Something weird is happening with LLMs and chess

Maybe I'm really stupid... but perhaps if we want really intelligent models we need to stop tokenizing at all? We're literally limiting what a model can see and how it percieves the world by limiting the structure of the information streams that come into the model from the very beginning.

I know working with raw bits or bytes is slower, but it should be relatively cheap and easy to at least falsify this hypothesis that many huge issues might be due to tokenization problems but... yeah.

Surprised I don't see more research into radicaly different tokenization.

How would we train it? Don't we need it to understand the heaps and heaps of data we already have "tokenized" e.g. the internet? Written words for humans? Genuinely curious how we could approach it differently?