In some ways AI is naturally centralizing.

The centralization is implied due to the capital requirements of training and inference, the existence of proprietary models, and the efficiency of scale in serving.

Centralization would be bad if there were stickiness to models.

But if you treat the model as a dumb, stateless machine, giving an answer to your prompt and then forgetting, it doesn't matter much; they don't accumulate data to accumulate power.

It's once the model starts getting a memory^[akk] that the power dynamics turn into something possibly compounding.^{[akl][akm][akn]}

The fact that LLM providers are now commodity and also that the API is the same and easy to swap to a different provider at the flip of a switch helps reduce the likelihood of centralization of power.