Imagine a future where humans live in huge'space oases' on Mars – luxury indoor habitats made of heat-reflective material that grow their own food. Robots are sent into the vast Martian wilderness, where they explore without the risk of exhaustion, radiation poisoning or dust contamination. Enormous space stations and satellites are manufactured in orbit, AI is trusted to make critical decisions, and the whole solar system is connected by a vast internet network. While this sounds like science-fiction, the European Space Agency (ESA) hopes it will become a reality in just 15 years. In a new report, the agency – which represents more than 20 countries including the UK – outlines an ambitious vision for space exploration by 2040.

Israel activated a new aerial defense system – dubbed "Barak Magen" – for the first time on Sunday night, saying it intercepted and destroyed multiple Iranian drones. Israel activated a new aerial defense system – dubbed "Barak Magen," meaning "lightning shield" – for the first time on Sunday night, saying it intercepted and destroyed multiple Iranian drones. The Israeli Navy intercepted eight Iranian drones using the "Barak Magen" and its long-range air defense (LRAD) interceptor, which were launched from an Israeli navy Sa'ar 6 missile ship, the Israel Defense Forces (IDF) said in a statement. John Hannah, senior fellow at the National Security of America and the co-author of a report published earlier this month on Israel's defense against two massive Iranian missile attacks in 2024, told Fox News Digital on Monday that the air defense system "significantly enhances" the air and missile defense architecture of Israel's navy. "The Barak Magen is simply another arrow in the expanding quiver of Israel's highly sophisticated and increasingly diverse multi-tiered missile defense architecture – which was already, by leaps and bounds, the most advanced and experienced air defense system fielded by any country in the world," Hannah said.

Cyclone rapid intensification is the rapid increase in cyclone wind intensity, exceeding a threshold of 30 knots, within 24 hours. Rapid intensification is considered an extreme event during a cyclone, and its occurrence is relatively rare, contributing to a class imbalance in the dataset. A diverse array of factors influences the likelihood of a cyclone undergoing rapid intensification, further complicating the task for conventional machine learning models. In this paper, we evaluate deep learning, ensemble learning and data augmentation frameworks to detect cyclone rapid intensification based on wind intensity and spatial coordinates. We note that conventional data augmentation methods cannot be utilised for generating spatiotemporal patterns replicating cyclones that undergo rapid intensification. Therefore, our framework employs deep learning models to generate spatial coordinates and wind intensity that replicate cyclones to address the class imbalance problem of rapid intensification. We also use a deep learning model for the classification module within the data augmentation framework to di fferentiate between rapid and non-rapid intensification events during a cyclone. Our results show that data augmentation improves the results for rapid intensification detection in cyclones, and spatial coordinates play a critical role as input features to the given models. This paves the way for research in synthetic data generation for spatiotemporal data with extreme events. Introduction Over the past decade, the impacts of climate change have manifested in an alarming increase in the strength of tropical cyclones, characterised by elevated levels of precipitation and wind intensity, resulting in devastating consequences on a global scale [1, 2, 3]. Rappaport et al. [4] defined rapid intensification as a sudden surge in wind intensity exceeding 30 knots (35 miles / hour or 55 kilometres / hour) within 24 hours [5]. Forecasting the rapid intensification of high-category cyclones (Category 4 and 5) poses greater challenges due to their infrequent occurrence, in contrast to lower-category cyclones[6].

The Madden-Julian Oscillation, or MJO, is a significant weather pattern that affects weather, influencing rainfall, temperature, and even storm frequency and intensity. When the MJO is active, it can affect the weather globally. To better predict weather changes with 3-4 weeks in advance, we rely on the ability to predict the MJO's activity. Data-driven methods such as the ones that rely on deep neural networks have been recently employed to make such predictions. By examining existing MJO patterns, neural networks attempt to predict upcoming ones. However, while neural networks are robust enough to predict the MJO's activity, they do not provide confidence intervals for those predictions. To address this shortcoming, we use a model known as the "Gaussian process" or GP. This statistical tool is distinctive because it not only provides predictions but also quantifies the level of confidence in them.

