Comment by vineyardmike
2 days ago
> the moat might be in the hardware and vertical integration.
The moat is the products that can be built. The moat is always the product - because a differentiated product can't be a commodity. And an LLM is not a product.
Google and MSFT and Meta have already "won" because they have profitable products they can build LLMs onto. Every other company seems to be burning cash to build a product, and only ChatGPT is getting the brand recognition to realistically compete.
Building an LLM is like building a database. Sure a good one unlocks new uses, but consumers aren't buying something for the database. Meanwhile enterprise customers will shop around and drive the price of a commodity down while open source alternatives grow from in-house uses to destroy moats.
Even hardware isn't a true moat. Only Google has strong vertical integration with their TPUs, and that gives them a lead. BUT Microsoft, AWS, Meta and a whole bunch of startups are building out custom silicon which will surely put pressure on them and Nvidia to keep innovating and earning that price edge.
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.
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.
Oracle is doing great just selling databases. Having your data is a moat.