Stellarators are magnetic confinement devices under active development to deliver steady-state carbon-free fusion energy. Their design involves a high-dimensional, constrained optimization problem that requires expensive physics simulations and significant domain expertise. Recent advances in plasma physics and open-source tools have made stellarator optimization more accessible. However, broader community progress is currently bottlenecked by the lack of standardized optimization problems with strong baselines and datasets that enable data-driven approaches, particularly for quasi-isodynamic (QI) stellarator configurations, considered as a promising path to commercial fusion due to their inherent resilience to current driven disruptions. Here, we release an open dataset of diverse QI-like stellarator plasma boundary shapes, paired with their ideal magnetohydrodynamic (MHD) equilibria and performance metrics. We generated this dataset by sampling a variety of QI fields and optimizing corresponding stellarator plasma boundaries. We introduce three optimization benchmarks of increasing complexity: (1) a single objective geometric optimization problem, (2) a "simple-to-build" QI stellarator, and (3) a multi-objective ideal-MHD stable QI stellarator that investigates trade-offs between compactness and coil simplicity. For every benchmark, we provide reference code, evaluation scripts, and strong baselines based on classical optimization techniques. Finally, we show how learned models trained on our dataset can efficiently generate novel, feasible configurations without querying expensive physics oracles. By openly releasing the dataset along with benchmark problems and baselines, we aim to lower the entry barrier for optimization and machine learning researchers to engage in stellarator design and to accelerate cross-disciplinary progress toward bringing fusion energy to the grid.

In AI research and practice, rigor remains largely understood in terms of methodological rigor -- such as whether mathematical, statistical, or computational methods are correctly applied. We argue that this narrow conception of rigor has contributed to the concerns raised by the responsible AI community, including overblown claims about the capabilities of AI systems. Our position is that a broader conception of what rigorous AI research and practice should entail is needed. We believe such a conception -- in addition to a more expansive understanding of (1) methodological rigor -- should include aspects related to (2) what background knowledge informs what to work on (epistemic rigor); (3) how disciplinary, community, or personal norms, standards, or beliefs influence the work (normative rigor); (4) how clearly articulated the theoretical constructs under use are (conceptual rigor); (5) what is reported and how (reporting rigor); and (6) how well-supported the inferences from existing evidence are (interpretative rigor). In doing so, we also provide useful language and a framework for much-needed dialogue about the AI community's work by researchers, policymakers, journalists, and other stakeholders.

Recent advances in Large Multimodal Models (LMMs) have revolutionized their reasoning and Optical Character Recognition (OCR) capabilities. However, their complex logical reasoning performance on text-rich images remains underexplored. To bridge this gap, we introduce LogicOCR, a benchmark comprising 2780 questions with two subsets, i.e., LogicOCR-Gen with 1100 multi-choice questions on generated images, and LogicOCR-Real with 1680 meticulously designed free-form questions on real-world images. For constructing LogicOCR-Gen, we first curate a text corpus from the Chinese National Civil Servant Examination, and customize an automatic pipeline to steer GPT-Image-1 to generate images with varied layouts and fonts, ensuring contextual relevance and visual realism. Then, the generated images are manually verified. We evaluate a range of representative LMMs under Chain-of-Thought (CoT) and direct-answer settings. Our multi-dimensional analysis reveals key insights, such as the impact of test-time scaling, input modality differences, and sensitivity to visual-text orientation. Notably, LMMs still lag in multimodal reasoning compared to text-only inputs, indicating that they have not fully bridged visual reading with reasoning. Moreover, we propose TextCue, a training-free method that enhances LMMs' perception of image regions containing important text cues for solving questions. We leverage LMMs' attention maps and an off-the-shelf text segmentation specialist to determine the region, which is then cropped and enlarged to augment the original image. Experiments show its effectiveness, e.g., a 1.8% accuracy gain over LLaVA-OV-1.5-8B under the CoT setting. Our benchmark is available at https://github.com/MiliLab/LogicOCR.

