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This article, based on the sharing of researcher Victoria Lin, systematically reviews the mainstream technical approaches of native multimodal large models (Chameleon, Transfusion, MOT) and their pros and cons. It points out that multimodal AI is still in the early exploration stage, with open problems such as gaps in scaling laws, inconsistency between image understanding and generation encoding, and connection with the physical world.