Excavations also revealed a large bread oven and fossilized dough. Breakthroughs, discoveries, and DIY tips sent every weekday. When you think of ancient Egypt, you might imagine towering pyramids, majestic temples, and the noseless Great Sphinx of Giza. But the iconic civilization produced many more architectural marvels than the monuments it's best known for today, and one such example has just come to light in the sands of the Sinai. Archaeologists working in the northern region of Sinai--the Egyptian peninsula bordering Israel--have discovered a military fort from ancient Egypt's New Kingdom era (1550-1077 BCE) along the Horus Military Road.

The 1,400-year-old'bingo' is the oldest known facility of its kind. Breakthroughs, discoveries, and DIY tips sent every weekday. Archaeologists have discovered South Korea's earliest known ice storage chamber at the site of one of the nation's most historically significant royal castles. At over 1,400 years old, the underground facility offers an unprecedented look into feudal Korean culture's architectural complexities and advancements. Researchers uncovered the ice storage bunker while conducting the seventeenth excavation survey of Busosanseong Fortress located about 90 miles south of Seoul in South Chungcheong Province.

Automated structural defect segmentation in civil infrastructure faces a critical challenge: achieving high accuracy while maintaining computational efficiency for real-time deployment. This paper presents FORTRESS (Function-composition Optimized Real-Time Resilient Structural Segmentation), a new architecture that balances accuracy and speed by using a special method that combines depthwise separable convolutions with adaptive Kolmogorov-Arnold Network integration. FORTRESS incorporates three key innovations: a systematic depthwise separable convolution framework achieving a 3.6x parameter reduction per layer, adaptive TiKAN integration that selectively applies function composition transformations only when computationally beneficial, and multi-scale attention fusion combining spatial, channel, and KAN-enhanced features across decoder levels. The architecture achieves remarkable efficiency gains with 91% parameter reduction (31M to 2.9M), 91% computational complexity reduction (13.7 to 1.17 GFLOPs), and 3x inference speed improvement while delivering superior segmentation performance. Evaluation on benchmark infrastructure datasets demonstrates state-of-the-art results with an F1- score of 0.771 and a mean IoU of 0.677, significantly outperforming existing methods including U-Net, SA-UNet, and U- KAN. The dual optimization strategy proves essential for optimal performance, establishing FORTRESS as a robust solution for practical structural defect segmentation in resource-constrained environments where both accuracy and computational efficiency are paramount. Comprehensive architectural specifications are provided in the Supplemental Material. Source code is available at URL: https://github.com/faeyelab/fortress-paper-code.

The world may be going to hell, but the writer and director James Gunn has graced it with a sunshine "Superman." The most recent installments in the franchise--Zack Snyder's diptych "Man of Steel" (2013) and "Batman v Superman: Dawn of Justice" (2016)--had a hectic, howling, near-apocalyptic sense of tragedy, but Gunn's vision is bright, chipper, and sentimental. A title card announces that Superman has endured his first defeat, and the hero (played by David Corenswet) is shown tumbling from the sky and slamming with a sickening thud onto the surface of a frozen wasteland, where he lies prostrate, spitting red blood on the snow. Fear not: no sooner does the wounded combatant put his lips together and whistle for Krypto than his faithful and frisky canine companion arrives and drags his master back to the Fortress of Solitude. There, loyal robots examine the patient and, by exposing him to sunlight, begin to heal him.

