Inside LinkedIn’s AI ‘cookbook’: How engineers scaled GenAI to 1.3B users by distilling models to 220M parameters for a 10x throughput gain.

palantir hit $175/share because they understand what 99% of AI companies don't: ontologies. in 2021, the word "ontology" appeared 0 times in their earnings calls. by Q3 2024? 9 times. their US commercial revenue is growing 153% YoY. why? because LLMs are becoming the commodity, while ontologies are becoming the moat. let me explain why most enterprise AI initiatives are failing without one: every enterprise has the same problem: 47 different systems ❗️ 19 definitions of "customer" ❗️ 34 versions of "product"❗️ business logic scattered across 100+ applications ❗️ you throw AI at something like this? it hallucinates. but if you build an ontology first? it gains the context and data depth to be able to reason. palantir figured this out years ago. but here's what palantir doesn't do: verticalize at scale. they're brilliant at defense, government, contracting. but specialized industries need specialized ontologies. take telecommunications. a telco's "customer" isn't just a record - it's: ➕ a subscriber with multiple services ➕ a hierarchy of accounts and sub-accounts ➕ real-time network states ➕ billing cycles across geographies ➕ regulatory compliance per jurisdiction Orgs have tried to standardize this before. but standards aren't ontologies. they're just vocabularies. this is why Totogi has spent so much time and effort building their telco-specific ontology layer while palantir was perfecting horizontal enterprise ontologies, we went deep on telecom's unique semantic complexity. now telcos can deploy AI that takes one action - 'activate new customer' - and correctly translates it across systems that call it 'create subscriber' (BSS), 'provision user' (network), 'establish account' (billing), and 'initialize profile' (CRM). No more manual steps, no more dropped handoffs between systems. palantir proved the model. but they can't be everywhere. the future belongs to industry-specific semantic platforms like Totogi's BSS Magic 🚀 | 18 comments on LinkedIn

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