The FBI has charged a US man with creating more than 10,000 sexually explicit and abusive images of children, which he allegedly generated using a popular artificial intelligence tool. Authorities also accused the man, 42-year-old Steven Anderegg, of sending pornographic AI-made images to a 15-year-old boy over Instagram. Anderegg crafted about 13,000 "hyper-realistic images of nude and semi-clothed prepubescent children", prosecutors stated in an indictment released on Monday, often images depicting children touching their genitals or being sexually abused by adult men. Evidence from the Wisconsin man's laptop allegedly showed he used the popular Stable Diffusion AI model, which turns text descriptions into images. Anderegg's charges came after the National Center for Missing & Exploited Children (NCMEC) received two reports last year that flagged his Instagram account, which prompted law enforcement officials to monitor his activity on the social network, obtain information from Instagram and eventually obtain a search warrant.

The US is widely seen as the global leader in artificial intelligence, thanks to companies like OpenAI, Google, and Meta. But the US government says it needs help from other nations to manage the risks posed by AI technology. At an international summit on AI Safety in Seoul on Tuesday, the US delivered a message from Secretary of Commerce Gina Raimondo announcing that a global network of AI safety institutes spanning the US, UK, Japan, Canada, and other allies will collaborate to contain the technology's risks. She also urged other countries to join up. "Recent advances in AI carry exciting, life-changing potential for our society, but only if we do the hard work to mitigate the very real dangers," Secretary Raimondo said in a statement released ahead of the announcement.

A unique online game of political skill is engaging players and users not just from across America but from all over the world -- who are learning about the American political system, including the Electoral College, especially as the 2024 presidential election season heats up. Mark J. Penn, chair and CEO of Stagwell Inc., is the creator of a virtual political game of strategy called TwoSeventy. "This is more or less the only serious political online game right now," Penn told Fox News Digital in an interview. "There are online games in which you can catch sharks, kill Mafiosi, shoot people -- but it's pretty rare for you to be able to play a sophisticated political game where you take on the characters in the campaigns and aim to become president," he said. "It's pretty rare for you to be able to play a sophisticated political game where you take on the characters in the campaigns and aim to become president," said Mark Penn, creator of the online game called TwoSeventy.

The Iran-backed Houthi rebels in Yemen claimed on Tuesday they shot down an American drone over the impoverished Arab country. The U.S. military did not immediately acknowledge the claim. If confirmed, this would be the second MQ-9 Reaper drone downed by the Houthis over the past week as they press their campaign over the Israel-Hamas war in the Gaza Strip. Last Friday, the Houthis claimed downing an American drone over the province of Marib, hours after footage circulated online of what appeared to be the wreckage of an MQ-9 Reaper. And early Saturday, a vessel also came under attack in the Red Sea.

The first 16 companies have signed up to the voluntary artificial intelligence safety standards introduced at the Bletchley Park summit, Rishi Sunak has said on the eve of the event's follow-up in Seoul. But the standards have faced criticism for lacking teeth, with signatories committing only to voluntarily "work toward" information sharing, "invest" in cybersecurity and "prioritise" research into societal risks. "These commitments ensure the world's leading AI companies will provide transparency and accountability on their plans to develop safe AI," Sunak said. "It sets a precedent for global standards on AI safety that will unlock the benefits of this transformative technology." Included in the 16 are Zhipu.ai, The presence of signatories from countries that have been less willing to bind national champions to safety regulation is a benefit of the lighter touch, the government says.

Experts from around the globe kicked off their two-day discussions for nuclear arms reduction in Yokohama on Tuesday, with the impact of artificial intelligence on the agenda. The fourth meeting of the International Group of Eminent Persons for a World without Nuclear Weapons is themed on rebuilding the arms control system with the Nuclear Nonproliferation Treaty at the center. The 15 experts from nuclear haves and have-nots including such nuclear superpowers as the United States, China and Russia, some of whom are joining online, will also focus on the risks posed to nuclear disarmament by artificial intelligence and other new technologies. Foreign Minister Yoko Kamikawa said in a video message to the meeting that the Russian invasion of Ukraine, North Korea's nuclear and missile development and rising tensions in the Middle East have further deepened divisions and confrontations in the world. That is why it is necessary to strongly emphasize the importance of the NPT regime, which is the foundation of nuclear disarmament, she stressed.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. New federal certification rules finalized Monday for train dispatchers and signal repairmen will set minimum standards to counteract the investor pressure on railroads to continually cut costs while making sure those employees have the skills they need to operate all the high-tech systems on today's trains. The new Federal Railroad Administration rules are the latest steps in the agency's broad efforts to improve rail safety since the disastrous East Palestine derailment in Ohio last year although these rules were in the works years before that train crash. FRA Administrator Amit Bose said in an interview with The Associated Press that both these crafts of workers are responsible for some of the advanced technology railroads rely on like the assortment of trackside detectors that help spot mechanical problems before they can cause derailments, so it made sense to set certification standards for them.

