Because they trained the text model. Then froze the weights. Then trained a vision model on text image pairs of progressively higher quality. Then trained an ad

Because they trained the text model. Then froze the weights. Then trained a vision model on text image pairs of progressively higher quality. Then trained an adapter to align their latent spaces. So it became smart on text then gain a new input sense magically without changing its weights