Leaked Google document: “We Have No Moat, And Neither Does OpenAI”

OpenAI is now the clear leader in LLM APIs - a position that 4 years ago Google was arguably in the default position to win. The failure of Google to capitalize on its many advantages specifically in AI has been striking. It feels like a Xerox Parc moment of inventing transformers, having all the talent, data, and distribution to build the seminal ... See more

‘openness’ often enables systemic exploitation of developers’ and creators’ labor while maintaining the infrastructural and ecosystem dominance of the largest firms. In the context of high levels of corporate concentration and gatekeeping over the ingredients necessary to build AI systems, ‘open’ AI as currently operationalized is primed for corpor... See more

LLMs are a moat, but for how long?

An LLM vendor like OpenAI isn’t an aggregator, As far as I can tell.

• An aggregator leverages a monopoly on demand to commodify supply .

• Whereas a traditional industrial monopoly leverages a monopoly on supply to extract $ from demand .

LLM vendors seem more like a traditional industrial monopoly. Like an industr

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The moats are in the customers, not the data. We predicted that the best generative AI companies could generate a sustainable competitive advantage through a data flywheel: more usage → more data → better model → more usage. While this is still somewhat true, especially in domains with very specialized and hard-to-get data, the “data moats” are on

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Weaker defensive moats due to the commoditization of AI models and challenges with data network effects.

The seals around corporate research are never airtight: team members leave to found their own AI startups, and some groups like Microsoft Research, Facebook AI Research, and DeepMind still publish articles on their most meaningful contributions. But broadly speaking, if one of these companies makes a unique breakthrough—a trade secret that could ge

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However, a key risk with several of these startups is the potential lack of a long-term moat. It is difficult to read too much into it given the stage of these startups and the limited public information available but it’s not difficult to poke holes at their long term defensibility. For example:

• If a startup is built on the premise of taking base L

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