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Ben and Jay unpack why Broadcom’s “fourth customer” (~$10B) custom-ASIC win reset sentiment even after a modest beat/raise, and how that squares with hyperscalers second-sourcing away from NVIDIA in the near term. They frame the true battleground as networking—Ethernet’s ubiquity vs. NVLink’s tight integration—then differentiate GPUs’ performance-per-watt advantages from custom ASIC cost calculus, arguing that “lumpiness” (program outcomes) is not “cyclicality” (inventory swings). They stress TAM realism: it’s easy to total up CapEx, but the ROI numerator (revenue/profit) is still unknowable. Structurally, TSMC remains the default winner, with a plausible Intel Foundry financing path in the wings, while Google looks more likely to “sell capacity” for TPUs than chips. Net: GPUs keep the bulk of spend through 2030 even as select first-party silicon scales, and the market should judge claims against networking choices and workload fit—not headlines.
By Ben Bajarin and Jay Goldberg4.7
3838 ratings
Ben and Jay unpack why Broadcom’s “fourth customer” (~$10B) custom-ASIC win reset sentiment even after a modest beat/raise, and how that squares with hyperscalers second-sourcing away from NVIDIA in the near term. They frame the true battleground as networking—Ethernet’s ubiquity vs. NVLink’s tight integration—then differentiate GPUs’ performance-per-watt advantages from custom ASIC cost calculus, arguing that “lumpiness” (program outcomes) is not “cyclicality” (inventory swings). They stress TAM realism: it’s easy to total up CapEx, but the ROI numerator (revenue/profit) is still unknowable. Structurally, TSMC remains the default winner, with a plausible Intel Foundry financing path in the wings, while Google looks more likely to “sell capacity” for TPUs than chips. Net: GPUs keep the bulk of spend through 2030 even as select first-party silicon scales, and the market should judge claims against networking choices and workload fit—not headlines.

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