Pre-language learning of conceptual structures

In current large language models, learning is based on supervised training using gigantic language datasets. Human learning begins differently: before having significant language capabilities, infants acquire a broad range of meaningful concepts, relationships between concepts and their implications, with little or no supervision.

I will describe examples of modeling infant-like acquisition of meaningful concepts and early conceptual structures. I will use the results to make comparisons with AI models, and discuss whether early conceptual structures can contribute to them.