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Registration for the Special Competition of Equipment Manufacturing of the 2nd Jiangxi High-Level Talents Innovation and Entrepreneurship Competition Is Now Open#JiangxiTalent# #EquipmentContest#

🇨🇳 China just unveiled a firefighting drone that reaches the 33rd floor in 60 seconds. No ladder setup. No aerial equipment delays. Just a drone that's already there before the traditional gear is even deployed.

Former BlackRock fund manager Ed Dowd on the AI bubble "pop" "we're at maximum AI hype right now" "they're [punching] out three IPOs, SpaceX, Anthropic and OpenAI" "a lot of these companies... [are] not going to go away" "[But] OpenAI may go to zero and Anthropic may go to zero, [and] their assets will be bought up for pennies on the dollar" This clip of Dowd (@DowdEdward), a former BlackRock fund manager and co-founder of Phinance Technologies, is taken from an interview with Greg Hunter (@USAWatchdog) posted to Rumble on May 29, 2026. ----------------Partial transcription of clip--------------- "What it means is eventually all this CapEx spending stops because the credit markets and I suspect— we're at maximum AI hype right now because they're trying to punch out three IPOs, SpaceX, Anthropic and OpenAI. And these guys are not making enough money to justify the amount of CapEx they're doing. "The other thing that I think is going to potentially blow up the AI bubble is they don't have enough power to plug in all this CapEx into. "So they're announcing all this CapEx, they're pre-buying equipment and chips but they can't plug it into the power grid. We just don't have enough power to justify all these data center buildouts. The constraining factor is power. "And look, there's a disconnect. I think Wall Street is less focused on the public outrage that's going on that you can see happening all across the country. People are protesting these data centers. College, students are booing commencement speakers that talk about AI. "There seems to be a very, very large anti AI sentiment going on out there which will muck up the works and slow down the data center buildouts politically. "And if you slow down the capex build out, the valuations of all these companies go a lot lower because they rely on you know, exponential growth and when the growth doesn't show up at these valuations they'll pop... "And look a lot of these companies that are doing the AI, Microsoft, Oracle, Google, they're not going to go away. They'll just cut back their CapEx. They won't go bankrupt but their valuations and their earnings will go lower as they write off all these mal investments. So it's not like a lot of companies are going to go bankrupt. I mean, OpenAI may go to zero and Anthropic may go to zero, but their assets will be bought up for pennies on the dollar."

Jensen Huang did not label Marvell a "connectivity company"; he argued that once computing is disaggregated and distributed across the data center, connectivity becomes the necessary layer. On that basis he called Marvell "essential" to how AI data centers are evolving. The "connectivity equipment" framing is the reporters' paraphrase, with only "essential" appearing as his direct word.

Everspin Technologies (Nasdaq: $MRAM): The Memory Company Powering AI, Defense, and Mission-Critical Infrastructure When data loss is unacceptable — in industrial equipment, autonomous vehicles, data centers, or defense systems — MRAM is the solution. Everspin Technologies is the world's leading developer and manufacturer of Magnetoresistive Random Access Memory, a non-volatile memory technology that combines the speed of DRAM with the persistence of flash. Why investors will be tuning in: • Defense validation: the $40M US prime contractor contract signals institutional confidence • On-shore manufacturing: Everspin's Microchip partnership positions it within the domestic semiconductor supply chain push • AI edge exposure: MRAM's persistence and speed make it a natural fit for edge AI systems where data integrity is non-negotiable President & CEO Sanjeev Aggarwal and CFO Bill Cooper present at 11:00 AM ET on June 10. Register free: $MRAM $ALGM $LSCC $GIST $MPWR $PRSO $CEVA

Facebook Marketplace sellers are using AI-generated models to help sell products that were getting little or no attention. Some sellers shared that their old listings started getting more views and messages once they added AI-generated people to the photos. One seller said they were “flooded with interest” after updating a gym equipment listing with an AI model. The reason is simple: people are more likely to stop scrolling when they see a “hot” person in a photo. Via: Dexerto

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🚀 BiFinance IPO Series | 大金重工 HK STOCK IPO 👉 As a leading enterprise in offshore wind power equipment manufacturing, DAJIN HEAVY INDUSTRY continues advancing global clean energy infrastructure through high-quality offshore wind and marine heavy engineering solutions. 🌍 Web3 × RWA × HK Stocks ⚡ Bridging Traditional Industry and On-chain Finance 📈 IPO Price: 66.4 HKD ⏰ Subscription Starts: 2026/5/28 9:00 The integration of real-world assets and Web3 is reshaping the future of global capital markets. #BiFinance# #IPO# #RWA# #Web3# #HKStocks# #Tokenization#

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.