Makoto Tabe

RankseekerさんのShelfに代わるボール管理ツールの開発を進めています。 本日より公開βテストを開始します。 ご興味のある方はこちらのドキュメントを参照の上、お試しください。 mtabe-blog.blogspot.com/2026/01/mtabes… リツイート等での拡散もお願いします！ #shelf #bowling #ボウリング

@Issy895 ファイト！！！！

おはようございます。 4日目 執念 根性

drawioのmcp-app-serverが出てる！ Claude上でインフォグラフィックの可視化と作成が簡潔できるやん！

SLS, NASA's Moon rocket 🌙🚀

This is my favorite climate change chart. Japanese monks, aristocrats, and emperors kept meticulous records of cherry blossom festivals for 1,200 years and accidentally built the world's longest climate dataset.

@tim_cook I reversed the video

@kinnoji1970 ミーティング中に飲んでみたものの、どんな味だったか覚えておらずもう一本購入。 そしてまたミーティングで…w

風呂上がりに飲んでみましたが これはジムビーム、もとい Dr.ペッパーじゃない(´･～･｀) というかドクペ感を期待して飲むと 肩すかしを食らいました 個人的にはドクペ感はほぼゼロかなと その昔駄菓子屋で飲んだ謎メーカーの 炭酸飲料の味に近い気がしますが ぶっちゃけビミョーです_(:3 」∠)_

Japan has roughly the same number of daily X users as the United States. With one third of the population. 75 million accounts. 60% of the country. X is bigger than Facebook in Japan, which is the opposite of every other market on Earth. When an earthquake hits, when a train line shuts down, when a typhoon warning drops, the first place 75 million people check is X. 76.5% of Japanese X accounts are pseudonymous. In a culture where expressing the wrong opinion publicly can get you socially ostracized overnight, X became the only platform where people say what they actually think. LINE has more users but LINE is private messaging. YouTube is bigger but YouTube is passive consumption. X is where Japanese public opinion actually forms. Elon said it in a leaked internal meeting in 2022: "It may seem as though our user base is US-centric, but if anything it's Japan-centric." Now Grok auto-translates Japanese posts and recommends them directly into American For You feeds. No opt-in. No toggle. A Japanese user posts in Japanese, it shows up in English on your timeline. Two of the largest information ecosystems on the same platform, separated by a language barrier for 15 years, just got merged by an algorithm update. 75 million anonymous users who built an entire parallel internet on X just got a global audience they never asked for.

We just released Turntable in Illustrator for everyone 🎉 You can rotate 2D vector art in 3D. Place all frames on canvas. Great for animations and game design. No Redrawing, just drag the slider and done!

レーシングSIMで画面が広い方が速度がわかりやすい話もこれと同じような感じだね

seedance2.0で、フェイシャルテスト。 ①アングル変わっても2Dキャラ、3D顔にならない！ →3Dキャラは、アングルによって、顔を変形させないと2Dにできないのですが、それが完全に必要なくなっている、、、😱😱😱 ②大まかな表情芝居もprevisで指定できる →瞬き、ハーフブリンク、口のちょっとした開け閉め、口角の引きなどは効く。ただ、瞼の微妙な動きとかは来ない(ちょっとアニメーター泣かせかも) →デフォルト表情は、リファレンス画像から来てるっぽい ③コマ打ちも、ほぼそのままきてる！ →２コマ打ちと３コマ打ち混ぜたのですが、それぞれ反映できている アニメーター側で、どこまでコントロールするか、どこからはしないか。 まずは、そのラインを見極めたい🥹 ※右下が、previsとしてつくったフェイシャルアニメーションです。フェイシャル仕込んだモデルは、仕事でしかなくて、10年前くらいに個人でつくったモデルをひっぱりだしてきました、、、🤣

