Why the world's militaries are scrambling to create their own Starlink The reliable internet connections provided by Starlink offer a huge advantage on the battlefield. Starlink's satellite constellation provides a reliable internet connection to almost anywhere on Earth, conferring an advantage on the modern battlefield. But it is also run by controversial billionaire Elon Musk, presenting a risk to militaries that could easily find themselves cut off. So, now countries are racing to build their own version. The Starlink network consists of almost 10,000 satellites that offer internet connections across most of the planet via small dishes on the ground.

The US and Iran are trading blows in the Gulf with a simple drone that costs as little as $50,000 to make. But why is a slow, cheap and relatively primitive drone seeing use in 2026 alongside hypersonic missiles and stealth jets? Iran invented the relatively simple Shahed 136 attack drone, but is now fending off US copies launched against it in combat. Why, when the US military has expensive, cutting-edge and hi-tech weapons, is it making flimsy drones powered by a motorbike engine? Iranian company Shahed Aviation Industries originally designed the 136.

Oshen's robotic sailboats are powered by the wind and the sun The UK's Royal Navy may return to the age of sail, with a new demonstration involving a flotilla of small, wind-propelled robot boats. Made by Oshen in Plymouth, UK, the vessels, known as C-Stars, are just 1.2 metres long and weigh around 40 kilos. Solar panels power navigation, communications and sensors, while a sail provides propulsion. Deployed as a constellation, the small vessels act as a wide-area sensor network. How the US military wants to use the world's largest aircraft "The simplest way of describing C-Stars is as self-deploying, station-keeping ocean buoys," says Oshen CEO Anahita Laverack .

The ideas presented in George Lakoff and Srini Narayanan's The Neural Mind are fascinating, but the writing is far less compelling This is a book review in two parts. The first is about the ideas presented in The Neural Mind: How brains think, which are fascinating. The second is about the actual experience of reading it. The book tackles one of the biggest questions in neuroscience: how do neurons perform all the different kinds of human thought possible, from planning motor actions to composing sentences and musing about philosophy? The authors have very different perspectives.

As the world looks to incorporate more renewables into energy grids, centuries-old systems that can balance supply and demand are being reappraised and innovated upon.

The evolution toward sixth-generation wireless systems positions intelligence as a native network capability, fundamentally transforming the design of radio access networks (RANs). Within this vision, Semantic-native communication and agentic intelligence are expected to play central roles. SemCom departs from bit-level fidelity and instead emphasizes task-oriented meaning exchange, enabling compact SC and introducing new performance measures such as semantic fidelity and task success rate. Agentic intelligence endows distributed RAN entities with goal-driven autonomy, reasoning, planning, and multi-agent collaboration, increasingly supported by foundation models and knowledge graphs. In this work, we first introduce the conceptual foundations of SemCom and agentic networking, and discuss why existing AI-driven O-RAN solutions remain largely bit-centric and task-siloed. We then present a unified taxonomy that organizes recent research along three axes: i) semantic abstraction level (symbol/feature/intent/knowledge), ii) agent autonomy and coordination granularity (single-, multi-, and hierarchical-agent), and iii) RAN control placement across PHY/MAC, near-real-time RIC, and non-real-time RIC. Based on this taxonomy, we systematically introduce enabling technologies including task-oriented semantic encoders/decoders, multi-agent reinforcement learning, foundation-model-assisted RAN agents, and knowledge-graph-based reasoning for cross-layer awareness. Representative 6G use cases, such as immersive XR, vehicular V2X, and industrial digital twins, are analyzed to illustrate the semantic-agentic convergence in practice. Finally, we identify open challenges in semantic representation standardization, scalable trustworthy agent coordination, O-RAN interoperability, and energy-efficient AI deployment, and outline research directions toward operational semantic-agentic AI-RAN.

Despite the promising capability of multimodal foundation models, their application to the generation of meteorological products and services remains nascent. To accelerate aspiration and adoption, we explore the novel use of a vision language model for writing the iconic Shipping Forecast text directly from video-encoded gridded weather data. These early results demonstrate promising scalable technological opportunities for enhancing production efficiency and service innovation within the weather enterprise and beyond.