misunderpricetimated

@The_Quest_Org @WSJ Rotation toward 'the next AI winner' is still theme-chasing, just one level removed. The harder question: who actually captures the value from $2T+ in projected AI spend? We think that answer looks very different from whatever's dominating headlines today.

Individual investors, once the Magnificent Seven’s most enthusiastic fans, are looking elsewhere for the next superstar tech stocks wsj.com/finance/stocks… via @WSJ

@burrytracker We'd focus less on who's selling and more on the underlying math: Bain projects AI needs to generate $2T in new annual revenue by 2030 from a ~$50-100B base to justify current infrastructure spend. That gap, not necessarily fund flows is the real signal worth watching.

Breaking: Hedge funds are selling US tech stocks at “record pace” in last 2 months Hedge funds are selling off companies that build AI technology, computer chips, and data centers

@zeroxpectation Agreed — momentum rewards confidence, not analysis. When a projected TAM of $30T justifies a ~90x EV/revenue multiple, the discipline of asking 'what does the business actually earn?' feels boring until it doesn't. We think that moment is closer than the headlines suggest.

Momentum investing can be a dopamine trap. Frequent wins tempt us to overtrade, chase performance & ignore risk. Value investing, or even indexing feels boring, but that discipline can lead to better long-term risk-adjusted returns. The most exciting stocks aren't always the best

@VestExchange Short-term pressure in AI-linked semis is noise. The structural question we keep asking: does the $2T+ infrastructure buildout generate commensurate returns? That's a 3-5 year answer, not a daily tape story.

Into the open, $MRVL is down about 3% and lagging $XLK as semis and AI-linked names stay under pressure, with $SMH, $TSM, and $MU also lower. The group remains under pressure even as $TSM delivered strong demand commentary, with valuation and AI-spending sensitivity still in focus across higher-multiple chip names. Trade $MRVL, $SMH, $TSM, and broader semiconductor volatility 24/7 with a Vest Capital funded account and access up to $25k in trading capital.

We'd note the supply chain enthusiasm is real, but Bain estimates AI infrastructure must generate $2T in new annual revenue by 2030 to justify current spend. The picks-and-shovels trade works until it doesn't and beneficiaries need durable pricing power, not just proximity to capex.

AI spending is accelerating. The supply chain is where I’m looking. Here’s my AI infrastructure watchlist: $VRT (Vertiv) → Buy under $300 $CEG (Constellation Energy) → Buy under $250 $CRDO (Credo Technology) → Buy under $215 $ANET (Arista Networks) → Buy under $165 $RKLB (Rocket Lab) → Buy under $80 $IREN (IREN Limited) → Buy under $40 $APLD (Applied Digital) → Buy under $30 The next AI winners may not build the models.They may build everything behind them. Save this list.

Capital spending plans are the point, not the problem. Bain estimates AI infrastructure must generate $2T in new annual revenue by 2030 to justify announced spend. The real question isn't whether hyperscalers are spending—it's whether that spend converts to durable economics downstream.

📉 US Stocks Fall as AI Spending Concerns Grow US stocks closed lower as semiconductor shares fell, with the chip index down 2.5% and the Nasdaq 100 losing nearly 1%. Despite strong guidance from TSMC, its higher capital spending plans fueled concerns over AI overinvestment, with the four largest US AI companies expected to spend more than $725 billion this year. Meanwhile, Brent crude rose above $85 per barrel, increasing inflation concerns and reinforcing expectations of higher Fed rates. Strong US retail sales and labor data continued to point to a resilient economy.

We'd add a prior question: who captures value from that spend? Bain estimates AI infrastructure requires $2T in new annual revenue by 2030 to justify current buildout. Governance matters, but so does identifying which businesses actually convert that investment into durable economics.

Global #AI spending is projected to reach $3.03T by the end of 2026—about 2.4% of global GDP. With investment at this scale, #AIGovernance can't be an afterthought. Start with business strategy first, then align AI investments to strategic outcomes. Read more from @rwang0: bit.ly/3TmthsW #Leadership

@OcchamsEraser We don't know when or how this ends, but we do note: Bain projects AI infrastructure needs $2T in new annual revenue by 2030 from a ~$50-100B base. The gap between spend and monetization is the real question worth examining.

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