Hello everyone! Today i want to share some trading ideas with you! 1. $Alphabet(GOOGL)$ trying to build a TPU ecosystem outside of GCP by exploring spinning TPU into standalone unit while financing third-party data center partners to compete with $NVIDIA(NVDA)$ stack. That includes investing ~$100M in Fluidstack at ~$8B valuation & backing projects tied to $Leverage Shares 2X Long CIFR Daily ETF(CIFG)$ , $Hut 8 Mining Corp(HUT)$ & $TeraWulf Inc.(WULF)$ to drive TPU demand. Image 2. $CoreWeave, Inc.(CRWV)$ down ~12% after reports

Hello everyone! Today i want to share some trading ideas with you! 1. $Alphabet(GOOG)$ Cloud grew 48% last quarter with a $240B backlog and now we know why. Gemini 3.1 Pro just took the #1 spot across multiple agentic AI and coding benchmarks. Image 2. $AppLovin Corporation(APP)$ is planning to launch its own next-gen social media platform after its TikTok bid failed. Management says the goal is to build proprietary organic traffic on top of AppLovin’s ad tech reversing $Meta Platforms, Inc.(META)$ playbook of building traffic first and monetizing later. Image 3. $Amazon.com(AMZN)$ ($717B) just passed

Hello everyone! Today i want to share some trading ideas with you! 1. India data center firm Yotta is building a $2B+ AI compute hub powered by $NVIDIA(NVDA)$ Blackwell Ultra under a $1B+ 4-year DGX Cloud deal. Another large-scale AI factory is coming online in APAC by August extending Nvidia’s platform footprint beyond U.S. hyperscalers. Image 2. What’s more, $NVIDIA(NVDA)$ CEO Jensen Huang says Nvidia is preparing new chips for GTC 2026 “the world has never seen before.” Signals Nvidia’s product cadence is still accelerating even as Blackwell and Rubin are just ramping. 3. At the same time, $Alphabet(GOOGL)$ is building new subsea fiber routes linking India wi

Hello everyone! Today i want to share some trading ideas with you! 1. $Meta Platforms, Inc.(META)$ , $Alphabet(GOOGL)$ , $Microsoft(MSFT)$ & $Amazon.com(AMZN)$ are racing to own the AI infrastructure layer because whoever owns the compute owns the toll booth of the next digital economy. Build the platform first then let the ecosystem build on top and capture margin on every workload that runs through your stack. Image 2. $Advanced Micro Devices(AMD)$ partners with one of India’s largest IT services firms Tata Consultancy to deploy Helios rack-scale AI infrastructure. This is

Daniel & I dove into four big themes:1. $Taiwan Semiconductor Manufacturing(TSM)$ earnings reset the AI narrative. When the company that actually builds the silicon says demand is still outrunning supply then it confirms AI is already a real business with real demand. We break down what that means for the AI Utility trade in $IREN Ltd(IREN)$ , $NEBIUS(NBIS)$ & $Cipher Mining Inc.(CIFR)$ .2. A SpaceX IPO would force a repricing of space infrastructure. That has major implications for $Rocket Lab USA, Inc.(RKLB)$ building end-to-end space logistics,

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