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Friday, October 16, 2026· 9799 stock ideas· 217 writers·
16,689 views· 7,671 clicks

From X

@convequity

Convequity on X

We added to Tesla ($TSLA) as a long-term holding in physical AI through Optimus and Cybercab, and we keep the position small. Our view is that an affordable, capable Optimus could become an enormous product, extending Tesla's opportunity beyond its vehicle business. Tesla's batteries and its ability to coordinate difficult industrial supply chains add to that potential. The position stays small because reliability in real working environments, affordability and commercialization timing are unproven. Demonstrations alone do not establish that Optimus is ready for sustained use, and commercialization could take longer than investors expect. Reports that China was slowing humanoid-company IPO activity reinforce our concern that financial enthusiasm can advance faster than the underlying technology. A rumored Tesla facility in Ningbo, near Shanghai, could strengthen the industrial case if confirmed. Its proposed role is to coordinate Chinese suppliers and validate components for Optimus V3. The associated target of 50,000 Optimus units by year-end remains unconfirmed and ambitious, and we do not build our case around that volume. Our interest rests on the eventual product opportunity and Tesla's ability to solve production problems.
@convequity 1 click

Convequity on X

3D chips could create more room for specialist EDA startups. We are not convinced that more difficult chip design automatically translates into a large revenue windfall for $SNPS, $CDNS and Siemens. Fine-pitch stacking changes decisions that used to be made within one die. Put a circuit upstairs and its wires may get shorter, but its heat affects the circuit below. Placement, signal timing and power delivery have to be optimized together across the stack. That creates a reason for $AVGO and $NVDA to build custom tools around their architectures. Broadcom already describes a proprietary design flow built on industry-standard tools. Nvidia publishes its own research on assigning connections across tiers in 3D chips. Our inference is that the chip designers will keep some of the most differentiating optimization work in-house. A startup that solves a costly gap in cross-die planning or optimization could also win business without replacing an entire EDA suite. The incumbents still supply implementation, verification and manufacturing sign-off tools, and they are developing 3D capabilities themselves. Internal tooling is evidence that customers need more than the standard flow; it does not establish that incumbent spending falls. We see a more interesting startup opportunity where a tool can shorten repeated design iterations or improve the resulting chip enough to earn a separate budget. That is the part of the 3D transition we would investigate before assuming the largest EDA vendors capture most of the upside.zz
@convequity

Convequity on X

The Information reports that Anthropic has an unannounced multiyear cloud contract with $IREN. Our view is that it is most likely a contract IREN has already announced and already counts. On 27 August, in its FY26 results, IREN said it had signed a new multiyear AI cloud contract with an unnamed "leading frontier AI lab". In the same release it put contracted annualised run-rate revenue (ARR) for its 2026 capacity at $4bn, against $1bn of ARR operating on 26 August, and said its 2026 capacity was largely sold out. The Information gives no size or term, and neither IREN nor Anthropic has confirmed the deal. If Anthropic is the August lab, the report names a customer but adds nothing to the $4bn. It would only be new revenue if IREN raised that figure, and IREN has not said it will.

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