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VVTLD | Money Signal
381 posts
VVTLD | Money Signal
@VVTLD
Filtering noise in Money, AI & Markets. Tracking AI infra, capital flows, and Asia-linked signals before markets reprice.
Hong Kong Katılım Nisan 2021
63 Takip Edilen2K Takipçiler
@Schuldensuehner This is the real AI trade now. Not just who has the best model, but who can keep funding the infrastructure race without compressing returns. Capex is becoming the moat, but also the risk.
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Morgan Stanley has again raised its capex forecasts for the five hyperscalers Amazon, Alphabet, Meta, Microsoft, and Oracle. It now expects them to spend about $805bn this year, up from a previous estimate of $765bn. For next year, the forecast has been lifted from $951bn to $1.1TRILLION. To put that into perspective, their 2026 spending alone would be roughly equal to what all non-tech companies in the S&P 500 spent combined in 2025. The expected ~$800bn for 2026 is nearly double 2025 levels and about three times what was spent in 2024.
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@fiscal_ai This is the part market may start questioning: user growth can stall while ad load still expands. But that is not the same as demand growth. At some point the debate shifts from “Meta has more users” to “how much more monetization can the same attention base absorb?”
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Huawei is less about replacing Nvidia overnight and more about pressuring the AI hardware pricing structure. The constraint is still ASML, HBM, packaging, and software stack maturity. China’s near-term path is probably not brute force parity, but efficiency and vertical integration.
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IMO, the only way to resolve this massive hardware price surge is for Huawei's new inference chips to be supplied globally.
But, neither the US nor China will want that.
Plus, the biggest issue right now is skyrocketing energy prices.
I think this market is going to be tough for a while.
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@evrgn11112231 The interesting part is where Mark’s psychology meets the unit economics. He may be directionally right on AI, but the market still has to underwrite a much more capital intensive Meta.
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@KobeissiLetter The debt number gets the headline, but the liquidity rhythm matters more for markets. Tax season pulls cash into the TGA, bill issuance slows, then issuance picks up again as cash inflows fade. That shift is what markets actually have to absorb.
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The US government's cash balance is rising:
The Treasury General Account (TGA) is up to ~$1 trillion, the highest since April 2021.
The TGA is the US government’s main checking account at the Fed, used to hold and spend federal funds.
The TGA balance has risen +$300 billion over the last 3 weeks.
This surge was driven by the spring tax season, as US households and businesses paid their annual tax bills over the few weeks leading up to April 15th.
In response, the Treasury reduced T-bill issuance by $35 billion last week versus the same period in March, briefly pushing total US federal debt below $39 trillion.
However, T-bill issuance will pick up again as the cash flowing into the TGA is set to slow in the following weeks.
The US debt crisis is set to reaccelerate.
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@StockMKTNewz This is why the capex debate matters. Meta is not just spending more on AI. It is spending more while the core attention asset is showing early signs of maturity. That is a very different valuation problem.
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@pepemoonboy The real question is when the market stops valuing Meta as an ad platform with AI costs and starts valuing it as a real-world data network with distribution. If that shift happens, the multiple debate changes completely.
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The Meta AI Glasses are collecting real world data all day long, capturing how people interact, move, and make decisions.
That data becomes training fuel for AI models that will eventually power the brains of humanoid robots.
Now you see the play.
This is a data flywheel at scale.
This is how you build human level intelligence.
And if this plays out, $META has a real shot at becoming the most dominant AI company in the world.
Pepe Invests@pepemoonboy
$META might have just positioned itself as the biggest robotics play of the next decade. Meta acquired Assured Robot Intelligence, a startup developing artificial intelligence models for robots, as part of a major initiative to build humanoid technology. If this plays out… Meta becomes the operating system for robots. BULLISH
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@tphuang This is why I still think China’s industrial base is underpriced. The next cycle may not be won only by software or models, but by whoever controls power, grids, offshore engineering, and heavy infrastructure at scale.
