$Alphabet(GOOG)$ • 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
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
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
MY 3 THOUGHTS ON $Oracle(ORCL)$ EARNINGS1. Revenue missed at the worst possible momentOracle is trying to convince the market it is becoming a top-tier AI infra supplier but another revenue miss in an environment where AI spend is exploding tells investors the monetization curve still isn’t matching the bookings narrative.2. Margins compressed right as the company needs to fund multi-gigawatt buildoutsCapex pushed past $20B in six months, FCF swung from +$11B to –$13B, cloud expenses jumped 45%, and Oracle is carrying $120B+ of debt with $25B due in three years. This is real financial strain. 3. Oracle as a high-beta, high-capex AI buildout storyRPO hitting $523B is incredible but the equity is now a bet that Oracle can• build capacity faster than