Obviously, a concept (which is an abstraction in more ways than one) is different from a textual representation. But LLMs don't operate on the textual description of a concept when they are doing their thing. A textual description (which is associated with other modalities in the training data) serves as an input format. LLMs perform non-linear transformations of points in their latent space. These transformations and representations are useful not only for generating text but also for controlling robots, for example (see VLAs in robotics).
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Obviously, a concept (which is an abstraction in more ways than one) is different from a textual representation. But LLMs don't operate on the textual description of a concept when they are doing their thing. A textual description (which is associated with other modalities in the training data) serves as an input format. LLMs perform non-linear transformations of points in their latent space. These transformations and representations are useful not only for generating text but also for controlling robots, for example (see VLAs in robotics).