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Exactly. The market keeps treating memory like a cyclical component story, but AI is turning it into a capacity bottleneck across devices, servers, cars, and edge compute. 32GB becoming normal on PCs is not just a consumer upgrade cycle. It is another signal that baseline memory intensity is moving structurally higher.
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$MU $DRAM $SNDK Microsoft just raised the bar:
16GB RAM = "baseline" with compromises
32GB RAM = the new “No Worries” standard for
Windows 11 gaming PCs With Discord, Chrome tabs, streaming apps, and next-gen games all fighting for memory, 32GB is now the sweet spot for smooth multitasking and future-proofing.
Gamers & creators upgrading → more DRAM consumption across the board.
Now throw Agentic AI and Edge AI to the equation. Consumer DRAM shortage is about get worse.
Trade Whisperer@TradexWhisperer
$MU Signs of structural memory transformation during earnings today. Must Read 👇 Automotive: "The average car today has less than L2 ADAS capability, containing approximately 16GB of DRAM, while vehicles with L4 autonomy require over 300GB." Robots: "Humanoid robots will be AI-enabled and powered by a compute platform that rivals a high-end L4-capable automobile, requiring significant memory and storage. We expect this exciting new category to further underpin the long-term favorable dynamics shaping our industry." PC: "PCs with on-device agentic AI have recommended memory specs of at least 32GB, twice the average PC." Workstations: "The fast-growing category of personal AI workstations, such as NVIDIA DGX Spark and AMD Ryzen AI Halo, come in 128GB configurations, ideal for running large language models on device." Mobile: "The mix of flagship smartphones shipping with 12GB or more of DRAM increased to nearly 80% in Q4, up from under 20% a year ago." Data Center LP DRAM: "We sampled the industry's first 256GB LP SOCAMM2 product, built on our 1γ node, enabling 2TB of capacity per CPU. Quadrupling content from just a year ago." Data Center Demand: "AI server demand (vs. traditional server) is driving DRAM and NAND data center bit TAM to exceed 50% of industry TAM for the first time in calendar 2026." The AI Shift is Here
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Exactly. The market is pricing AI like software leverage, but the buildout increasingly looks like an energy and infrastructure cycle. The real question is not just who has the best model. It is who can secure power, grid access, cooling, and capital before everyone else discovers the same bottleneck.
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The US is pouring unprecedented amounts of money into AI in record time
Meanwhile, the real constraint is energy and grid access... in the middle of the biggest energy crisis in history
- AI = ~45% of the S&P
- Energy = ~4%
So everyone is massively overweight energy-hungry AI… while underweight the thing it literally depends on
What could go wrong
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Exactly. The issue is not that analysts hate AI spend. It is that the old Meta model had clean margins, clean FCF, and clean ad leverage. Now the market has to price an AI capex curve without knowing where the steady-state margin actually is. That uncertainty is the multiple compression.
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Let me tell you guys something about $META.
The street analysts aren't strictly bearish -- they are just *FRUSTRATED* that mark zuckerberg won't tell them WHICH NUMBERS TO PLUG IN TO THEIR DUMBASS MODELS.
I watched this exact same dynamic play out as $NGS bottomed.
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@TheGeorgePu Exactly. The market is not punishing Meta because earnings are weak. It is repricing the quality of those earnings if AI turns one of the best asset-light ad businesses into a structurally more capital-intensive machine.
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Meta lost $4 billion on Reality Labs last quarter.
Nobody noticed.
Total metaverse losses since 2021?
$83.5 billion.
Everyone mocked Zuck for it. Fair.
Now look at the AI number.
Meta is spending $125-$145 billion on AI.
Just this year.
More than they lost on the metaverse in five.
The CFO said it on the call:
'We have continued to underestimate our compute needs.'
The stock dropped 5%.
Net income was up 61%.
Read that again.
Up 61%. Stock down 5%.
That's the market saying $145 billion isn't enough.
The CFO just admitted it's the floor.
Not the ceiling.
