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Nvidia Supply Bottlenecks Shift AI Hardware Demand to Custom ASIC Developers

 ·  1 min read

Sustained constraints in CoWoS packaging capacity at Taiwan Semiconductor Manufacturing Co. are driving enterprise cloud providers to diversify their AI hardware portfolios. While Nvidia maintains dominance in general-purpose GPU computing, delivery lead times extending past 40 weeks have created operational bottlenecks for hyperscalers expanding generative model infrastructures.

Strategic Shift to In-House Silicon
Alphabet, Amazon, and Microsoft have responded by increasing capital expenditure allocated to custom Application-Specific Integrated Circuits. Google’s fifth-generation TPU deployment and Amazon’s Trainium2 rollout reflect a concerted effort to reduce unit economics on inference workloads. Analysts estimate custom accelerators will account for 22 percent of cloud AI compute capacity by late 2025.