I'm talking about linguistic information here, because I'm interested in linguistics and language learning. Humans abstract phonemes from sound, and morphemes/

I'm talking about linguistic information here, because I'm interested in linguistics and language learning. Humans abstract phonemes from sound, and morphemes/lexical items from phonemes. Once we have a rough measure of how many words of input the toddlers get, we can roughly equate the amounts of _linguistic_ data that goes into acquiring linguistic capabilities. While GPT gets tokens as input, from the lexical lexical level onward, there can be an argument that we can roughly estimate the volume of the _linguistic_ data that goes in to the system regardless of earlier decoding stages. I don't claim that there are a lot of other kinds of data feeding into a human brain, and the modality is totally different. (Multimodal-interactive vs. "predict the next token") GPT, therefore, is at disadvantage in that it needs to learn stuff – other than linguistic stuff – _only_ from linguistic input, whereas a human baby can use world model gained through other modalities as a scaffolding. But for acquiring linguistic capabilities, auditory and visual data seems hardly relevant as input data, other than helping building that the scaffolding that can help "top-down" understanding.