Yes, in many cases companies do not feel comfortable with their code leaving their network. This presents an interesting technical challenge as most of the larg

Yes, in many cases companies do not feel comfortable with their code leaving their network. This presents an interesting technical challenge as most of the large scale transformer models require large amounts of resources not only to train but even to serve. We DO offer an on-prem version of the product that while requiring a decent GPU, does not exactly require people to go out and buy a fleet of TPUs. I personally think there will be a lot of developments in the efficiency of these models (e.g. DeepMind's RETRO) as well as the usual compute efficiencies always improving. However, I also believe there will always be an incentive to make the models as big as resources allow, because "more is different" as PW Anderson said in his famous essay and I give kudos to the OpenAI team for pushing the limit on these models.