The broad AI trade is among the most undervalued markets in years on a growth-adjusted basis because demand for intelligence keeps rising. Usage of open-weight and closed frontier models keeps climbing, while GPU rental prices are up around 80% this year despite exploding supply. Nvidia, AMD and SpaceX share this demand bet as long as both lines keep rising. x.com 

Nvidia's CUDA retains developers, putting it among 12 stocks that could dominate the decade ahead. Nebius's GPU rental price rise signals demand; Fabrinet and Credo supply AI connectivity. DraftKings has betting scale; Microsoft has Azure and an OpenAI partnership; Figma anchors design work; Shopify powers stores. TeraWulf pivots power sites to AI leases; Constellation, the largest US nuclear operator, signs big-tech power deals; Meta spends on AI; Uber has autonomous-vehicle partnerships. x.com  … Show more

Nvidia faces risks on both sides of the AI cycle. Vendor financing is a concern at the center of the buildout: strong AI sentiment brings competition, while weaker sentiment brings a slowdown. That makes it the largest holding of greatest concern. x.com 

Enterprise demand for sovereign AI favors Palantir's transformation model. In a two-pronged AI economy, businesses can retain their IP and use low-cost open models while frontier labs compete for the last increment of intelligence. x.com 

AI infrastructure bottlenecks could give eight stocks as much as 18x upside. Nvidia supplies frontier-model GPUs; Broadcom and Marvell supply custom silicon and networking; TSMC makes advanced chips; Micron supplies sold-out HBM; Vertiv provides power and cooling; Palantir monetizes enterprise AI; Alphabet spans TPUs, research, cloud and apps. The list tracks where AI infrastructure spending is flowing. x.com  x.com 

Palantir looks exposed as AI deployment gets cheaper and more crowded, because outside government contracts it lacks domain expertise and controls no meaningful infrastructure software, relying on others such as Databricks. Amazon and Microsoft are launching forward-deployed engineering and frontier AI groups backed by deep enterprise relationships, and open-source models gaining traction should bring costs down. IT services firms such as Infosys could do really well instead. x.com  x.com 

AI software and hardware advances make GPUs and power more valuable, creating huge long-term tailwinds for compute providers and AI model and app businesses. Each new software generation increases a GPU's value; each hardware generation increases the value of a gigawatt of power. That favors Nvidia, Broadcom, Intel and AppLovin. x.com 

Enterprise and neocloud demand is creating a second wave of AI infrastructure spending, with tailwinds for Nvidia and Super Micro. Dell forecasts 200 GW of AI data center growth through 2030, half driven by these customers, and estimates a $1 trillion AI infrastructure opportunity over the next four years. AI servers could enter a new growth phase in 2027, with higher shipment volumes and more revenue per deployment. x.com 

Nvidia and Micron face the risk that AI's true running costs eventually hit the semiconductor buildout. Microsoft canceled internal Claude licenses over escalating token expenses, a sign that running models at scale costs far more than flat-rate revenue, so either companies curb usage and slow frontier labs' revenue ramp or labs absorb losses. High memory prices are also driving workarounds, such as optical interconnects that allow more HBM. For now, semis remain the only game in town. x.com 

NVIDIA's free-model plan could defend chip demand as the two largest AI labs cut reliance on its hardware. OpenAI is building a chip with Broadcom; Anthropic mostly uses Google and Amazon chips. NVIDIA is putting together Reflection AI (in talks), Hugging Face and Groq for free models and paid chips. At 11x expected 2029 earnings versus ~19x for Microsoft, Alphabet and Amazon and 32x for Apple, its price reflects fears of slower AI spending and lost customers. NVIDIA is a 'Maximum Opportunity'. … Show more