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@calvinblissett 1 click

Calvin Blissett on X

Reposting because of the amount of work I put into this and how quality of an opportunity I think it is. A 300bps rate hike affects 9% of NI. I think Wall Street still thinks it’s same old keep every loan or wholesale interest rate sensitive $SLM. Not giving them credit at a LTM 5.8x multiple for the new expanding TAM and Capital light partnership model. Just like it took Wall Street ages to figure out $FNMA in the early 80s when Lynch was accumulating every share he could.
@convequity 8 clicks

Convequity on X

We think the gross margin gap between Cerebras ($CBRS) and NVIDIA ($NVDA) says little about which company delivers compute more cheaply. Cerebras reported a 14% gross margin in Q2 2026, against roughly 75% for NVIDIA. That is not a clean comparison, because Cerebras's commercial agreements include customer warrants. A customer warrant gives a buyer of Cerebras compute the right to buy Cerebras shares at an agreed price, adding potential equity upside to the compute it purchases. Cerebras records the value of these incentives over time as a reduction in revenue. Its cost of delivering the compute stays the same, so the full amount comes out of gross profit and its reported gross margin falls too. Add the warrants and a few other items back and Cerebras's Q2 margin was 41%, so the reported gap tells us little about what each company spends to deliver equivalent compute. Cerebras could challenge NVIDIA with attractive economics on selected workloads without matching every capability of NVIDIA's platform. In our view NVIDIA's stronger answer is Feynman reaching customers on schedule with the 3D-stacked SRAM we expect. Stacking more fast memory close to the compute would reduce the need to fetch data from slower external memory, helping NVIDIA narrow the architectural advantage behind Cerebras's fast inference. NVIDIA's adoption of Groq technology could ease some of this pressure, but we believe Groq's current architecture remains weaker than Cerebras's for low-latency inference. The longer Feynman takes to arrive at scale, the more time Cerebras has to win customers.
@convequity 5 clicks

Convequity on X

We see Nova ($NVMI) as a potential next-generation KLA ($KLAC), and we are backing it to take a larger share of semiconductor process-control spending. Its wins with leading chipmakers are strengthening that case. A leading global foundry has selected Nova’s materials-measurement tools for production of its next generation of transistors. Another chipmaker has adopted a different Nova platform for the same transition. These wins show Nova securing a place in the manufacturing processes behind more advanced chips. KLA’s broader process-control business has a strong emphasis on finding and analysing manufacturing defects. Nova is more concentrated on measuring chip dimensions, material composition and the chemistry used in production. KLA also competes in these areas, but they are more central to Nova’s business. These measurements help manufacturers understand whether each production step is delivering the intended result and where adjustments are needed. As logic chips and memory stacks become more complex, manufacturers need tighter control over the structures they build and the materials they use. Small variations can hurt performance or reduce the number of usable chips. We expect this to increase demand for Nova’s measurements and create more opportunities for its tools to become essential to production. In our view, the Western semiconductor supply chain badly needs new entrants. Equipment leaders $AMAT, $KLAC, $LRCX and Tokyo Electron, design-software vendors $SNPS, $CDNS and Siemens, and $TSM in manufacturing are too cautious and slow to match the pace of startups and highly driven Chinese challengers. Protecting existing products and the returns on past investments can make these incumbents reluctant to pursue technologies that threaten their established businesses.