Alphabet Cl A (GOOGL)

$GOOGL is in a $468M round for Marvel Fusion, a German laser-based nuclear fusion startup. Makes sense with data center power demand still climbing. Google is clearly looking at long-term sustainable energy options, and fusion is one of the cleaner but high-risk bets on the table.

$META $MSFT $AAPL $GOOGL is $NVDA a mag 7🤭😅

$GOOGL 400

$AMZN $GOOGL $META $MSFT $TLT :) working really nicely Long FAANG Short duration bonds

Goldman baseline model implies $765B in annual AI CapEx in 2026, growing to $1.6T in annual CapEx in 2031 Debates about the scale of AI infrastructure investment are often framed as a referendum on demand: whether AI adoption, monetization, or productivity gains will ultimately justify trillions of dollars of capital investments. But the amount of capital required to support today’s AI ambitions is not a single, fixed number—it is highly sensitive to a small set of structural assumptions about how the infrastructure itself is built and renewed. The implication is not that current estimates are obviously too high or too low, but that they are far more conditional than they appear & so may shift over time. As assumptions around technology progress and system design and market demand behavior shift, estimates of required capital will move with them. For investors and operators, critical questions remain: What fundamental assumptions do we have about the future, and how resilient to changes in those assumptions are our plans? There is a certain circularity hinted at in this analysis. Much of it has focused on how difficult it will be to deploy trillions of dollars of capital against the physical, institutional, and economic constraints we have described. But if the ecosystem does manage to conquer those constraints—if the infrastructure is built, the bottlenecks are cleared, and the cost of compute continues to fall—then the history of technology suggests that the result may not be surplus capacity but rather a new wave of demand and use cases that could not have existed at higher price points. The success of the build-out for today’s AI ambitions may be what ensures that it is not enough for tomorrow’s technological opportunities. $NVDA $AMZN $GOOGL $MU $DTCR

$GOOG $GOOGL where are all those momentum buyers at. Come push Google back over $400 the chart is breaking out $MU $SSNLF $SNDK

$AAPL $GOOGL Only a matter of time

SemiAnalysis ests cumulative AI capital spending (across IT & datacenters) will hit roughly $11.1T from 2024 to 2029 As this arms race shifts from cash reserves to debt-financed expansion, outstanding AI-related debt is projected to reach about $7.1T by 2029 Goldman Sachs ests about $7.6T of global AI infrastructure investment from 2026 to 2031 across compute, data centers & power McKinsey ests that data centers will require $6.7T worldwide by 2030, w/ $5.2T tied to AI workloads alone Morgan Stanley ests a cumulative $4.8T–$5.2T from 2024 to 2029, tracking just the top 5 hyperscalers (capturing ~45% of SemiAnalysis’s total global footprint) Bank of America ests a cumulative $5.9T–$6.4T from 2024 to 2029, but looks strictly at traditional on-balance-sheet corporate Cloud + AI CapEx- --- Note: Each f/cast counts the AI buildout differently, so the totals are not directly interchangeable $NVDA acts as a pseudo-"central bank" by offering a 6-year minimum GPU rental rev guarantee program. This structure allows "neocloud" operators to secure massive credit without prime corporate credit ratings --- This structure serves as Nvidia's structural hedge against legacy hyperscalers who are aggressively designing internal custom ASIC chips. By underwriting these neocloud balance sheets,Nvidia secures downstream platform economics. Nvidia is building a "neocloud proxy army" to protect itself It wouldn't be a surprise if Nvidia eventually (10+ years) consolidates these dependent networks to step forward as a dominant first-party hyperscaler itself Note: When Nvidia previously tried to build DGX Cloud as a direct cloud service, it caused severe friction w/ AWS & Azure. This friction forced Nvidia to fold DGX Cloud into internal R&D operations. Hyperscalers acct for 45%-50% of Nvidia’s total corporate revs currently $DRAM $AMZN $GOOGL $ARTY

$META expect to buy back in 400s on Overshoot of those March lows as low ROI for excessive AI Spending gets sharper focus. $GOOGL $NVDA

$GOOGL -- Just entered BUY mode above 3169.4