There is a trend towards larger models in the state of the art of deep learning research. The total cost of the on-chip memory on the NVidia GPU is still a good value proposition compared to current custom deep learning accelerators. This cost to get to large on-chip memory, combined with the flexibility of CUDA for other types of scientific applications, makes it harder for such accelerators to compete with Nvidia in such large academic research clusters. I hope that this situation changes over the next couple of years.