Over the course of a three-day trip to the Middle East, President Trump and his emissaries from Silicon Valley have transformed the Persian Gulf from an artificial-intelligence neophyte into an A.I. power broker. They have reached an enormous deal with the United Arab Emirates to deliver hundreds of thousands of today's most advanced chips from Nvidia annually to build one of the world's largest data center hubs in the region, three people familiar with the talks said. The shipments would begin this year, and include roughly 100,000 chips for G42, an Emirati A.I. firm, with the rest going to U.S. cloud service providers. The administration revealed the agreement on Thursday in an announcement unveiling a new A.I. campus in Abu Dhabi supported by 5 gigawatts of electrical power. It would the largest such project outside of the United States and help U.S. companies serve customers in Africa, Europe and Asia, the administration said.

Underwater 3D scene reconstruction is crucial for underwater robotic perception and navigation. However, the task is significantly challenged by the complex interplay between light propagation, water medium, and object surfaces, with existing methods unable to model their interactions accurately. Additionally, expensive training and rendering costs limit their practical application in underwater robotic systems. Therefore, we propose T ensorized Underwater Gaussian Splatting (TUGS), which can effectively solve the modeling challenges of the complex interactions between object geometries and water media while achieving significant parameter reduction. TUGS employs lightweight tensorized higher-order Gaussians with a physics-based underwater Adaptive Medium Estimation (AME) module, enabling accurate simulation of both light attenuation and backscatter effects in underwater environments. Compared to other NeRF-based and GS-based methods designed for underwater, TUGS is able to render high-quality underwater images with faster rendering speeds and less memory usage. Extensive experiments on real-world underwater datasets have demonstrated that TUGS can efficiently achieve superior reconstruction quality using a limited number of parameters, making it particularly suitable for memory-constrained underwater UA V applications.

The RSF is trying to show that they don't need to reach Port Sudan by land in order to be able to have an impact there,

The administration of U.S. President Donald Trump is clearing a path for two key Persian Gulf allies to pursue their artificial intelligence ambitions -- and some of the biggest U.S. tech companies are seizing on that opening with plans to spend billions of dollars in the region. Under agreements with the U.S. expected to be unveiled in coming days, Saudi Arabia and the United Arab Emirates are poised to win wider access to advanced AI chips from Nvidia and Advanced Micro Devices that are considered the gold standard for running AI models. The deals are taking shape while President Donald Trump visits the Middle East seeking to forge deeper business ties that put U.S. technology initiatives at center stage. Even before any formal announcement of accords between the U.S. and its partners, news began to emerge of American companies readying expanded projects in the region.

On May 4, Sudan's paramilitary Rapid Support Forces (RSF) launched a barrage of suicide drones at Port Sudan, the army's de facto wartime capital on the Red Sea. The Sudanese Armed Forces (SAF) accused foreign actors of supporting the RSF's attacks and even threatened to sever ties with one of its biggest trading partners. The RSF surprised many with the strikes. It had used drones before, but never hit targets as far away as Port Sudan, which used to be a haven, until last week. "The strikes … led to a huge displacement from the city. Many people left Port Sudan," Aza Aera, a local relief worker, told Al Jazeera.

Former President Donald Trump is embarking this week on a high-stakes tour of the Persian Gulf region, targeting business deals and strategic partnerships with three oil-rich nations: Saudi Arabia, the United Arab Emirates and Qatar. The trip marks Trump's first major foreign visit of his new term and comes as nuclear negotiations with Iran drag on and as war continues between Israel and the Palestinian terror organization, Hamas, in the Gaza Strip. While business is the official focus, the backdrop is anything but calm. White House press secretary Karoline Leavitt described the mission as part of Trump's broader vision that "extremism is defeated [through] commerce and cultural exchanges." Under President Joe Biden, U.S. relations with Gulf states cooled, particularly after Biden vowed to make Saudi Crown Prince Mohammed bin Salman a "pariah" over the 2018 killing of journalist Jamal Khashoggi.