With the ever-growing adoption of artificial intelligence (AI), AI-based software and its negative impact on the environment are no longer negligible, and studying and mitigating this impact has become a critical area of research. However, it is currently unclear which role environmental sustainability plays during AI adoption in industry and how AI regulations influence Green AI practices and decision-making in industry. We therefore aim to investigate the Green AI perception and management of industry practitioners. To this end, we conducted a total of 11 interviews with participants from 10 different organizations that adopted AI-based software. The interviews explored three main themes: AI adoption, current efforts in mitigating the negative environmental impact of AI, and the influence of the EU AI Act and the Corporate Sustainability Reporting Directive (CSRD). Our findings indicate that 9 of 11 participants prioritized business efficiency during AI adoption, with minimal consideration of environmental sustainability. Monitoring and mitigation of AI's environmental impact were very limited. Only one participant monitored negative environmental effects. Regarding applied mitigation practices, six participants reported no actions, with the others sporadically mentioning techniques like prompt engineering, relying on smaller models, or not overusing AI. Awareness and compliance with the EU AI Act are low, with only one participant reporting on its influence, while the CSRD drove sustainability reporting efforts primarily in larger companies. All in all, our findings reflect a lack of urgency and priority for sustainable AI among these companies. We suggest that current regulations are not very effective, which has implications for policymakers. Additionally, there is a need to raise industry awareness, but also to provide user-friendly techniques and tools for Green AI practices.

The continuous monitoring of the interactions between cyber-physical components of any industrial control system (ICS) is required to secure automation of the system controls, and to guarantee plant processes are fail-safe and remain in an acceptably safe state. Safety is achieved by managing actuation (where electric signals are used to trigger physical movement), dependent on corresponding sensor readings; used as ground truth in decision making. Timely detection of anomalies (attacks, faults and unascertained states) in ICSs is crucial for the safe running of a plant, the safety of its personnel, and for the safe provision of any services provided. We propose an anomaly detection method that involves accurate linearization of the non-linear forms arising from sensor-actuator(s) relationships, primarily because solving linear models is easier and well understood. We accomplish this by using a well-known water treatment testbed as a use case. Our experiments show millisecond time response to detect anomalies, all of which are explainable and traceable; this simultaneous coupling of detection speed and explainability has not been achieved by other state of the art Artificial Intelligence (AI)/ Machine Learning (ML) models with eXplainable AI (XAI) used for the same purpose. Our methods explainability enables us to pin-point the sensor(s) and the actuation state(s) for which the anomaly was detected. The proposed algorithm showed an accuracy of 97.72% by flagging deviations within safe operation limits as non-anomalous; indicative that slower detectors with highest detection resolution is unnecessary, for systems whose safety boundaries provide leeway within safety limits.

Karoline Leavitt's family member was swarmed by ICE agents while picking up son from school as child's father tell her to'self deport' Deaths from highly infectious virus are growing... as states brace for widespread outbreaks My book on the Kennedys was used as a'mistress manual' by Olivia Nuzzi... then this wannabe Carolyn Bessette had the nerve to hound me with these outrageous texts: MAUREEN CALLAHAN Katy Perry's legal victory as judge orders disabled veteran to pay singer nearly $2m over Montecito mansion Trump reveals next DC renovation project to remove'Biden filth' after White House ballroom Cracker Barrel CEO whines that she got'fired by America' for woke redesign Kroger employee reveals shocking amount laundry products have increased by... 'biggest price jump I've seen in a single week' Hollywood heir, 23, whose mom Anne Heche died in horror car fireball has secret LOVE CHILD with 43-year-old... now she's telling all Missing Melodee Buzzard's mom'left her daughter with strangers she met at the zoo' Rachel Zoe reveals why she dumped husband of 26 years... and if she has started dating again Horrific moment cops found body of Cowboys star Marshawn Kneeland after he shot himself at end of 145 mph chase'This is pretty lurid' Jenny McCarthy, 53, reveals health emergency that involved NINE surgeries, her'teeth falling out' and'growth' on her eyeballs Maryland grandma, 58, dragged across floor after being deported to country she'has never even visited' Campbell's FIRES executive secretly recorded saying its soups are full of'bioengineered meat' and made for'poor people' Campbell's Soup has fired the executive caught in a secret recording insulting customers and claiming the company's products were filled with bioengineered meat. Vice President and Chief Information Security Officer Martin Bally was originally placed on administrative leave after a lawsuit against Campbell's was filed last week and the audio recording was released. In the audio, a speaker identified as Bally was heard saying: 'We have s**t for f***king poor people. It's not healthy now that I know what the f**'s in it.' The voice, alleged to be Bally, also claimed that the chicken used in the brand's soups'came from a 3D printer.' Campbell's revealed on Wednesday that their investigation concluded that the voice on the secret recording was Bally and the executive was removed from the company on Tuesday.

