$PANW valuation exercise. Not investment advice. A quick sum-of-parts relative valuation using $CHKP, $ZS, and $CRWD. Simply just add up each ones market cap and compare the total against $PANW.

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#DeepSeek report

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4/ Nevertheless, the show goes on. Gigawatt-scale data centers are on the horizon – each capable of hosting 600k+ B200 in 8.3k GB200 NVL72 racks.

3/ Hyperscalers are nearing their threshold. As the scaling of OOMs continues, CAPEX levels are rising to the point where investors are increasingly focused on AI ROI and shareholder returns.

2/ Google’s 2025 CAPEX plan of $75B triggered a 7% sell-off, but every hyperscaler seems set to keep expanding CAPEX, which bodes well for both $NVDA and $AVGO.

😂😂😂.

$CVNA report on Substack. Link in bio.

Open-source ontology frameworks like RDF, FOAF, and Good Relations have made the internet what it is today. Without these we wouldn’t be able to search and find things so easily online. SNOMED AND UMLS are ontologies for healthcare, allowing different IT systems used by doctors, pharmacies and insurance companies to communicate in a shared codified language. The issue is ontologies are really hard to do which is why all these are open source because it is incredibly hard for one entity to manage - but not for PLTR. And ultimately we’ve seen this as their core advantage since we first covered the stock in Jan-21

They are the only company that can create customised ontologies. Furthermore they are the only company who can do this with high-grade security, governance, and access controls. Ontologies are extremely hard to do. $AMZN has an ontology for Amazon, $META has an ontology for Facebook/Instagram, and a few other big tech names. But these are internal to them; $PLTR creates customised ones for each enterprise.

Ontologies aren’t just an intermediary layer; they encode domain expertise AGI will still need for reliability in high-stakes fields. Even if AGI builds its own conceptual structures, ontologies provide explicit meaning and inference rules for interpretability and alignment. LLMs still rely on knowledge graphs — AGI won’t make ontologies obsolete, just more refined.

@OestaOne Indeed AGI will learn much faster on ontologies compared to pre-AGI models. But that doesn’t mean an ontology will be a commodity when that happens. You’re conflating the intelligence of AGI with the ontology.

@OestaOne An ontology is bespoke to each enterprise, so ... no.

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