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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.
@convequity

Convequity on X

$RBRK's backup engine breaks data into fixed-size blocks, for example 4 MB, and stores only the unique blocks across backups. Commvault and Cohesity instead divide data into variable-sized chunks, with the boundaries set by the content itself. Each design has a trade-off. With fixed blocks, a small change inside a block means the whole block gets written again, so Rubrik uses more storage. In return, hashing and comparing blocks is simple, which means faster backups and lower compute overhead. With variable chunks, only the changed portions are written, so storage use is much lower. Working out chunk boundaries and hashes as the data comes in takes more CPU and memory, which can slowdown backups. Cohesity offsets part of this with a scale-out architecture that processes in parallel across nodes. The two designs fit two different jobs. Variable-length deduplication suits long-term archives, where storage cost matters more than speed. Fixed-block deduplication suits recovery after a hack or ransomware attack, where fast restores and predictable performance matter more than saving storage. That matches how each company started. Rubrik came into the market in 2014 focused on security and on getting critical data back quickly after a breach. Cohesity started from a different idea. It built its own file system that spreads data across many servers, each with its own computing power. Backup copies stay readable like normal files, so companies could search and analyze them where they sit, without restoring them first. Security came second. The two are now moving closer together. Cohesity has leaned much more into security and recovery, especially after buying Veritas's backup business in 2024.

Investor Letters

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Boyz in the Hood

Robinhood’s AI agents, 24/7 equity trading and 10:1 crypto perpetual futures encourage higher retail trading velocity, leverage and…

HOOD $98B
WHAT ARE WE DOING? “Contrarians At The Gate”

Vertiv Holdings Co. (VRT)

Vertiv's 33% stock decline followed a 2026 forecast increase, despite a $15 billion backlog and rising AI data-center demand for power and…

VRT $94B
SixSigmaCapital: Navigating the Financial Markets

Research Roundup Vol. LV

OpenAI’s enterprise privacy push and Synopsys’s Factory 2 royalty model anchor a technology roundup, alongside oil above $100 and Bitcoin’s…

SNPS $97B
Monte Independent Investment Research
VEEV · long

Veeva Systems INC

Veeva Systems is a vertical software company valued as if its best growth years are behind it.

VEEV $46B
Value Investors Club

New Position (ONON): Game is On

On Holding (ONON) is gaining sportswear share, expanding store space and launching soccer with Kylian Mbappé as investors debate U.S.

ONON $11B
Aurelion Research 3 clicks

Deep Dive: Intuit ($INTU)

Intuit’s $21.4 billion software franchise faces AI-driven pricing pressure in tax and accounting, even as QuickBooks and TurboTax retain…

INTU $79B
Rebound Capital 4 clicks

Canterra Minerals: Research Note

Canterra Minerals increased Lundberg indicated tonnage 55% to 26.1Mt, with 226.2Kt of contained copper equivalent, supporting a Buchans…

EQX $13B
Atrium Research - Equity Research

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