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Even a little activity during the remote workday can help you focus, improve your mood and energy levels, and relieve stress.

For the enterprise, the promise of agentic AI is much more than just a better chatbot. It is software agents that execute business tasks end-to-end across people, business workflows, data, and systems. The platform best-suited to run agents is built with proper CPU capacity, resilient data access, policy-aware tool use, observability, memory management, and the…

The state electricity utility seeks information that would allow it to close identified gaps in its existing system.

A leading environmental economics journal is looking into claims that a 2025 study linking national innovation to lower carbon emissions contains data that does not match its source, after an expert in the field requested the paper be retracted. The article appeared in Ecological Economics, the journal for the International Society for Ecological Economics and … Continue reading Journal investigating apparent data mismatch in climate study

This article is republished with permission from Laser Wars , a newsletter about military laser weapons and other futuristic defense technology. The most critical component to actually fielding high-energy laser weapons at scale isn’t the diode pump, or the gain medium, or the beam director. It isn’t even the power source. In reality, it may actually be this tiny fiber-optic converter. On July 23, defense technology company Attalon—formed earlier this year from the spin-off of American laser com

arXiv:2607.22006v1 Announce Type: new Abstract: Buildings account for roughly 34% of global final energy use and 37% of energy- and process-related CO$_2$ emissions. Stranding regulation now being enacted (New York City Local Law 97, the EU Energy Performance of Buildings Directive recast) presupposes that a building portfolio's carbon intensity can be measured per square metre and compared against a science-based pathway. Whether corporate disclosure is actually fit for that comparison has not,

arXiv:2604.26577v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly considered for deployment as the control component of robotic health attendants, yet their safety in this context remains poorly characterized. We introduce a dataset of 270 harmful instructions spanning nine prohibited behavior categories grounded in the American Medical Association Principles of Medical Ethics, and use it to evaluate 72 LLMs in a simulation environment based on the Robotic H

Mobile robots operating in human-populated environments must navigate complex, multi-room spaces while ensuring safety, i.e., generating collision-free motion. In this study, we present a sensor-based model predictive control (MPC) scheme designed for safe crowd navigation in such non-convex environments. The proposed framework decomposes the free space into a set of overlapping convex regions to construct a topological graph, enabling a high-level planner to compute optimal sequences of travers

Tadej Pogačar's fifth Tour de France victory came after last-minute course changes due to wildfires, underscoring how climate change is influencing major sporting events.

Multi-turn long-horizon planning is critical for foundation model agents, yet how to fundamentally improve it remains unclear. Existing models are trained on uncontrollable and opaque Internet data, making it difficult to identify how planning ability is acquired, shaped, and integrated. To address this challenge, we introduce a unified and controlled multi-turn environment that enables precise control. It allows systematically study long-horizon planning across three stages. (1) Planning abilit

The study, released after months of delays and mounting criticism, was ordered two years ago amid growing concerns about resources for data centers.

Entering 2026 from a position of relative strength, the energy price shock from the war in the Middle East is projected to slow growth to about 1 percent and lift inflation to around 3 percent, amid ...

Lawmakers are setting their sights on data centers proposed for military bases, concerned about massive energy and water consumption.

Safe quadrotor navigation in cluttered and dynamic environments depends not only on instantaneous geometric perception, but more critically on anticipating collision risks induced by relative motion. Conventional modular pipelines frequently suffer from perception latency, while end-to-end learning methods relying on implicit scalar rewards often struggle to extract reliable spatio-temporal features without physics-grounded supervision. To address this, we propose an anticipatory risk-guided rei

Since Volta introduced Independent Thread Scheduling (ITS), NVIDIA GPUs have been widely assumed to handle warp divergence in a fixed manner. We test this assumption across Ampere, Hopper, and datacenter and consumer Blackwell GPUs, using pre-ITS Pascal as a baseline. Combining cycle-accurate microbenchmarks, hardware counters, and static analysis of compiler-generated SASS, we separate stable behavior from architectural change. Across all tested generations, divergent paths serialize linearly w

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Our animosity toward data centers is really more about our anxieties about A.I.

Large language models (LLMs) are being increasingly integrated into immersive environments and design workflows, providing application prospects in areas such as rapid scene prototyping for non-expert users and scene understanding capabilities for accessibility design. While many workflows that incorporate LLMs in immersive spaces are proposed, such systems can exhibit errors, potentially resulting in frustration, loss of user trust, and compromised user safety. This paper studies the underexplo

In a cybersecurity test, OpenAI's most advanced models breached the boundaries of their isolated test environment, reached the open internet, and hacked the AI platform Hugging Face on their own. The attack took hours, not the weeks a human hacker would need. At least seven days passed before OpenAI realized what had happened. By then, the FBI was already involved. Earlier warning signs had apparently gone ignored. The article New reports reveal the extent of OpenAI's loss of control during the

A close call in Northern Virginia revealed just how poorly data centers respond to grid disruptions. Here's how to fix the problem.

