Will it be a full copy of the original algorithm - the same exact implementation? Often not.
Will it be close enough to be useful? Maybe.
LLMs use human language data as inputs and outputs, and they learn (mostly) from human language. But they have non-language internals. It's those internal algorithms, trained by relations seen in language data, that give LLMs their power.
I personally believe that our thinking is fundamentally grounded/embodied in abstract/generalized representations of our actions and experiences. These representations are diagrammatic in nature, because only diagrams allow us to act on general objects in (almost) the same way to how we act on real-world objects. With “diagrams” I mean not necessarily visual or static artefacts, they can be much more elusive, kinaesthetic and dynamic. Sometimes I am conscious of them when I think, sometimes they are more “hidden” underneath a symbolic/language layer.