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Exactly. AI is starting to look less like a software cycle and more like an industrial capacity cycle. The bottleneck is no longer just users or models. It is chips, power, cooling, data centers, and the balance sheets willing to fund them. That is where the inflation risk comes from.
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apple products are sold out. infinite demand for inference, rate limits everywhere. anthropic & openai growing at ridiculous pace. nvidia & google at all time highs. record meta earnings.
we are now more supply constrained than demand constrained. i suspect we’ll see inflationary pressure again very soon.
fundamentally, technology is the economy, & the economy is technology.
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@rohanpaul_ai China’s edge here may not be the robot itself. It is access to messy real-world environments at scale. For robotics, that data loop may matter more than the demo.
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Real homes in China are now data labs for robotics.
A hybrid human-robot home cleaning service is already in operation. Robot handles the repetitive stuff, while the person focuses on the rest.
A preview of the everyday future we will be living soon.
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@evrgn11112231 The pre-iPhone analogy works only if Meta turns AI into a new interface, not just a better feed or ad engine. That is why the market debate is so interesting: Zuck may be right on direction, but the cost of keeping belief alive is much higher this time.
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Mark Zuckerberg is the closest thing we have today to Steve Jobs, IMO.
The biggest difference is that while Steve was a designer who perfects then ships, Mark is an engineer who ships to perfect.
And right now, $META is $AAPL pre iPhone.
I will die on this hill.
Evergreen@evrgn11112231
Zuck is the goat. $META
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@Mr_Derivatives Clean technical setup, but the real test is whether buyers treat this as a dip in the same Meta story or a repricing of the AI capex risk. The chart can bounce before the debate is settled.
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$META Down 4 days in a row. Right at the 50% retracement from the March 30th trough to April 17th peak.
I’m going in again.
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@tanayj Exactly. This is the strongest bull case for Meta’s AI spend: compute is already improving the core ad machine, not just funding future experiments. The debate is whether those efficiency gains can keep scaling fast enough to offset a structurally higher capex base.
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It's still underrated how more compute has enabled Meta to significantly improve their recommendation and ads ranking systems and drive engagement and monetization efficiency gains every quarter.
From their earnings call this week:
"On Instagram, the ranking improvements that we made in Q1 drove a 10% lift in Reels time spent. On Facebook, total video time increased more than 8% globally in Q1, the largest quarter-over-quarter gain in four years."
"In Q1, enhancements we made to Lattice’s modeling and learning techniques along with advances in our GEM model architecture drove a more than 6% increase in conversion rate for landing page view ads"
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@TaviCosta This is the part most markets still underprice. Hard assets are not just an inflation trade. They are a trust trade. When most countries keep expanding credit and only a few choose monetary discipline, capital eventually starts repricing the credibility of money itself.
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Argentina is the only country where money supply is contracting at a double-digit rate.
Meanwhile, the rest of the world continues to expand credit with little to no monetary discipline.
None of us own enough hard assets.
tavicosta.substack.com/p/macro-update
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This is the key divergence. Semis are still being priced as if the AI capex cycle is broadening, but Nvidia remains the confirmation signal for whether the cycle is still accelerating. If SMH keeps making highs without NVDA confirming, the market is no longer buying the leader. It is buying the theme.
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Since Nvidia's blowout earnings report in May 2023, every time semiconductors have made a new high without Nvidia confirming, it has served as an uncomfortable warning sign over the strength of the current trend.
We are seeing similar signals this week, with $SMH up more than 30% over its October top while $NVDA is down 4%.⬇️
io-fund.com/ai-stocks/nvid…
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@HyperTechInvest Exactly. The market is not questioning whether Meta can afford the capex. It is questioning whether Meta has the same ROI visibility as Google and Amazon. Without cloud, the AI spend looks less like capacity expansion and more like the rising cost of defending the ad franchise.
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The market is much more confident that $GOOG and $AMZN will achieve a strong ROI on capex than $META
$META has the weakest positioning (no cloud), a history of wasting money (Reality Labs), uncompetitive in-house models, and no direct tie to Anthropic/OpenAI growth
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