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SHINJIRO ATAE (from AAA)「Follow Me」のMusic Videoフルサイズが本日YouTubeで公開されました！！ 前向きになれるメッセージが込められた爽快チューン！ SNSで皆さんのお気に入りのシーンをスクショして 「#與真司郎」# をつけて投稿してくださいね！ #與真司郎# #FollowMe#

Hey everyone! I'm Crypto Zeus (@zeusky9 ） A dedicated Bitcoin & Doge believer, honestly documenting my real 0 to 1 journey in crypto: Web3 project interactions AI tools & overseas practical experiences Survival stories through bull and bear markets Follow me and I’ll share more interesting stuff from China and global crypto opportunities! Let’s connect and grow together! Drop a or say “Hi” in the replies! 大家好，我是 Crypto 宙斯 (@zeusky9) 比特币 & Doge 铁粉，真实记录币圈 0→1 生存日记 + Web3 项目交互 + AI 出海实战。 关注我，我会分享更多来自中国的有趣内容～

At midnight on May 1, 24 tons of South African apples cleared customs in Shenzhen — the very first shipment under China's expanded zero-tariff policy for all 53 African diplomatic partners. Days later, Kenyan avocados, coffee, and green beans followed. Effective May 1, 2026, the policy grants 100% tariff-free access to 20 more African nations, building on the coverage for 33 least-developed countries since December 2024. China's Commerce Ministry calls it a concrete step for high-level opening-up and a milestone in the China-Africa Economic Partnership. #ChinaAfrica# #ZeroTariff# #Trade#

For my new moots and followers: This is a nsfw account, minors dni 🔞 bullies, akgaes and antis dni. My job on twt is to thirst for Flx. I'm OT8 and multiship. Come interact with me, i swear i don't bite 🤭 I follow back other nsfw accounts or if we interact and i know you 🙏

I just got 8k followers overnight thanks to @katedeyneka's post, so I should pay it forward. here are some more people to follow if you want to keep up with what the Codex team is shipping and learning: leadership + product direction @romainhuet - launches, examples, and how builders are using Codex @thsottiaux - product direction and major releases APIs + launches @charlierguo - API launches and realtime demos plugins + ecosystem @coreyching - plugins and integrations around Codex workflows + how to use it @Dimillian @dkundel @nickbaumann_ @derrickcchoi @pvncher community & education @gabrielchua @reach_vb @kagigz cyber + security @fouadmatin - Codex Cyber and security who else should be on this list?