MIT's Nobel Prize-winning economist just published a model with one of the most alarming conclusions in the AI literature so far. If AI becomes accurate enough, it can destroy human civilization's ability to generate new knowledge entirely. Not gradually degrade it. Collapse it. The paper is called AI, Human Cognition and Knowledge Collapse. Authors: Daron Acemoglu, Dingwen Kong, and Asuman Ozdaglar. MIT. Published February 20, 2026. Acemoglu won the Nobel Prize in Economics in 2024. He is not a doomer blogger. He is the most cited economist of his generation, and his models tend to be taken seriously by the people who set policy. Here is the argument in plain terms. Human knowledge is not just a collection of facts stored in individuals. It is a living system that requires continuous reproduction. People learn things. They apply them. They teach others. They build on prior work to generate new work. The entire engine of science, medicine, technology, and innovation runs on this cycle of active human cognition. What happens when AI provides personalized, accurate answers to every question people would otherwise have to learn themselves? Individually, each person is better off. They get correct answers faster. They make fewer errors. Their immediate outcomes improve. But they stop doing the cognitive work that sustains the collective knowledge base. Acemoglu's model shows this produces a non-monotone welfare curve. Modest AI accuracy: net positive. AI helps at the margin, humans still do enough learning to sustain collective knowledge, everyone gains. High AI accuracy: net catastrophic. AI is accurate enough that learning yourself feels unnecessary. Human learning effort collapses. The knowledge base that AI was trained on is no longer being refreshed or extended. Innovation stalls. Then stops. The model proves the existence of two stable steady states. A high-knowledge steady state where human learning and AI assistance coexist productively. A knowledge-collapse steady state where collective human knowledge has effectively vanished, individuals still receive good personalized AI recommendations, but the shared intellectual infrastructure that enables new discoveries is gone. And the transition between them is not gradual. It is a threshold effect. Below a certain level of AI accuracy, society stays in the high-knowledge equilibrium. Above that threshold, the system tips. And once it tips, the collapse is self-reinforcing. Because the people who would have learned the things that would have pushed the frontier forward never learned them. And the AI cannot push the frontier on its own. It can only recombine what humans already knew when it was trained. The dark irony at the center of the model: The AI does not fail. It keeps giving accurate, personalized, useful answers right through the collapse. From the individual's perspective, nothing looks wrong. You ask a question, you get a correct answer. But the collective capacity to ask questions nobody has asked before, to build the frameworks that generate new knowledge rather than retrieve existing knowledge, that capacity is quietly disappearing. Acemoglu has been the most prominent mainstream economist skeptical of transformative AI productivity claims. His prior work found that AI's actual measured productivity gains were much smaller than the technology industry projected. This paper is a different kind of warning. Not that AI will fail to deliver promised gains. But that if it succeeds too completely, it will undermine the human cognitive infrastructure that makes long-run progress possible at all. The welfare effect is non-monotone. That is the sentence worth sitting with. Helpful until it is not. Beneficial until it crosses a threshold. And past that threshold, the same accuracy that made it so useful is precisely what makes it devastating. Every student who uses AI instead of working through a problem is a data point. Every researcher who uses AI instead of developing intuition is a data point. Every generation that grows up with accurate AI answers and no incentive to develop deep domain knowledge is a data point. Individually rational. Collectively catastrophic. Acemoglu proved this is not just a cultural concern or a vague anxiety about screen time. It is a mathematically coherent equilibrium that a sufficiently accurate AI system will push society toward. And there is no visible warning sign before the threshold is crossed.

@Issy895 ファイト！！！

さぁさぁ3日目。 不思議と疲れを感じない。

まとも イーロン・マスクが𝕏に実装した自動翻訳表示により、世界中のほとんどの人々はまともだという事が可視化される newsbrewing.net/matomo

原さんの種明かしシリーズ勉強になる〜

新人ITエンジニア・ゲームプログラマー向け Tips 5選 ・壊れたときは黙らない ・迷ったら事故らない方 ・自分の違和感はユーザーの違和感 ・質問力もスキルのうち ・派手な技術より、確認・共有・期限感 入社直後は、スキルを見せることより、安心して任せられる動き方が大切です。

本日、最終回！

@Issy895 ファイト！！

いざ二日目！！

さすがnoteというか、AI時代の正しいことをしているんだけど、言語化がおぼつかなくて、何がすごいのかを全然説明できていない。 AI時代に人間が触るUIの話と、AIがどう読むかの話とかをすべて統合してこの機能を考えてそうというか。

【拡散希望】 npm週間1億DLの axios が乗っ取られました。 リードメンテナーのアカウントが乗っ取られ、RATが仕込まれた偽バージョンがnpmに公開されています。 現在進行系。 axios@1.14.1 と axios@0.30.4 にRATが仕込まれています。npm install した瞬間にマルウェアが実行されます。 ✅ 安全なバージョン: 1.14.0 / 0.30.3 ❌ 危険: 1.14.1 / 0.30.4 macOS、Windows、Linux全対応。ペイロード実行後に自己消去。プロの仕事です。 npm install を今すぐ止めてください。 全容をまとめました↓

@Issy895 ファイト！

プロテスト1日目 行ってきます。