Nvidia will invest $1 billion in South Korean internet company Naver to help finance an AI data center under construction in South Korea, the chipmaker announced late Friday. The funding will allow Naver to more than triple the size of the facility from 55 megawatts to 200 megawatts, with US private equity firm Brookfield agreeing […] This story continues at The Next Web

Today's links Apple's robo-repo: Privatizing the risk premium, socializing its costs. Hey look at this: Delights to delectate. Object permanence: Printed batteries; Monopoly credit cards; Mapping airport power outlets; EMI loves pirates; Mexican indigenous phone co-op; Sewer cover textiles; Surge pricing v antitrust; Carbon offsets v forest fires; Charter schools as money laundries. Upcoming appearances: Edinburgh, Sydney, Melbourne, Brighton, London, South Bend. Recent appearances: Where I've b

A small Finnish town has turned to the world's largest commercial sand battery to tackle a major hurdle in the energy transition: intermittency.

Publication date: September 2026 Source: Technology in Society, Volume 88 Author(s): Xue Lei, Xin Jin, Shanshan Yue, Muhammad Tufail

Publication date: November 2026 Source: Technological Forecasting and Social Change, Volume 232 Author(s): Hanna Buyssens, Stijn Viaene

Publication date: November 2026 Source: Technological Forecasting and Social Change, Volume 232 Author(s): Wei Shan, Renbo Shi, Changfeng Cheng, Tailai Xu

The company has comitted to 10 natural gas plants since last year.

The utility says FCC should pause the complaint while parties privately dispute the issue.

AI data center projects have divided the Republican rural community in states like Texas, and Democratic nominees are taking advantage.

To effectively integrate AI into high-stakes, critical environments such as healthcare, autonomous driving, and aviation--and to advance toward higher levels of automation and seamless human-AI collaboration--building trust in AI-driven solutions is essential. Trust, in turn, is closely linked to the explainability of AI systems. The rapid advancements in AI across various domains have underscored the challenges of establishing trust, raising increasing interest in AI explainability even more wh

Large Language Models (LLMs) are increasingly deployed as autonomous agents, transitioning from static conversational interfaces to dynamic systems capable of complex reasoning, tool execution, and decision-making. However, the operational reliability of these agentic AI systems is fundamentally challenged by the absence of reliable ground truth in open-ended environments and the risk of increasing operational drift over time. To address this challenge, we propose and experimentally evaluate an

Vision-language model (VLM) agents increasingly use tools to act on 3D scenes rather than only describe them. Existing 3D benchmarks score textual responses or single-object operations, leaving agent action on complete multi-object 3D scenes under evaluated. We present SceneActBench, a benchmark for visually conditioned action across five 3D tasks under a unified agent-environment loop. Given PNG images or sampled video frames and, where applicable, supplied 3D assets, an agent acts on a 3D envi

High-complexity operational environments require methods that detect and anticipate temporally distributed patterns rather than classify isolated events. This paper introduces TRACTA (Temporal Reasoning and Capability-Trajectory Analysis), a controlled synthetic benchmark for temporal structural reasoning in high-complexity event-driven systems, instantiated through Multi-Domain Operations (MDO)-like scenarios. The benchmark includes three tasks: early_warning, pattern_detection, and run_classif

We introduce time-reversed imaging, a new paradigm that infers what just happened in a scene from fading multimodal traces. Instead of extrapolating or interpolating video frames, our goal is to infer past human-environment interactions from residual physical imprints observable in thermal, ultraviolet, and visible spectra. To study this problem, we present TRACE-HEI, the first proof-of-concept dataset for time-reversed imaging, containing synchronized tri-modal video sequences of actions such a

Chinese AI lab Moonshot’s open model Kimi went viral this week for reasons that had less to do with the model itself and more to do with how the U.S. AI industry reacted to it. Meanwhile, an unreleased OpenAI model wandered outside its test environment and ended up connected to a real security breach at Hugging Face — a reminder […]

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Large language models (LLMs) and AI agents have demonstrated strong potential for data integration in zero-shot and few-shot settings. However, they continue to face significant accuracy and cost challenges in enterprise environments due to a persistent knowledge gap. This paper envisions trustworthy, scalable, and cost-efficient integration through knowledge-grounded LLMs and agents operating within a retrieval-augmented generation (RAG) workflow. Here, trustworthiness refers to evidence-ground

Unlike the U.S., China is making clean energy a core part of its AI infrastructure buildout.

The number of data centers in China is surging thanks to AI , just like in the U.S. But unlike the U.S., China is racing to power them with clean energy. A data center in Mongolia , for example, is connected to 200 megawatts of wind power, 100 megawatts of solar power, and 45 megawatts of battery storage. In remote Qinghai, a pilot data center runs fully on a solar microgrid. In another part of northern China, a data center is connected to 500 megawatts of solar and 1.5 gigawatts of wind power.