[orbital-decay]

>Of COURSE it doesn't know the rules of chess and doesn't know how to move the pieces.

That depends on what you mean by knowing. Surely it extracted certain higher level correlations from the recorded games and chess books, and is able to make certain predictions based on them. I would call it knowledge, it isn't that good though.

The main problem is that the model is purely functional, and is unable to store the state (except for the context, which isn't what I mean). Both humans and chess engines keep track of the figures and run stateful algorithms constrained by the rules. This model doesn't do that, which severely limits its capabilities in chess.

[2-718-281-828]

A disk has also knowledge stored on it but it doesn't know anything.

[orbital-decay]

The disk is unable to extract the correlations, nor is it able to apply the knowledge; it transparently stores the data verbatim. The model doesn't store the training set, it extracts the complex correlations from it, and is able to make actual predictions based on the knowledge it extracted.

But yeah, the "knowledge" and "understanding" are hard to define formally, so this discussion can be endless. Common well-defined terms are required.

[2-718-281-828]

the model does not extract knowledge. an external algorithm trains the models parameters and then the model is fed a string that is also evaluated externally based on the models configuration.

[orbital-decay]

Semantics. You could say the same about the disk - the data doesn't get magically teleported from the magnetic plates to the RAM, it needs a lot of underlying hardware to read and transfer it.

Model is not just a set of weights, it's inseparable from the underlying architecture, the way to train and to apply them in practice.

[2-718-281-828]

> You could say the same about the disk

that's exactly my point

[orbital-decay]

Yeah, and that's arguing about semantics. We could do that in a loop endlessly, ignoring the fact they're fundamentally different.