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

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

Hello everyone! Today i want to share some trading ideas with you!1.EVERY PART OF THE NUCLEAR TRADE IS NOW INTERCONNECTED• Upstream you have the uranium miners & fuel processors like $Cameco(CCJ)$ , $Energy Fuels(UUUU)$ & $Centrus(LEU)$ that feed the entire system.• Midstream you have the reactor & SMR builders like $NuScale Power(SMR)$ , $Oklo Inc.(OKLO)$ , $BWX Technologies Inc(BWXT)$ & $NANO Nuclear Energy Inc(NNE)$ turning that fuel into deployable nuclear capacity.• Downstream

Space is one of my favorite 2026 themes because the real customer base is moving from commercial buyers to fully funded government programs that view this theme as national security infrastructure. It's a once in a lifetime thematic that sits inside budgets that renew every year and grow when geopolitical pressure rises. Once you understand that shift, the companies positioned for federal procurement start to separate from the rest of the sector.1. $Rocket Lab USA, Inc.(RKLB)$ | Rocket LabRocket Lab already understands this shift because they stopped presenting themselves as a launch company years ago. Every decision they have made points toward a world where fully integrated space company with vertical control across manufacturing, payload, conne

5 REASONS WHY $NEBIUS(NBIS)$ , $IREN Ltd(IREN)$ , $Cipher Mining Inc.(CIFR)$ , $TeraWulf Inc.(WULF)$ & $Galaxy Digital Holdings Ltd.(GLXY)$ ARE GETTING HIT THIS WEEK1. The $APPLIED DIGITAL CORP(APLD)$ bond blowup broke the dam & exposed the weakest link in the AI-infra chain.A 10% yield on more than $2B of debt with only $634M of equity is the market telling you the model doesn't work without cheap money. Especially when they're paying $275M a year in interest alone on a ~$300M rev base so once the market sees a structure that f

The biggest theme across Nvidia GTC event & the $Amazon.com(AMZN)$ , $Meta Platforms, Inc.(META)$ , $Alphabet(GOOG)$ & $Microsoft(MSFT)$ earnings was compute demand is exploding but power delivery struggles to keep up.That’s why the Nvidia’s 800V DC Alliance matters since it’s how the next generation of AI factories will run nonstop without blowing through energy budgets or cooling limits.The companies in this group are building that layer of the AI stack:1. $STMicroelectronics NV(STM)$ scaling SiC devices from EVs to data center energy systems2.

This past week was huge for the AI Utility theme. The hyperscaler earnings all pointed to one thing that demand is running ahead of power, racks & chips which directly sets up the next leg for independent AI compute providers. $Amazon.com(AMZN)$ showed AWS re-accelerating to 20% growth on a $132B run rate with backlog near $200B. They added 3.8 gigawatts of power in the last year and expect to double again by 2027. Every megawatt that isn’t delivered by AWS on time gets filled by third-party GPU infrastructure. $Microsoft(MSFT)$ said AI capacity will grow 80% this year & their entire data center footprint will double in two years. They're capacity constrained through FY26 even after spending $35B