The rapid advancement of large language models (LLMs) introduces dual-use capabilities that could both threaten and bolster national security and public safety (NSPS). Models implement safeguards to protect against potential misuse relevant to NSPS and allow for benign users to receive helpful information. However, current benchmarks often fail to test safeguard robustness to potential NSPS risks in an objective, robust way. We introduce FORTRESS: 500 expert-crafted adversarial prompts with instance-based rubrics of 4-7 binary questions for automated evaluation across 3 domains (unclassified information only): Chemical, Biological, Radiological, Nuclear and Explosive (CBRNE), Political Violence & Terrorism, and Criminal & Financial Illicit Activities, with 10 total subcategories across these domains. Each prompt-rubric pair has a corresponding benign version to test for model over-refusals. This evaluation of frontier LLMs' safeguard robustness reveals varying trade-offs between potential risks and model usefulness: Claude-3.5-Sonnet demonstrates a low average risk score (ARS) (14.09 out of 100) but the highest over-refusal score (ORS) (21.8 out of 100), while Gemini 2.5 Pro shows low over-refusal (1.4) but a high average potential risk (66.29). Deepseek-R1 has the highest ARS at 78.05, but the lowest ORS at only 0.06. Models such as o1 display a more even trade-off between potential risks and over-refusals (with an ARS of 21.69 and ORS of 5.2). To provide policymakers and researchers with a clear understanding of models' potential risks, we publicly release FORTRESS at https://huggingface.co/datasets/ScaleAI/fortress_public. We also maintain a private set for evaluation.

The indie video game scene is currently dominated by two unassailable genre titans: the rogue-like and the deck-builder. The first is a type of action adventure in which players explore procedurally generated landscapes, where they battle enemies, level up and then die – whereupon they start all over again from scratch. The latter is about building decks of collectible cards (think Pokémon or Magic: The Gathering, but digital) and fighting with them. Titles that combine both in interesting ways – such as Balatro and Slay the Spire – can become huge crossover hits. But the market is getting saturated and so developers are having to find new genres to mix into this potent game design cocktail.

This work introduces Amorphous Fortress Online -- a web-based platform where users can design petri-dish-like environments and games consisting of multi-agent AI characters. Users can play, create, and share artificial life and game environments made up of microscopic but transparent finite-state machine agents that interact with each other. The website features multiple interactive editors and accessible settings to view the multi-agent interactions directly from the browser. This system serves to provide a database of thematically diverse AI and game environments that use the emergent behaviors of simple AI agents.

Drone photographs taken of a 3,000-year-old "mega fortress" nestled deep in the Caucasus Mountains reveal the settlement is actually 40 times larger than archaeologists once thought. New aerial images of the Dmanisis Gora settlement, located in present-day Georgia, show a large land area well guarded by steep gorges and plastered with various stone structures and field systems. Though the structure's inner fortress has been well-documented for several years, new mapping made possible thanks to a simple hobbyist drone helped redraw the Bronze Age monument's boundaries. Researchers shared their findings this week in the journal Antiquity. The Dmanisis Gora is one of several documented fortresses that popped between the Middle East and the Eurasian Steppe sometime between 1,500 and 500 BCE.

Thousands of magical projectiles whizz across the horizon, arachnoid infantry hack the armor of our troops to pieces. As Orc Warlocks, we throw ourselves into battle, a water spirit at our side pushing back the enemy troops, but General Thrall can barely hold the line. The intro to The War Within is a strongly staged invasion on the beach, which then leads into a siege battle around a dwarven fortress. The intro to The War Within is a strongly staged invasion on the beach, which then leads into a siege battle around a dwarven fortress. The intro to The War Within is a strongly staged invasion on the beach, which then leads into a siege battle around a dwarven fortress.

We explore the generation of diverse environments using the Amorphous Fortress (AF) simulation framework. AF defines a set of Finite State Machine (FSM) nodes and edges that can be recombined to control the behavior of agents in the `fortress' grid-world. The behaviors and conditions of the agents within the framework are designed to capture the common building blocks of multi-agent artificial life and reinforcement learning environments. Using quality diversity evolutionary search, we generate diverse sets of environments. These environments exhibit certain types of complexity according to measures of agents' FSM architectures and activations, and collective behaviors. Our approach, Quality Diversity in Amorphous Fortress (QD-AF) generates families of 0-player games akin to simplistic ecological models, and we identify the emergence of both competitive and co-operative multi-agent and multi-species survival dynamics. We argue that these generated worlds can collectively serve as training and testing grounds for learning algorithms.