🚨 $GOOGL co-founders Larry Page and Sergey Brin are now the 2nd and 3rd richest people on the planet.
Yes, Google just leap-frogged nearly everyone. According to Bloomberg’s latest rankings, here’s the current Top 10 richest people in the world: 1️⃣ Elon Musk — $442B 2️⃣ Larry Page — $276B 3️⃣ Sergey Brin — $258B 4️⃣ Larry Ellison — $254B 5️⃣ Jeff Bezos — $251B 6️⃣ Mark Zuckerberg — $225B 7️⃣ Bernard Arnault — $196B 8️⃣ Steve Ballmer — $166B 9️⃣ Michael Dell — $155B 🔟 Jensen Huang — $155B The Google founders jumping to #2 and #3 is a reminder of one thing: AI isn’t just reshaping technology, it’s reshaping the leaderboard of global wealth in real time. Source: Evan
🚨 Fresh data just dropped and it’s sending mixed signals about the job market.
📉 Weekly jobless claims fell by 6,000 to 216,000, beating expectations of 225,000. 👉 Translation: fewer people filed for unemployment last week. Layoffs remain relatively low. But here’s the twist: 📈 Continuing unemployment claims rose by 7,000 to 1.96 million. 👉 That means more people are staying on unemployment longer. What does this combo really signal? While companies may not be cutting large numbers of workers, the economy doesn’t seem to be creating enough new jobs to absorb people who are already unemployed. In short: 🔹 Layoffs are low. 🔹 Hiring isn’t high enough. 🔹 Workers are getting stuck in unemployment longer. A cooling job market… or the calm before a bigger shift? Source: Truflation, Bianco Research
Alphabet Google's forward PE looks like a meme stock. Nearly doubled off the low. 👇
Source: Matt Cerminaro @mattcerminaro
Stablecoin Tether bought more gold last quarter than every Central Bank.
Source: Sam Callahan @samcallah FT
The exodus from BTC ETFs appears to have stopped/slowed...
Source: Bloomberg, zerohedge
UBS Hikes Copper Target to $13,000 per tonne 📈
As reported by Reuters, UBS has aggressively updated its projections. The bank raised March forecasts by $750 and mid-year targets by $1,000, predicting prices will climb to a new high of $13,000 by Dec 2026. The Catalysts: ⚡ Demand: Powered by AI data centers & EVs. ⛏️ Supply: "Persistent mine disruptions" widening the gap. Source: Mining Visuals on X https:// miningvisuals.com
🦔 HSBC built a model to figure out if OpenAI can actually pay for all the compute it's contracted. The short answer is no. Actually not even close.
The Commitments: $250B in cloud compute from Microsoft $38B from Amazon 36 gigawatts of contracted capacity All tied to a total deal value up to $1.8 trillion HSBC’s estimate: OpenAI will owe ~$620B per year in data-center rent once everything ramps… and only a third of that capacity is online by 2030. 🔢 The Math (and the Problem) By 2030: Cumulative rental costs: $792B (→ $1.4T by 2033) Projected free cash flow: $282B Cash from Nvidia/AMD: $26B Undrawn debt: $24B Liquidity: $17.5B Even after stacking every possible dollar, there’s still a $207B hole — plus the $10B safety buffer HSBC thinks they need. 💥 And here's where it gets tricky 👇 HSBC’s model already assumes everything goes right: 3B OpenAI users by 2030 (44% of all adults outside China) Paid conversion rising from 5% → 10% 2% share of global digital ads $386B in annual enterprise AI revenue Even under that fantasy scenario, OpenAI still can’t pay the bills. HSBC’s suggested “solution”? OpenAI may need to walk away from its data-center commitments and hope Microsoft/Amazon “show flexibility.” Translation: The economics don’t work — unless everyone politely pretends the contracts aren’t real. And yet this is the company anchoring a $500B Stargate project and driving hundreds of billions in AI infrastructure spending. If this is what the best case looks like… imagine the base case. My take: be very careful with AI plays which are asset-heavy. They might disappoint in terms of shareholders' returns in the years to come. Do you remember the Telecom bubble? The long-term winners have been the asset-light companies. The asset heavy companies never recover. Source: Hedgie on X, FT
Interesting view by Shay Boloor @StockSavvyShay about why the AI cycle is nothing like the dot-com era.
"Early-2000s fiber ran at roughly 7% utilization because the industry built far ahead of demand that never showed up. The physical layer scaled faster than the software. Today is the inverse. $NVDA clusters inside $MSFT, $AMZN, $GOOGL and $META are running ~80% utilization because every model lab is capacity-constrained. The software layer is scaling far faster than the physical. One cycle had excess supply and no demand. This one has excess demand and not nearly enough supply. That’s the entire difference". ➡️ True. At least for now. But are we sure that capacity utilization will remain as high when hyperscalers would have spent trillions of dollars in additional capacity? What if demand does not pick up as much as supply??? The 7% utilization rate of fiber optics is the one which applied to the end of the cycle, once all fiber optics got built. When the telecom companies started to over-invest, they never assumed that capu would be that low at the end...
