Selective bank lending limits bubble risk in the AI build-out, while early agent adoption supports lasting demand. Banks are cautious about neocloud loans; Meta's Muse reached more than 10 million people in about six weeks, and demand still outruns supply. Nvidia, Broadcom and Micron look priced for a sharp slowdown around 2029, but the application layer is just beginning. This cycle looks much longer than the market prices, even if it is cyclical. 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

Financing announcements point to more accelerator demand, supporting semiconductors. About $200bn in announced Meta, Anthropic/Broadcom and SpaceX/Nvidia financing likely drives $400bn in XPU purchases. Data centers burn cash until lit, then cash flow 20-40% annually; AI spend rising from 0.1% to 0.5-1% of current payroll could balance the buildout if agents replace roles. Sustainable token demand is the bet, but smaller local models are the bigger risk, though not an immediate concern. x.com  … 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.com 

HSBC's forecasts suggest CoreWeave's returns will fall short of its borrowing costs, compounding its debt stress. HSBC estimates 2028-30 EPS 50-70% below consensus, 8.9% ROIC below borrowing costs and revenue per MW 30% below hyperscalers as LLM revenue growth slows. If things worsen, a bailout is very likely; Nvidia may be the most likely candidate given Jensen Huang's commitment, though that would suggest it has been buying its own products. x.com  x.com 

Semiconductors could capture scarce spot compute's value if its forward curve holds. Compute trades in deep contango, while chip stocks price in little of that value; near-term moves are unpredictable. That makes the sector very bullish. The earlier lab-funding risk looks less acute: Anthropic should hold nearly $200B cash after its IPO and is operating-cash-flow profitable. Even with 2029 capex cuts, chips look cheap if future buyers do not default. x.com  x.com  x.com  x.com  x.com 

Semiconductor trade faces a capex growth ceiling even if AI delivers what bulls expect. Spending cannot compound at 70-100% a year indefinitely, and compute per dollar roughly doubles every two years, so the same budget buys more capacity later. Today's chip valuations also demand years of 20% AI earnings growth beyond 2028: roughly 10.9 extra years for AMD, 8.9 for ASML, 7 for Marvell and 6.4 for TSMC, versus 1.6 for Broadcom and 0.8 for Nvidia; Micron needs none under the chart's assumptions. … Show more

Financing risk makes AI-linked growth stocks unattractive to add here. Much of the money reaching suppliers such as Nvidia and Micron is financed, so harder funding would limit spending on chips, compute and memory. The buildout is not over, but stock prices could remain suppressed until it slows. A significant drawdown would make adding appealing; for many high-beta names with weak fundamentals and balance sheets, the highs look to be in. x.com 

Semiconductor demand could withstand slower OpenAI and Anthropic growth if open-source models and post-training add more chip demand than it removes. Falling token prices need not erode per-GPU economics as cost per token falls and output per GPU rises, potentially keeping rental rates firm. The balance is unresolved; the lean is bullish, but markets may focus on the easier-to-see slowdown. Shares could chop until numbers defeat the bears, or a well-founded bear case could trigger heavy selling. … Show more

Cheaper AI tokens increase demand for AI infrastructure as lower costs bring more agents, apps and inference through Jevons paradox. Nvidia's GPUs, Micron, SK hynix and Samsung memory, and AWS, Azure, Google Cloud and CoreWeave capacity are the most likely beneficiaries. Demand is only going to grow: this is the start of a dot-com-like boom with limits a very long way off. Model-layer margins may compress, but frontier models can still command a premium. x.com