Google's growing TPU business needs HBM, adding demand for Micron, SK hynix and the memory basket. Google Cloud rose 103% to $30.7B, with backlog reportedly $561B; UBS models more than double TPU shipments in 2027. Micron should be up double digits on this, not down 5%. Samsung has LTAs with 10 major customers and is negotiating with 10 more, targeting 60-70% of capacity under contract. x.com  x.com 

Google TPU adoption could broaden the AI hardware opportunity beyond Nvidia, with demand reaching custom ASICs, HBM, packaging, optics and testing. Per The Information, OpenAI reportedly plans to buy Google's TPUs and is hiring compiler engineers, but no purchase is confirmed. Broadcom, SK hynix, Samsung, Micron, TSMC, Coherent, Lumentum, FormFactor and Teradyne could benefit. x.com 

TSMC may lose pricing power as performance gains shift from shrinking transistors to stacking, interconnects and optics, while logic folding could make older processes competitive. Despite strong leading-edge demand, investors may overestimate the profit share its node leadership can retain. Its cautious expansion and past reluctance toward advanced packaging suggest a risk-averse culture that protects returns but could leave it late to disruptive technologies and key customers. x.com 

TSMC sits at the end of the money trail as agentic AI reprices the chip supply chain, and Google's $40 billion Anthropic deal is the clearest proof. That deal is effectively a prepaid inference contract for 5GW of TPU capacity over five years, and every TPU flows through TSMC, where advanced-node demand runs about 3x supply. Agentic AI burns 10-100x more compute per session than a chatbot. CoWoS packaging is the tighter bottleneck, with prices rising 10-20% a year, double logic wafers. x.com  … Show more

Broadcom's integrated optics, electronics and packaging could lower custom-chip system costs because separate suppliers defend their margins. At similar valuations, it is preferred to Nvidia and has more room to beat expectations. Google TPU v8 shipments are estimated at 4.0M in 2026 and 9.1M in 2027, assuming Broadcom supplies the remainder after MediaTek's allocation. Anthropic financing adds value only if chip profit exceeds likely support payments and capacity costs. x.com  x.com 

TSMC is not a favorite longer term because the US administration and US companies have a stated goal of building a domestic source of silicon supply, and relationships toward that are already being forged. x.com 

TSMC manufactures chips for most of the leading tech companies while Intel still struggles with its own foundry. It makes NVIDIA's GPUs, Apple's phone chips, AMD's processors and Google's TPUs, plus chips for Amazon, Microsoft and Meta. x.com  x.com 

Google's allocation of massive TPU capacity to Anthropic strains its own AI effort while its researchers face compute constraints. CNBC reported internal tension; Anthropic competes with Gemini. Google should keep more TPUs for its own AI and buy more NVIDIA GPUs to rent to cloud customers, serving CUDA developers alongside Gemini. Selling TPU systems changes the equation, but Alphabet does not disclose TPU margins, so NVIDIA-like economics cannot be assumed. x.com 

TSMC's failure to prioritize Apple marks an irreversible turning point that the market will take a long time to price, even though near-term results won't be hurt. Apple paid development costs for 2nm and saw itself as a de facto shareholder, yet got no priority supply. TSMC is not expanding capacity and told Google to go through back-end partners. That treatment drives customers like Apple toward Intel, and years from now CC Wei's stance will be looked back on with regret. x.com  x.com  x.com  … Show more

TSMC's latest results point to AI chip demand still running ahead of supply, supporting the semiconductor and equipment trade. Cantor says TSMC raised its 2026 revenue outlook again, guided December-quarter sales above consensus and held 65-67% gross-margin guidance through the N2 ramp; its bullish sector read names Nvidia, Broadcom, AMD, ASML, Applied Materials, Lam Research and KLA. Jensen Huang says AI labs need not reach trillions in revenue to justify the buildout. x.com  x.com