DONALD TRUMP IS FLYING TO IRELAND TO GOLF AT HIS OWN RESORT AND YOU'RE PAYING FOR THE JET FUEL September 12th and 13th. Doonbeg, County Clare. Trump International Golf Links Ireland. Owned by Trump. Profiting Trump. Guarded by your tax dollars He'll slap a fig leaf of "official business" on it first — a quick meet-and-greet with embassy staff — then it's straight to the fairway at a course that already vacuumed up $10,755,683 in golf revenue off the taxpayer-funded motorcade that follows him everywhere Last time around this exact resort pulled in an estimated $21.5 million for the Trump family in just two years while Trump sat in the Oval Office His sons run the "day to day" now, they say. Cute. The money still lands in the same family bank account either way Secret Service footing security. State Department footing logistics. American taxpayers footing the bill for a golf vacation that fattens the Trump Organization's wallet on foreign soil This isn't a president taking a break. This is a sitting president using Air Force One as a shuttle bus to his own cash register Every dollar spent protecting him on that golf course is a dollar that could've gone to a VA hospital, a food bank, a disaster relief fund Ordinary Americans get furloughs, funding freezes, and "tighten your belt" lectures. Trump gets a taxpayer-subsidized golf holiday at a resort with his name on the gate This is the same family that turned the presidency into a revenue stream in year one and never once looked back They are not going to stop grifting off this office as long as we let them pay for it

There have already been 2 KOL farming incidents in the ARC ecosystem First, the OTC bridge, where people bought USDC at 60x the real price, then started vamping over 300K USDC after it got shilled by vamp KOLs Second, trading through some unclear bridge mechanism into a USD platform, handled by one person, while ARC USDC is not even officially live yet What comes next??? It is obvious that the people promoting this are cancer across multiple chains, They come in, take profit in one day, then leave everyone else stuck there holding losses Why not just build for the ecosystem instead, and start trading when ARC officially launches its bridge and mainnet announcement? You are not going to find the next $CASHCAT like this, $CASHCAT started in a fair way, without forcing too much hype Excessive FOMO is never healthy for a chain ecosystem

🗺️ Even frontier GPT-5 succeeds on just 14.4% of real-world spatial tasks. A new benchmark goes beyond staring at a static image and exposes how weak AI agents still are at active spatial reasoning. Title: SpatialWorld: Benchmarking Interactive Spatial Reasoning of Multimodal Agents in Real-World Tasks URL: 📝 Overview SpatialWorld measures whether multimodal LLMs can solve tasks by actively exploring 3D environments from a vision-only, egocentric viewpoint. It unifies eight different simulators across indoor, outdoor, and digital-game settings under a shared protocol, and evaluates 15 frontier models on 760 human-annotated tasks. The agent gets no prior map and no reference solution; it has to look, move, and decide on its own. ❓ Challenges Solved Prior spatial-reasoning benchmarks relied on passive evaluation via static VQA or pre-recorded video. That can't capture the interactive spatial understanding the real world demands, where an agent must move its own viewpoint to gather visual evidence and replan on the fly under partial observability. There was a large gap between recognizing a static scene and actually moving through an unfamiliar space to get a task done. 💡 Methodology & Proposed Approach ・The task is framed as a vision-only POMDP (Partially Observable Markov Decision Process) ・The agent receives only a natural-language goal and a single native-resolution egocentric RGB image, with no depth, maps, or semantic metadata ・Actions are issued through a high-level text interface covering navigation, viewpoint control, object interaction, and task completion ・It integrates eight backends: indoor (AI2-THOR, ProcTHOR, VirtualHome), outdoor (CARLA, EmbodiedCity), and digital games (Block3D, Snake3D, Rubik's Cube) ・Success is judged by whether the final terminal state satisfies the goal, not by matching the trajectory, and is validated by human annotators ・Beyond success rate, it measures step efficiency against human reference trajectories to surface inefficient behavior 🎯 Use Cases It offers a unified, fair way to evaluate the spatial abilities of home robots and autonomous agents before real-world deployment. It can systematically diagnose where long-horizon tasks that combine navigation and manipulation break down, serving as a rigorous testbed for improving spatial-reasoning models. 📊 Experimental Results ・Across 15 frontier models, physical-task success was 14.4% for GPT-5, 12.2% for Qwen-3.5-397B, 9.2% for Gemini-3.1-Pro, and 9.2% for Kimi-K2.5 ・On digital games, Gemini-3.1-Pro led at 39.0%, followed by GPT-5 at 36.4% ・By complexity, interaction-only tasks averaged 50.2%, navigation-only dropped to 8.6%, and combined navigation-and-interaction collapsed to just 4.2% ・Models with similar success rates showed very different efficiency scores, revealing heavy reliance on trial-and-error exploration ・Model rankings shifted dramatically across environments, with no single model dominating every category #AIAgents# #SpatialReasoning#