What is in the 28-point US plan for Ukraine? Why is Europe opposing Trump's peace plan? Is the fall of Pokrovsk inevitable? 'A corruption scandal may well end the Ukraine war' Russia says talks to end Ukraine war'serious' but rules out concessions Russia says the United States-brokered talks to end the war with Ukraine are "serious", but its officials caution that an agreement is a long way off and Moscow would offer no major concessions to Kyiv. Kremlin spokesman Dmitry Peskov said in televised comments on Wednesday that the negotiations were ongoing and "the process is serious."

When you purchase through links in our articles, we may earn a small commission. AI is causing a DRAM apocalypse and it's affecting the whole PC market this holiday season. This year, Black Friday tech shoppers should heed one important message: Don't wait, buy now. Because certain components are skyrocketing in price--and it's expected to get even worse. DRAM prices, for example, have doubled in little more than a month. AI hyperscalers have snapped up whatever they can buy.

A push by military contractors could alter pending legislation that would have empowered servicemembers to repair equipment. Lobbyists are pitching a subscription service instead. Right to repair provisions in the National Defense Authorization Act, which would secure funding for the US military in 2026, are likely to be struck from the final language of the bill despite enjoying broad bipartisan support, sources familiar with ongoing negotiations tell WIRED. They say that provisions in the act enabling servicemembers to repair their own equipment are likely to be removed entirely, and replaced with a data-as-a-service subscription plan that benefits defense contractors. The right to repair has become a thorny issue in the military.

Karoline Leavitt's family member was swarmed by ICE agents while picking up son from school as child's father tell her to'self deport' Deaths from highly infectious virus are growing... as states brace for widespread outbreaks My book on the Kennedys was used as a'mistress manual' by Olivia Nuzzi... then this wannabe Carolyn Bessette had the nerve to hound me with these outrageous texts: MAUREEN CALLAHAN Katy Perry's legal victory as judge orders disabled veteran to pay singer nearly $2m over Montecito mansion Trump reveals next DC renovation project to remove'Biden filth' after White House ballroom Cracker Barrel CEO whines that she got'fired by America' for woke redesign Kroger employee reveals shocking amount laundry products have increased by... 'biggest price jump I've seen in a single week' Hollywood heir, 23, whose mom Anne Heche died in horror car fireball has secret LOVE CHILD with 43-year-old... now she's telling all Missing Melodee Buzzard's mom'left her daughter with strangers she met at the zoo' Rachel Zoe reveals why she dumped husband of 26 years... and if she has started dating again Horrific moment cops found body of Cowboys star Marshawn Kneeland after he shot himself at end of 145 mph chase'This is pretty lurid' Jenny McCarthy, 53, reveals health emergency that involved NINE surgeries, her'teeth falling out' and'growth' on her eyeballs Maryland grandma, 58, dragged across floor after being deported to country she'has never even visited' READ MORE: New'stone head' statue mysteriously appears on Easter Island One of the biggest mysteries surrounding Easter Island may finally be solved - as scientists pinpoint who built the iconic stone heads over 900 years ago. In the past, researchers assumed that the 12 to 80-ton statues would have required the combined efforts of hundreds of labourers to build and move. However, new archaeological evidence shows that the statues, known as moai, were not carved by a single powerful chiefdom. Instead, each moai was carved by a small clan or by an individual family, with as few as four to six people working on a single statue. Using a new 3D model of the island's main moai quarry, which you can explore below, archaeologists identified 30 unique'workshops' where the statues were produced.