Monday, November 9, 2026

@aleabitoreddit Oct 25 3 clicks

Serenity on X

Not actively. I've been pointing out issues with Neocloud/Colo financing since 2025 from $SLNH to $CRWV debt interest. And maintain my opinion only a few neoclouds would survive in a few years, given they build enough of a moat to differentiate themselves against hyperscalers. So I don't think Elon's comments are completely wrong about Neoclouds, but there's nuances. One example was $NBIS SOFR + 2.75% $3.5B facility with Citibank, which actually has better rates than GPU financing from $2T+ companies. So kinda hard to say neocloud financing has "entirely shut off" since this Citibank facility was announced 3D ago I'm not arguing the merits of Elon's claims here. There's some truth to them, even if they're framed in extremes. I'm happy to hear his opinion on the direction of the industry... but if they're mainly amplifying concerns about competitor downfall (which benefits $SPCX + $TSLA) There's some cause for concern about how healthy that is to the town square dynamic Elon originally envisioned with X.

@irbezek Oct 25 2 clicks

Ian Bezek on X

@ConnorJBates_ The majority of U.S. food and beverage stocks are trading near 20-year low valuations, but $COST and $WMT have gone into a mini-bubble. It's quite the funny little divergence.

@aleabitoreddit Oct 25 4 clicks

Serenity on X

I've always defended X as the only platform to be on for financial discourse. But it's getting harder to when the owner constantly amplifies narratives of collapse… of companies whose interests conflict with his own at $SPCX or $TSLA. Would people be comfortable if $NVDA Jensen Huang owned $META? And then the timelines were dominated by his amplified narratives of $AVGO failing? I can't see how that would be healthy for grassroots discussion.

@DevinLaSarre Oct 25 3 clicks

Devin LaSarre on X

Newest out. Philip Morris International: Ho-hum Hrmm? $PM $BTI $MO $IMBBY $STG $HAYPP

@partners_road Oct 25 9 clicks

RiverRoadPartners on X

@JamesTrvdes Micron’s CFO is just one of many who question how “real” the LTA backstop is. I asked him about this specifically at a dinner & his reply was straightforward & direct: “In a memory downturn, to enforce LTA’s, we’d have to sue our customers…we’re not suing our customers.” $MU

@convequity Oct 25 1 click

Convequity on X

Guess what is a more severe bottleneck than HBM? Grid transformers, switchgear and EPC, and electrical steel, both severity 94, are more severe than HBM at 93. Those numbers come from our AI Infrastructure Bottleneck Map, an AI infrastructure supply chain map. Severity runs from 0 to 100 and measures how hard a node constrains new AI capacity in 2026 to 2028. It measures scarcity, not the size of the market. On each company we score return potential and risk, each from 1 to 10 over the same 2026 to 2028 window. Return potential is the upside still left in the company. Risk is company risk, and 10 is the riskiest. The goal is to identify the companies with high remaining return potential and relatively lower risk. Not investment advice. The five most severe nodes, and what each one is: Grid transformers, switchgear and EPC, severity 94 Medium- and high-voltage equipment, grid interconnect, and the construction services that install them. The backlog runs multiple years, and the constraint is forming through 2028. • $HTHIF Hitachi, Ltd. Return potential 6.2. Risk 1. This is the lowest risk on the list, the return potential is still high, and the grid business sits inside Hitachi rather than in a separate listing. • $POWL Powell Industries. Return potential 7.5. Risk 3.2. This is the highest return potential on the list, the risk is still moderate, and Powell sells the medium- and high-voltage equipment on this node. • $600089.SS TBEA Co., Ltd. Return potential 6.5. Risk 6.1. Return potential is high and risk is high, and TBEA builds high-voltage transformers in China. Electrical steel, severity 94 The core steel inside transformers. Supply is tight, and this constraint is also forming through 2028. • $5401.T Nippon Steel. Return potential 6.4. Risk 3.2. High return potential with relatively lower risk, from a major mill for the electrical steel that goes into transformer cores. • $005490.KS POSCO Holdings. Return potential 6. Risk 3.8. This is the holding company rather than a separate steel listing, POSCO is a major electrical-steel mill, and the return potential is lower than Nippon Steel's with higher risk. • $CLF Cleveland-Cliffs. Return potential 6.5. Risk 4.2. Return potential is high, the risk is higher than Nippon Steel's, and Cleveland-Cliffs is the only US producer of grain-oriented electrical steel, the steel in transformer cores. HBM, severity 93 High-bandwidth memory stacks, which constrain accelerator performance. Supply is extremely tight and the vendors are few. • $005930.KS Samsung Electronics. Return potential 6.5. Risk 3.5. High return potential with relatively lower risk, from one of the three companies that make HBM. • $000660.KS SK hynix. Return potential 6.5. Risk 4. SK hynix is the second of the three HBM makers, with the same return potential as Samsung and higher risk. • $MU Micron Technology. Return potential 6.5. Risk 5. Micron is the third HBM maker, with the same return potential and the highest risk of the three. Gas turbines and on-site generation, severity 88 The turbines that make prime and backup power on site, and the hot-section parts those turbines need. This is the next power constraint forming in the 2026 to 2028 window, and this node has two listed names, not three. • $HWM Howmet Aerospace. Return potential 6. Risk 2.3. High return potential with relatively lower risk, and Howmet makes the castings that large turbines wait on. • $603308.SS Anhui Yingliu Electromechanical. Return potential 7.2. Risk 7.8. Return potential is high and risk is high, and Anhui Yingliu makes castings for industrial gas turbines in China. Leading-edge foundry capacity, severity 86 Manufacturing capacity at 7 nanometers and tighter. The map calls this the main AI hardware bottleneck. • $TSM TSMC. Return potential 6.2. Risk 3.8. The scarce capacity on this node is the capacity TSMC already runs. • $INTC Intel Corporation. Return potential 7.4. Risk 6.8. Return potential is high and risk is high, and the foundry work sits inside Intel with no separate foundry listing. • $0981.HK SMIC. Return potential 6.2. Risk 6.8. SMIC, Semiconductor Manufacturing International Corporation on the Hong Kong line, is the third listed foundry on this node, with a higher risk than TSMC.

@convequity Oct 25 1 click

Convequity on X

@hunterguo101 That's the concerning part. OpenAI + $AVGO are showing then can do 1st gen custom asic quickly in both tape out, volume deployment, and scaling production quite flawlessly while previous consensus is it takes at least 3 generations each taking 18mos+ to finish.

@aleabitoreddit Oct 25 1 click

Serenity on X

Few things: - $SIVE is targeting T1 hyperscaler deployments for pluggables, CPO, NPO. Not quite sure what you mean by Tier 2. They have direct engagements with hyperscalers but currently are more upstream by qualifying with companies like Ayar, $JBL, $GFS, O-Net that eventually likely ends up -> $AMZN / $MSFT for example. On financing: - Colo players like $CIFR still need $1B+ of financing for their sites. - Neoclouds like $CRWV need billions of financing to buy GPUs. Higher rates + less support for financing makes it more challenging for these players. $SIVE already raised 700M SEK for their buildout and largely rely on external foundries, so they don't have financing constraints. There's pressure on players that need currently need financing for capex, but markets group up everyone in AI sector indiscriminately. The second nuance is whether or not this effects the end customers in terms of demand. I'd argue optical sector is insulated, even if overall AI capex from hyperscalers decreases, I see optical content still rising and aggregate demand rising. And this is especially the case with new incoming players going through their first qual cycles.