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[RADIO INFO] 本日オンエア！よろしくお願いします🐰 ニューアルバム『NOW』のことや最近digしているものについてお話しています🔍 FM宮崎「dig app!」 8月4日（日）18:00〜18:55 コメント出演 📻 #radiko# #15th_abemao# #digapp#

AI coding didn’t just help me build MacMater faster. It helped me notice the small frictions people live with every day. On macOS, there still isn’t a simple native way to right-click in Finder and instantly open a file or folder with the app you actually want. There also isn’t a clean built-in way to right-click and create a new file from your own templates. So people install one app for Finder tweaks. Another for clipboard history. Another for mouse gestures. Another for input switching. But ordinary people shouldn’t need a folder full of tiny utilities just to make their computer feel right. That became the idea behind MacMater: an all-in-one native Mac utility that brings these daily improvements together. Open with your favorite apps. Create new files from templates. Switch input methods automatically. Make your mouse feel better. Bring back anything you copied. AI wasn’t a magic button. It was more like a patient teammate. It helped me unfold ideas, question tradeoffs, rewrite messy thoughts, and keep asking: “Is this actually useful to a real person?” The biggest lesson: AI coding does not remove human judgment. It demands more of it. You still have to know what matters. You still have to say no. You still have to choose simplicity over cleverness. In the end, the best technology disappears. What remains is a small moment: someone opens their Mac, does their work, and feels like the machine finally understands them a little better.

Multiple protests involving social organizations, collectives of families of the disappeared, dissident teachers, peasant organizations, and transport workers broke out in Mexico City as the 2026 FIFA World Cup began

A few years from now, nobody is going to remember how many likes you got on a random post. They’ll remember how you made them feel. I learned that the hard way. Some of the posts I’m most proud of barely got noticed. Meanwhile, some of the ones that performed best were forgotten within days. The numbers looked great, but they didn’t leave a mark on anyone, including me. That’s when I realized attention and impact are not the same thing. Attention is easy to measure. Impact isn’t. One disappears with the next scroll. The other stays with someone long after they’ve closed the app. That’s why I’ve started caring less about reach and more about whether something I share is actually worth reading. Not because it’s the best strategy. Because life is too short to spend it saying things you don’t believe. Part of why @RallyOnChain stands out to me is that it pushes people to contribute ideas, not just collect impressions. So here’s something I’ve been thinking about: If every post you’ve ever made disappeared tomorrow, which one would you still be proud of?

The Netherlands also has its Henry Nowak cases. In July 2020, 14-year-old Tamar from Marken was hit by a car on a dark dike road and left to die. Her body was later found in the berm. What happened next is deeply disturbing. The police initially told her mother that the driver was German. Days later the truth came out: it was four Iraqis in the car. The mother was told they withheld the real background because they didn’t want to create a "Wilders-effect" — they didn’t want to give Geert Wilders political ammunition. Even worse: evidence strongly suggests Tamar’s body was moved after the accident. The driver didn’t just flee, they dragged her off the road and left her there like an animal. The driver received only a €1,500 fine for looking at his phone while driving. He then disappeared completely. The fine was returned “undeliverable” and for years he was untraceable. Only after years of fighting by the family (including going to court to force prosecution), a breakthrough came in March 2026: the now 33-year old Jamal is finally being prosecuted for causing the fatal accident and leaving the scene. Just like Henry Nowak in Southampton — an innocent young person dies, authorities seem more focused on protecting a narrative and avoiding “political incorrectness” than on delivering swift justice. A 14-year-old girl dies on a Dutch dike. The system lies about the identity of the driver, gives him a slap on the wrist, loses him for years, and only after massive pressure does real prosecution begin. This is not just a traffic accident. This is a story about truth, accountability, and what happens when institutions put ideology before grieving families. Her name was Tamar. She was 14. She deserved better. ♡

I have a hypothesis about the current 3D vs non-3D debate. Perhaps the endgame is that these two paths eventually merge. Non-3D approaches currently feel incredibly strong. Scale data, scale compute, scale parameters, and surprisingly quickly: 20 → 40 → 60 → 80. Realism improves. Motion improves. Benchmarks improve. But going from 80 → 100 feels fundamentally different. Physical correctness, multiview consistency, object permanence, contact dynamics, and long-horizon reasoning feel much harder. My intuition is that 0 → 80 is mostly a scaling problem, while 80 → 100 may be a world-state problem. Current large-scale data gives us enormous amounts of observations: pixels, videos, actions. But much less geometry, depth, pose, contact, physical constraints, or object state. As models become stronger, perhaps the bottleneck slowly shifts from “Can models fit the data?” to “Does the data contain enough world state?” This is why I think 3D matters—not necessarily as the final representation, but as data infrastructure. Multiview capture, simulation, synthetic interaction, counterfactual rollouts, state supervision. These systems don’t simply create more data; they create higher information density data. Which creates an interesting possibility: maybe non-3D systems win early because scaling observations is easy, while 3D systems catch up later because scaling world-state is harder. And eventually, perhaps the distinction disappears. Sufficiently strong non-3D systems may need to implicitly learn world structure, while sufficiently strong 3D systems must learn appearance, dynamics, and semantics. Perhaps the real question is not: 3D vs non-3D. But: How do we scale world states. Before the intelligence scale, the data engine needs to scale first.

🚀 Just launched Trackply — the AI-powered job application tracker I built after getting fed up with the chaos. While working as an AI contractor and simultaneously applying for full time work, I was sending hundreds of applications… most of them disappearing into the void, rejected by AI screeners before a human ever saw them. So I built the tool I needed: • Chrome Extension that auto-tracks every application • AI that tailors your resume & cover letter on the fly • AI Job Hunter that searches 10+ boards at once Use AI to beat AI. Try it free → What’s your biggest job search frustration right now? 👇

Elon Musk: "I think it's always good when thinking about something that you're afraid of, when thinking about fear, look fear straight in the eye, and it will disappear, The nature of fear is that people don't look at it. Look at it directly and it will be gone"