning scenarios. On an NVIDIA RTX 4090, the engine achieves up to 2.03 million environment steps per second for 8192 parallel CartPole environments, and scales to batched surgical scenarios involving tissue deformation, fluid interaction, and ultrasound sensing. Overall, CRESSim-Neo provides a unified and scalable platform for surgical simulation, synthetic data generation, and surgical robot learning.

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:2608.25171v1 Announce Type: new Abstract: Soft pneumatic actuators offer inherent compliance and safe interaction but remain difficult to model and control because of their highly nonlinear, distributed dynamics. We present a control-oriented data-driven modeling and control framework that decomposes actuator behavior into a nonlinear static equilibrium model and a linear residual dynamics model identified using Extended Dynamic Mode Decomposition with control (EDMDc). This representation enables feedforward compensation, task-space feedback control, and local closed-loop stability analysis through an augmented linear model. Experiments achieve approximately 1 mm root mean square error (RMSE) during low-speed (approximately 10 mm/s) trajectory tracking and below 10 mm RMSE at higher speeds (approximately 100 mm/s). The framework further achieves stable tracking of highly dynamic user-generated references with peak accelerations exceeding 25 m/s^2 while simultaneously performing real-time obstacle avoidance. Finally, the proposed stability analysis is experimentally validated by accurately predicting stable, marginal, and unstable operating regimes. These results demonstrate that structured, control-oriented learning provides an accurate and practical framework for soft actuator control.