I think it is safe to say that learning a joint distribution of vision + language, is fully possible at this stage, demonstrating by this work. But 'understand

I think it is safe to say that learning a joint distribution of vision + language, is fully possible at this stage, demonstrating by this work. But 'understanding' itself needs to be further specified, in order to be tested even. What strikes me most is the fidelity of those generated images, matching the SOTA from GAN literature with much more variety, without using the GAN objective. It seems Transformer model might be the best neural construct we have right now, to learn any distribution, assuming more than enough data.