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Magnus effect model aircraft are experimental and hobbyist-built remote-controlled (R/C) planes that use spinning cylinders, or rotors, instead of traditional wings to generate lift.

417,762 görüntüleme • 8 ay önce •via X (Twitter)

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🇺🇸 The empire of aircraft carriers No nation in history has built, deployed, and fought with aircraft carriers on the scale of the United States. America has built more than 80 fleet aircraft carriers and over 120 escort carriers, more than any other country by a massive margin. From World War II, Korea, Vietnam, the Gulf War, Afghanistan, Iraq, and countless operations across the globe, U.S. carriers have been at the center of American military power for nearly a century. At the height of World War II, American shipyards launched carriers at a pace the world had never seen before. While enemies struggled to replace losses, the U.S. kept launching new flattops and filling them with thousands of aircraft. Today, the U.S. Navy operates 11 nuclear powered supercarriers, each capable of carrying an entire air wing of advanced fighters, surveillance aircraft, helicopters, and support assets. The largest and most powerful aircraft carriers ever built are American: ⚓ Nimitz-class ⚓ Gerald R. Ford class Displacing more than 100,000 tons and powered by nuclear reactors, these floating airbases can strike targets, enforce no fly zones, support allies, and project power anywhere on Earth. For nearly 80 years, every major navy has studied the aircraft carrier. Many nations built aircraft carriers. Only one nation built them in numbers so vast that they helped win wars, shape the modern world, and make the aircraft carrier the ultimate symbol of naval power. 🇺🇸 The United States.

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🇨🇳🇺🇲CHINA says New Y-30 Transport Will Outperform U.S. C-130J in Payload and Power. China's state-affiliated media and a recent analysis in Aerospace Knowledge (published by Beihang University) have highlighted the Y-30 as a next-generation medium-lift tactical transport aircraft intended to outperform the Lockheed Martin C-130J Super Hercules in several key areas. The Y-30 is a four-engine turboprop developed by Shaanxi Aircraft Industry Corporation (under AVIC). It completed its maiden flight in December 2025 and remains in the early prototype/testing phase, with no publicly confirmed production schedule or final operational specifications from official Chinese sources. According to the Chinese analysis, the Y-30 is positioned to surpass the C-130J in: 🔺️Engine power — Powered by four indigenous AEP-500 (or EP-500) turboprops, claimed to deliver significantly higher output than the C-130J's Rolls-Royce AE2100D3 engines. 🔺️Payload capacity — Targeted at around 30 tonnes (some reports mention up to 35 tonnes in certain configurations), compared to the C-130J's typical maximum payload of roughly 19–21 tonnes. 🔺️Structural design and materials — Extensive use of composites for reduced weight and improved strength, versus the C-130's more traditional all-metal airframe. 🔺️Avionics and flight control software — Modern integrated systems offering potential advantages in automation and performance.

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I just built my own wiki generator plugin for my agents. My agents can now generate wikis for anything I ask. One of my favorite wikis is called PaperWiki. This is a great example of what Andrej Karpathy describes. It uses obsidian vaults to organize papers, retrieve LLM-generated summaries, diagrams, and other advanced views for paper exploration. When Obsidian UI is not enough, I use my own artifact generator inside my agent orchestrator (see clip for example). This allows my agents to build any kind of view or exploration feature that I need. The papers are all curated with automations and several rules/patterns I have manually built over the years. On the surface, this looks basic. But behind the scenes, there are advanced search capabilities, connections, metadata, derived data, and other interesting bits of information that are extremely useful for my research agents. This is mostly built for agents. The artifact preview is just a high-level way to validate and quickly assess the quality of the wiki, suggest improvements, and it's also great for research. I use tobi lutke's qmd for all search capabilities. Everything is markdown. The summaries and even the diagrams. The wiki updates on its own based on several automations I have optimized over the past couple of weeks. The wiki grows and self-improves based on several requirements important for my research use cases. This is as personalized as it gets. There is nothing like it out there. And I use my research expertise to continue improving it over time. This is a vanilla wiki. There are so many things I want to build on top of this. Different aggregations, views, artifacts, etc. All to help automate more of my research work and accelerate productivity. I think the biggest leverage here is how powerful this could be for discovery and experimentation. One of my goals is to use it to find deeper connections and insights that would otherwise elude the top human researchers and use those to generate interesting new hypotheses and research experiments. That way, my agents can use autoresearch to explore research ideas at the frontier. Stay tuned for more.

elvis

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