I asked Claude to apply a capital cycle analysis to $MU. Here's what it came up with: Net reading: 11 of 14 capital cycle signals are bearish or strongly bearish. The framework reads this as late-cycle, not early/mid-cycle. The two unambiguously bullish signals (equipment lead times, industry concentration) are eroding rather than strengthening. Insights Yielded by Capital Cycle Analysis: 1) "Structural change" rhetoric is itself diagnostic. The capital cycle framework treats coordinated industry-wide CEO claims of regime change as evidence of late-cycle euphoria. The same language was deployed by the same CEOs (Mehrotra at Micron specifically) in 2017–2018 and was wrong. Bayesian base rates argue against accepting the current claims at face value. The previous analysis under-weighted this base-rate evidence. 2) Look at total capital flowing into the supply curve, not just incumbent capex. The structural-change analysis focused on Big Three capex. The capital cycle lens forces aggregation of all capital flowing into memory output: a) Incumbent capex: ~$104B in 2026 across DRAM + NAND; b) CXMT IPO proceeds: ~$4.2B (with state-aligned co-financing many multiples larger); c) YMTC capacity additions (privately financed) d) Substitute technology capital (Cerebras, photonic startups, CXL controller designers) — billions of dollars of equity raised to reduce HBM intensity per dollar of AI compute deployed. When aggregated, total effective supply-side capital formation in 2026 is materially higher than the Big Three capex alone suggests. The supply response is being underestimated. 3) The customer base is doing exactly what late-cycle customers do. Hyperscalers locking in 3–5 year LTAs, pre-ordering 2027 NAND, building strategic inventory — these are not signs of confident long-cycle visibility, they are signs of late-cycle scarcity panic. Historically (DRAM 2017–2018, oil 2008, shipping 2007), customer pre-buying at peak prices is followed by sharp inventory destocking when prices roll over. The structural-change narrative frames LTA penetration as a benefit; the capital cycle frames it as a peak signal. 4) Multiple expansion + earnings expansion = asymmetric downside. The previous analysis flagged the 15x NTM P/E multiple as aggressive (referring to UBS PT raise). The capital cycle framework sharpens this: when both earnings and multiple are at peak, the compound drawdown when either reverts is severe. Memory historically goes from 60% gross margin to negative gross margin and from 10x P/E to <5x P/E. Even a modest reversion to 35% gross margin and 8x P/E from current levels implies a 60–75% equity drawdown for the memory primaries — without any disorderly cycle. 5) Supply lag is real but not unique. The bullish point about EUV/TSV/hybrid bonding lead times is correct but mis-weighted. The capital cycle history of other capital-intensive industries (oil refining, shipbuilding, semiconductor wafer fab) shows that long lead times increase the eventual amplitude of the down-cycle: capital decisions made at peak are not reversible when conditions soften, leading to capacity overhang. Long lead times delay the down-cycle; they do not abolish it. 6) China is the textbook capital-cycle disruptor. In Chancellor's historical case studies (steel, shipbuilding, solar, panels, batteries), state-backed Chinese entrants repeatedly compressed margins of consolidated Western/Korean/Japanese oligopolies once technology gaps narrowed. The U.S. equipment restrictions on China have created the illusion that this dynamic is paused, but the data shows CXMT doubled DRAM share in 18 months and is targeting domestic HBM3. The structural-change analysis appropriately flagged this; the capital cycle framework would weight it heavier as the single most important multi-year risk. 7) Substitute capital formation is its own supply curve. The capital cycle framework treats financing flows into substitutes as a parallel supply expansion. Cerebras' $5.5B IPO, Marvell's $5B Celestial acquisition, the Sandisk/SK hynix HBF JV, and the CXL ecosystem (ALAB, MRVL, MCHP) are collectively financing "HBM intensity reduction." Even if HBM unit demand is met, the value capture per dollar of AI compute is diluted. Capital is flowing in adjacent to the memory primaries to reduce the share of AI spend that ends up in their P&L. 8) The bull case relies disproportionately on demand visibility. The capital cycle warns against demand-anchored theses. The bull case requires AI capex to continue at current levels or accelerate, hyperscaler ROI economics to remain favorable, sovereign AI to scale, and inference workloads not to migrate to non-HBM architectures. Each of these is plausible; the joint probability that all hold through 2028 is materially lower than the headline narrative suggests. 9) Sell-side estimate trajectory is itself a signal. UBS's PT trajectory ($535 → $1,625, a 3x increase in one revision) is historically associated with peak euphoria. Estimate revisions of this magnitude have a poor forward record. The framework would treat the velocity of estimate revisions as a contra-signal. 10) Where the asymmetry sits. The capital cycle framework reframes the risk/reward calculation. Even if the bull thesis is right and earnings hold through 2028, the upside from current levels is modest (multiple expansion has already happened). If the bull thesis is partially wrong — say, 2028 brings 25% peak-to-trough EPS decline rather than 50% — the equity drawdown is still material because multiples will compress simultaneously. The asymmetry is not favourable at current valuations. Bottom line: The structural change thesis was directionally correct but materially overweighted by the original analysis. The capital cycle framework appropriately reweights toward supply-side caution and treats current peak conditions, peak valuations, peak management confidence, and accelerating capital inflows as a coherent set of late-cycle signals. The memory industry has undergone real and beneficial structural change in shape, but the empirical base rate against the "cycle has been abolished" claim is overwhelming. The economic characteristics of memory businesses have improved but have not been transformed into stable, compounding, low-volatility ones — and the next 18–30 months are statistically more likely to mark the end of this up-cycle than a transition to a new regime.