Daniel
Self-Directed Investor, YouTube Investing Creator
Nvidia's push into open-weight AI should make compute demand explode by making AI far cheaper. In one week it announced a $13B acquisition of Hugging Face and a $6B licensing deal with Poolside to build frontier open-weight models. Open-weight models cost less than OpenAI's and Anthropic's closed models and can be tuned into specialized models that beat frontier ones on specific tasks at a fraction of the token cost. Cheaper AI means more usage, more tokens and more compute. x.comÂ
Nvidia has no real rival, and hyperscaler ASICs are not disrupting it. Hyperscalers build custom chips because AI compute demand is exploding and moving specific workloads in-house cuts costs, not because Nvidia is obsolete. Amazon says Trainium is about 40% more cost-efficient, yet plans to buy 2M Nvidia GPUs, and Elon Musk said SpaceX will build exclusively on Nvidia's Vera Rubin. The market is growing fast enough for ASICs and Nvidia to both win. x.comÂ
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.comÂ
Anthropic's customer spending and compute buildout show AI monetizing at scale, a bullish read-through for Nvidia, Broadcom, Alphabet, Amazon, Microsoft, Nebius, CoreWeave and Hut 8. Its IPO filing reports H1 revenue up 14-fold to $16.3B, 11,900+ customers spending $100K+ annually and 1,900+ spending $1M+, alongside $9B in H1 infrastructure spending and about $430B in future compute commitments. x.comÂ
Antitrust scrutiny of Nvidia's Hugging Face deal puts the duration of its AI-stack valuation at risk. Per Reuters, the DOJ is probing the roughly $13 billion deal. The near-term tests are whether it faces an unwind, conditions or delay, and how labs price dependence if model hubs concentrate under the same chip vendor. x.comÂ
Nvidia's Hugging Face acquisition is underappreciated by a market that treats it as marginal insurance. Big players are likely soon to move beyond using open models to cut costs and start investing in their development, to keep those models at the frontier, partly because AI labs compete with their own customers. Nvidia looks well ahead of the curve in understanding this dynamic. x.comÂ
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's AI profits are real, but its compute demand depends heavily on fragile venture funding. Per Chamath, 1% of firms account for 90% of AI spending, and 72 cents of each dollar comes from unprofitable VC-backed firms. Venture money passes through startups to Nvidia and cloud suppliers; if the next raises fail, concentrated orders could contract together. x.com x.com x.comÂ
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.comÂ
More open-weight models benefit Nvidia as greater AI adoption requires more compute. They bring more competition for OpenAI and Anthropic, putting pressure on pricing and making AI more accessible; the Financial Times reports Nvidia is in talks to acquire Reflection AI. x.comÂ
Nvidia could become the weakest link in AI's circular financing economy as it takes on more customer risk. It is turning to insurers to cover customers' GPU debt, and if insurers require Nvidia to keep backstopping deals, its liabilities will keep growing on top of $245B of supply chain commitments and prepayments as of last quarter. Such large counterparty conflicts are unwise. Amazon is also looking to move $8B of Nvidia Blackwell GPUs into an SPV to take on more debt for its AI buildout. … Show more
More AI tokens mean more compute demand for Nvidia even as pricing power starts to slip. OpenRouter data via the FT show weekly token use up ~250-fold since January 2025; the FT links the surge to agents' long call chains. Bloomberg's breakdown of a 1 GW AI campus that could cost roughly $30B puts well over half the bill in chips and servers, most landing at Nvidia as GPU racks. Servers wear out in 5-6 years, making AI capex a recurring chip refresh. x.com x.com x.com x.com x.com x.com x.comÂ