Japan aims to win a 30% share of the global market for software-defined vehicles designed to improve performance by upgrading software rather than hardware, the industry and transport ministries said Monday. The target was included in a new strategy released by the ministries for software development for next-generation vehicles with advanced digital technologies. The strategy calls on the public and private sectors to work together on research and development of in-vehicle semiconductors and the standardization of SDV systems to better compete against leading U.S. and Chinese makers of self-driving and so-called connected vehicles. Estimating that global SDV sales will reach 41 million units in 2030 and 64 million units in 2035, the strategy sets sales goals for Japanese makers at 12 million units in 2030 and 19 million units five years later. Besides software development, it urges all Japanese companies across industries to cooperate in capitalizing on data on new services including smart transportation and offering such services.

Computational simulation is a discipline that has been around for 80 years or so and that has emerged as a cornerstone tool across various scientific disciplines, facilitating the prediction of physical phenomena and enabling engineers to refine designs before costly experimental setups are pursued. Traditionally, these simulations have relied heavily on mathematical formulations, often expressed through partial differential equations (PDEs), to model complex systems in fields such as structural mechanics or fluid dynamics [1]. However, with the advent of the information era--the so-called fourth paradigm of science [2]--, a shift towards data-driven approaches, particularly deep learning algorithms, has garnered attention due to their ability to address the limitations of traditional methods, including handling nonlinear dynamics under real-time restrictions [3]. Deep learning algorithms, while powerful, are often computationally demanding and require extensive datasets, posing challenges in terms of scalability and generalization [4]. To address these challenges, recent research has explored novel architectures, such as geometric deep learning, which leverage problem structures to enhance performance and reduce data consumption [5-8]. This paradigm shift, which imposes specific constraints related to problem symmetries, has opened new avenues for learning from irregular and unstructured data representations, such as graphs [9]. At the same time, traditional mesh-based representations have long been favoured in modelling complex physical systems, offering adaptability and accuracy across various domains, from aerodynamics [10] to structural mechanics [11]. Despite their advantages, mesh representations have received relatively little attention in the realm of machine learning, where grid-based approaches dominate due to their compatibility with convolutional neural network (CNN) architectures [12]. Nonetheless, recent efforts have explored the potential of adaptive mesh representations in predicting the dynamics of physical systems, showcasing their ability to allocate computational resources optimally and adaptively change discretization during simulations [13].

The rise of Generative AI (GenAI) brings about transformative potential across sectors, but its dual-use nature also amplifies risks. Governments globally are grappling with the challenge of regulating GenAI, balancing innovation against safety. China, the United States (US), and the European Union (EU) are at the forefront with initiatives like the Management of Algorithmic Recommendations, the Executive Order, and the AI Act, respectively. However, the rapid evolution of GenAI capabilities often outpaces the development of comprehensive safety measures, creating a gap between regulatory needs and technical advancements. A workshop co-organized by Google, University of Wisconsin, Madison (UW-Madison), and Stanford University aimed to bridge this gap between GenAI policy and technology. The diverse stakeholders of the GenAI space -- from the public and governments to academia and industry -- make any safety measures under consideration more complex, as both technical feasibility and regulatory guidance must be realized. This paper summarizes the discussions during the workshop which addressed questions, such as: How regulation can be designed without hindering technological progress? How technology can evolve to meet regulatory standards? The interplay between legislation and technology is a very vast topic, and we don't claim that this paper is a comprehensive treatment on this topic. This paper is meant to capture findings based on the workshop, and hopefully, can guide discussion on this topic.