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【先行販売のお知らせ】 💖Care Bears™(ケアベア™) × ILLIT（アイリット）💖 スキニーディップから、“かわいい”をぎゅっと詰め込んだスペシャルコレクションが登場✨ @carebears @carebears_jp 2026年5月29日(金)〜6月7日(日)、SHIBUYA109渋谷店 地下1階 DISP!!!にて開催されるCare Bears™(ケアベア™) POPUP STORE『Care Bears™ on the Stage』にて先行販売START🫶 ぜひ会場でチェックしてください💕 【ラインナップ】
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《📢ガチャ®︎5月18日以降発売》 ◒Care Bears™ × ILLIT　もふもふポーシェット ／ 「Care Bears™」とILLITの スペシャルデザインが登場✨ ＼ 👛価格：500円 📌ラインナップ（全5種） ・Sweet Messages Bear YUNAH Ver. ・Cheer Bear MINJU Ver. ・Sweet Dreams Bear MOKA Ver. ・True Heart Bear WONHEE Ver. ・Wish Bear IROHA Ver. 　@carebears 　@carebears_jp 　#ケアベア# #CareBears# #ILLIT# #아일릿# ※発売時期は地域や店舗によって異なる場合があります。

／.･˚ 📢Care Bears™ x ILLIT Collab. Merch.が予約販売決定！ ＼˚･. 個性豊かなCare Bears™とILLITがスペシャルコラボを実現をいたしました！🧸💖 詳しくはこちら→ #ILLIT# #CareBears# #時よ止まれ# #Toki_Yo_Tomare#

" If SpaceX didn't work, Founders Fund would not exist." " We bet our careers on SpaceX." " At Founders Fund, we weren't trying to do portfolio management. We were trying to put the most money into the best companies possible." — Brian Singerman (@briansin) on @elonmusk

Elon Musk identified which jobs go first, and it destroys every assumption about who’s safe. Musk: “AI is going to take over those jobs like lightning. Anything that is digital, which is like just someone at a computer doing something.” Not factory workers. Office workers. The people who spent decades assuming education and desk jobs meant security are actually first. Musk: “Anything that’s physically moving atoms… those jobs will exist for a much longer time.” Output is a file? Vulnerable. Output is physical? Protected. That’s the entire framework. Musk: “AI is really still digital.” AI doesn’t need a body. Doesn’t need an office. Just needs access to the same software you use. Executes faster. Never tires. Costs nothing to scale. But it can’t weld. Can’t wire a building. Can’t fix pipes or work soil. Musk: “Literally welding, electrical work, plumbing. Those jobs will exist for a much longer time.” Trades aren’t the vulnerable jobs. They’re the durable ones. Physical presence, real-world adaptation, manual dexterity provide protection no digital credential offers. Analyst, accountant, paralegal, programmer, anyone producing files and documents, automates first because digital work is exactly what AI does natively. Person moving atoms has natural defense. Physics, unpredictable environments, material resistance create friction AI can’t scale past. Person moving bits has nothing. No friction. No physical barrier. Just software AI already operates better than most humans. The assumption that desk work and degrees represent safety just inverted completely. College graduate producing documents faces faster displacement than the electrician producing installations. Society spent generations telling people trades were beneath them. Pushed everyone toward offices and screens. Turns out the people who didn’t listen built the most automation-resistant careers. Most ironic outcome of the AI revolution. The work society treated as inferior turned out to be the work society couldn’t replace. And the work society valued most turned out to be the easiest to eliminate.

Elon Musk says he underweighted one trait in hiring and learned it the hard way. For decades, talent acquisition built its scorecards on three pillars. Skills. Experience. Cultural fit. Resumes were ranked accordingly. Then the bad hires happened anyway. "Generally, I think it's a good idea to hire for talent and drive and trustworthiness." Talent. Drive. Trustworthiness. The first three felt obvious. The fourth had cost Musk careers. Hires he'd defended. Hires he'd promoted. Hires he eventually fired. Then Musk named the trait most rubrics skipped. "And I think goodness of heart is important. I underweighted that at one point." Musk named the trait: **goodness of heart**. Polished. Predictable. Almost useless without it. Musk, who had interviewed the first few thousand SpaceX hires himself, knew the longest training set. A high-talent, high-drive, trustworthy employee with bad intent could ship more damage to a company over a quarter than a low-output engineer could in a decade, because the same competence that delivered the win also delivered the harm. "Are they a good person? Trustworthy? Smart and talented and hard working?" You can teach domain knowledge. You can teach a process. You cannot teach a person to be kind. Or to mean well when nobody's watching. After Musk made the correction, his hiring filters added a layer most rubrics never named. Goodness of heart became a yes/no gate. Musk, on the four traits that can't be unlearned: "Those fundamental properties, you cannot change." What's the trait you keep meeting in great hires that doesn't show up on any resume? P.S. I made a playbook breaking down 100+ most powerful decision making mental models used by history's greatest thinkers. 5,000+ downloads. 113 five-star reviews. Grab a free copy here: — Elon Musk ( @elonmusk ), CEO of Tesla and SpaceX, on Dwarkesh Patel's ( @dwarkesh_sp ) podcast

Anthropic CEO Dario Amodei : "Software is going to become cheap, maybe essentially free. The premise that you need to amortize a piece of software you build across millions of users, that may start to be false. But at the same time, there are whole jobs, whole careers that we've built for decades that may not be present. And, you know, I think we can deal with it. I think we can adjust to it. But I don't, I don't think there's an awareness at all of what, of what is coming here and the magnitude of it." --- From "The Wall Street Journal" YT channel (link in comment)

An Econ PhD student at the 20th ranked program who is working on stuff they are passionate about will have a better job market than one at MIT who's been doing nothing but phd-app-maxxing since undergrad. People get confused by this because they don't observe *how* successful people came about their insane knowledge bases. It wasn't by relentlessly grinding away at stuff because they had to. They look at Scott Kominers and say "if i grind and learn as much math as he did, i will be successful." You can't! *You* can't learn as much math as Kominers because he gets energized by configuration results for type ii lattices. You will burn out if you try to do it this way. You cannot, through grind alone, learn more about the economics of cities than Glaeser, or about how to maximize a value function than Acemoglu. Research careers are long. Most people give up and stop working on research (graph is share of elite PhD graduates with at least one publication in year X after graduation). If you're starting a PhD, you're presumably doing it to have a successful 40-year research career. The number one factor in whether that happens is not which program you get into, it's whether you find a research angle that energizes you enough to push through the endless barriers an academic career throws in your path. This is why a lot of the received wisdom around PhD applications is wrong. If you're 100% consumed by the predoc rat race already, it's going to be a long, hard road ahead. Obv you still have to do admissions, you should study a lot for the GRE, sigh it seems like taking real analysis is probably worth it. But spending time on the things that energize you about economics is a no-brainer, whether it's policy, or blogging, or whatever, you gotta do the things that light your fire and make you want to be on this road.

The Gen Z experience: - College degrees barely guarantee jobs anymore. - Rent eats half your paycheck. - AI is coming for entire careers. - Houses cost 20x what you make. - Feels like WW3 trends every other week. And boomers still ask why you’re stressed.