But it’s able to describe what a fluffiness is. And for us humans, the way I understand fluffiness, is about the sight and the touch senses. We have associate

But it’s able to describe what a fluffiness is. And for us humans, the way I understand fluffiness, is about the sight and the touch senses. We have associated this sight input and this touch input with the label “fluffiness”. Now we throughout our life have experienced this input a lot, but technically this input in its original form is just lightwaves and a combination of our nerves physically touching the fluffy object. This could in theory be represented in many data formats, it could be represented as a combination or group of input tokens. So the understanding for us is just the association of this input to this label. I don’t see how this in particular would give us any special understanding over if just raw input was given to an LLM. It’s just a special case where we have had this input many times over and over. It seems arbitrary whether LLM has been fed this data in this format or in some other format, e.g. text as opposed to lightwaves or touch feedback. This extra input could make those models more intelligent because it could help it uncover hidden patterns, but it doesn’t seem like it would be the difference between understanding and not understanding. Text is just a meaningful compression of this sensory input data.