The speakers discuss the continuous learning process involved in choosing the model architecture for biomedical generalist models. They highlight the effectiveness of teaching the model the notion of an image using tags instead of fine-tuning with multiple images. They also emphasize the importance of assembling a reasonable bag of tricks to optimize training large language models and the accumulation of know-how in leading organizations.

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