[dsco]

See I kind of buy the database argument but also kind of don't. A database needs an operator whereas a LLM doesn't. You're basically melting the product into a piece of goo and the UI can be approached using natural language.

For products that still need a UI you could claim that LLM operators take over, so that's still a tax you pay to the incumbents as you interact with a product. It's sort of like we take the money which was paid to SQL operators and engineers and instead pay it to the hyperscalers.

[vineyardmike]

LLMs absolutely need an operator - who runs the servers and GPUs that hosts the models? Who writes the system prompts? Who fine tunes and trains the models? This can be a big cloud api like AWS, but it can also be a custom-in-house service for a company.

Users of LLMs don’t quite have an equivalent employee to a DBA, but neither do most customers of AWS DynamoDB or RDS or whatever.

Many use cases of LLMs won’t be chat bots like ChatGPT. They’re be tools for automated summarizations, classifications, etc. They’ll be automated assistance and basic tool calling, etc. They’ll perform OCR and documentation analysis. Automated translations etc.