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 

Alphabet's lagging AI lab undermines the case for owning it for ANT exposure. The semiconductor-business framing does not make up for that lag, and hyperscalers are no longer needed for this exposure. x.com 

Alphabet's AI growth is harder to turn into cash because capacity shortages require rented compute while TPU system sales tie up inventory before delivery. Cloud grew 103%, with system sales contributing meaningfully; management expects rented compute to pressure Q4 Cloud margins. Q3 free cash flow was -$9.1B, partly reflecting inventory build and a one-off EU fine, while AI Mode monetizes less effectively than traditional Search. The dip is probably a buy with a reasonable timeframe. x.com  … Show more

Anthropic's compute commitments point to future revenue for Alphabet, Amazon, Microsoft, Broadcom and Nvidia. Its S-1 reports 14-fold revenue growth, positive second-quarter 2026 EBIT and more than $600 billion committed to compute through 2045. The AI trade is alive and well, more than expected, provided demand keeps pace with those commitments. x.com 

Alphabet's price action looks weak relative to SpaceX, with the stock down 6%. One possible reason is that Anthropic may be shifting more business toward Micron memory and less toward Google's TPUs, though @mason__capital counters that memory is no substitute for TPUs. x.com  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 

Broadcom was the right way to express a long Meta thesis, because incremental AI spend is shifting faster to custom ASICs. Nvidia will keep most of the dollar share of compute, but Meta's MTIA going from zero is a better rate of change for Broadcom than Nvidia doubling. The two grow at similar rates today, before major Broadcom ramps for OpenAI, Anthropic, MTIA and probably Microsoft, giving ASICs the edge for now. x.com  x.com  x.com  x.com 

Broadcom is depending on a massive Anthropic and OpenAI ramp over the next two years as Google becomes less and less important to it. CEO Hock Tan gave exact gigawatt figures for every customer except Google, which got only a vague tens of billions, a bad sign that MediaTek has taken share. x.com 

Alphabet's ownership of the whole AI stack, from chips to cloud to distribution, gives it a structural cost advantage rivals can't easily copy. It alone designs its own TPUs, runs a global cloud and owns Search, Android, YouTube and Workspace, so aggressive inference pricing is a strategic weapon. As inference overtakes training, case studies show moving workloads from GPUs to TPUs can cut operating costs by over 50%. Microsoft and Amazon are building custom chips, but Alphabet is years ahead. … Show more

Marvell's end-to-end networking approach is well suited to heterogeneous GPU, CPU and ASIC compute and mixed optical/copper technologies. Its shift from AI loser to winner deserves a lot of credit: its old custom-ASIC focus had lost out to Broadcom and Alchip, but it is now back in ASICs as Google's TPU v10 partner. The stock's excellent run reflects how it is now perceived. x.com