Wednesday, October 28, 2026

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$NVDA vs $AVGO: The Optical Edge NVIDIA can keep growing while facing pressure from more directions. Custom chips, optical supply constraints and specialized inference systems give customers more reasons to consider alternatives. Broadcom’s optical capabilities could help it win the accompanying compute order. Customers need both accelerators and the optical components that connect them to bring capacity online. Securing those components alongside an ASIC purchase could shift the customer’s platform choice toward AVGO. Control across lasers, photonic and electronic chips, and packaging also gives Broadcom more freedom to optimize the complete design. Embedded lasers could reduce the laser power required, easing dependence on scarce, high-power external lasers, although replacement becomes harder. For AVGO, this remains a potential design route. NVIDIA can respond through partnerships, but separate suppliers still have their own margins and product priorities. Google ($GOOGL) and Amazon ($AMZN) are expanding the alternatives through TPUs and Trainium. Our ABBX model allocates 10GW of Anthropic’s 13.8GW planned capacity to those two platforms. The plans span different timelines, but show how a few large buyers could redirect substantial spending away from GPUs. Huawei adds pressure through its integrated optical approach and the prospect of Chinese models supplying cheaper tokens internationally. That could affect both hardware choices and the prices compute providers can charge. Cerebras ($CBRS) targets workloads where faster responses matter. It can compete for latency-sensitive decoding without replacing GPUs across every stage of inference. NVIDIA’s defenses remain substantial. GPU batching supports high total output, flexibility across workloads matters, and its ecosystem is deeply established. Customers can use GPUs for prefill and specialized chips for decoding. Wider enterprise model development would also favor NVIDIA because smaller buyers have less reason to fund custom-chip programmes. At comparable valuations, we prefer adding to AVGO: it can benefit from custom-silicon adoption while helping customers secure the optics needed to deploy it. For NVIDIA, the key question is how much market share and pricing power it retains as customers gain more alternatives.

ORCL Update

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Danaher’s robotics era

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My Last GFL Update - Hopefully

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Are Neoclouds Dead?

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Reddit: Deep Dive Analysis

Reddit generated $805 million in Q2 2026 revenue, 95% from ads, but slowing Google search referrals expose AI-driven traffic and…

Qualcomm Inc. (QCOM)

Qualcomm supplies chips for on-device AI agents and data center inference, with Meta and AWS agreements expanding its role across both…

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