This blog post discusses the architecture and findings of Apple's MM1 paper on Multimodal Large Language Models. It explores the abstraction of input for Large Language Models, the image encoders, vision-language connectors, and the results of different ablations and pre-training data. The post highlights the impact of image resolution on performance and the potential applications of multi-modal LLMs.
