To The Moon

1. $ASML Holding NV(ASML)$ sits at the choke point TSMC just confirmed with rising EUV intensity keeping wafer supply constrained into 2028–292. $NVIDIA(NVDA)$ benefits from a true allocation economy where scarce advanced wafers sustain GPU pricing power & margins3. $Amkor Technology(AMKR)$ sits at the next bottleneck after wafers where advanced packaging turns scarce silicon into deployable AI systems4. $Applied Materials(AMAT)$ monetizes rising process intensity as hot fabs & advanced nodes drive more steps per wafer.5. $Advanced Micro Devices(AMD)$ gains from the same

$Alphabet(GOOG)$ • AI chips designs TPUs to keep AI compute cheap & controllable as inference becomes a margin business• Robotics invests in embodied AI through Apptronik to automate physical work once software automation saturates• Drones owns Wing to remove labor & time costs from last-mile logistics as commerce moves toward instant fulfillment• Space holds exposure to launch, satellite connectivity & Earth data via $AST SpaceMobile, Inc.(ASTS)$ , $Planet Labs Pbc(PL)$ & SpaceX• Autonomy operates Waymo to replace human labor with software in in transportation which is one of the largest cost centers in the economy• AI models builds Gemini & ad

1. $AST SpaceMobile, Inc.(ASTS)$ 1. Distribution is already solvedAST doesn’t need to acquire users since they come through carriers like $AT&T Inc(T)$ , $Verizon(VZ)$ , Vodafone, Rakuten and others. That’s billions of subscribers already embedded in the system so focusing on retail signups is the wrong metric when the carriers already own the customer relationship. 2. Coverage Is the ProductAST makes money by filling coverage gaps that networks can’t reach like roaming uplift, emergency access, etc. There is no hardware to subsidize, no dishes to ship and no consumer marketing funnel to fund so applying a consumer telecom playbook here leads to the wrong conclusi

2026 WILL BE THE YEAR OF AI MEMORY• $Micron Technology(MU)$ supplies the DRAM & HBM next to GPUs that let AI think longer & hold more context.• $SanDisk Corp.(SNDK)$ , $Seagate Technology PLC(STX)$ , $Western Digital(WDC)$ store massive AI datasets & model files so training and inference can scale.• $Pure Storage(PSTG)$ , $NetApp(NTAP)$ turn raw memory & disks into reliable storage systems enterprises actually run AI on.• $Lam Research(LRCX)$ ,

Hello everyone! Today i want to share some trading ideas with you!1. $NVIDIA(NVDA)$ frames physical AI around three computers: one to train models, one to run real-time inference & one to simulate outcomes before actions are taken.2. $NVIDIA(NVDA)$ CEO Jensen Huang said the first full-stack autonomous vehicle built on Nvidia’s platform will be on U.S. roads in Q1 2026.He added there is “no doubt” this becomes one of the largest robotics industries in the world.3.NVDA CEO Jensen Huang just announced Alpamayo which he calls the world’s first thinking and reasoning model built for autonomous vehicles.By open sourcing the Alpamayo stack, Nvidia is pushing self driving forward as a category after years of

Hello everyone! Today i want to share some trading ideas with you!THE 8 LAYERS OF THE REAL-WORLD AI BOOM1. $NVIDIA(NVDA)$ , $Advanced Micro Devices(AMD)$ , $ASML Holding NV(ASML)$ , $ARM Holdings(ARM)$ & $Broadcom(AVGO)$ design & manufacture the processors that AI models run on.2. Those chips only work at scale because of networking & optics where $Arista Networks(ANET)$ , $Credo Technology Group Holding Ltd(CRDO)$ , $Ciena(CIEN)$ ,

AI Chips• $Broadcom(AVGO)$ helps Google design custom TPUs so it can lower AI chip costs & avoid $NVDA pricing• $Taiwan Semiconductor Manufacturing(TSM)$ only foundry currently capable of producing Google’s leading-edge TPUs at scale with acceptable yields.• $ARM Holdings(ARM)$ licenses the CPU architecture Google uses alongside TPUs for AI inference & control• $Cadence Design(CDNS)$ sells the software Google uses to design each new generation of AI chips• $Synopsys(SNPS)$ provides chip testing/ IP so Google can ship complex TPUs without failures•

3 THINGS THAT MATTER ABOUT THE $NVIDIA(NVDA)$ + GROQ DEAL1. This was about owning inference economics, not fixing a chip gap Nvidia didn't aqui-hired Groq because it was behind on chips since Nvidia already dominates training and most inference & its roadmap (GB300, Rubin) continues to push cost-per-token down while expanding performance faster than nearly anyone else. Training is a one-time event while inference is where the new AI business model lives so as AI moves into real products the money shifts to whoever controls runtime.2. The future where inference escapes Nvidia just got absorbedGroq was one of the few credible proofs that latency-sensitive inference could eventually move off GPUs and over time that would have chipped away at Nvid

1. $Amazon.com(AMZN)$ goes from Mag-7 laggard to leader as AWS reaccelerates.Compute bottlenecks fade, Trainium gains real adoption & AWS growth moves back toward the mid-twenties, while Ads continues its steady climb & becomes a second profit engine that structurally lifts $AMZN margins.2. Space industry becomes a mainstream investment theme.A $1.5T SpaceX IPO forces public markets to rethink what the space economy is actually worth. That shift accelerates as Sam Altman explores a direct SpaceX competitor & as Sundar Pichai, Jeff Bezos & Elon Musk openly discuss orbital compute which creates a rare moment where politics, capital & technology align. $RKLB & $ASTS are my highest-conviction ways to express that re-rating.3. E

3 REASONS $Broadcom(AVGO)$ EARNINGS REACTION WENT NEGATIVE1. The backlog quality suddenly looked less securedMany investors treated the OpenAI relationship like a typical binding hyperscaler contract but Broadcom’s “multiyear journey” language in the Q&A made it sound more like a general framework than a firm capacity commitment.2. The revenue timing moved far outManagement made it clear that meaningful XPU revenue does not show up in 2026 & instead ramps in 2027–2029 and long-dated revenue always carries higher risk so this needs to be discounted.3. Supply constraints cap 2026 upsideBroadcom disclosed a $72B backlog with 18-month lead times which signals they're already running at full capacity & cannot accelerate deliveries even if d