> Are you talking about scaling up neural networks, which is more in the context of the conversation, but requires some very big assumptions about (artificial)

> Are you talking about scaling up neural networks, which is more in the context of the conversation, but requires some very big assumptions about (artificial) neural networks? Yes. But note that under the rubric of "deep neural networks" or "deep learning," I would include a lot of things, including combinations of methods like "deep reinforcement learning," learning by self-play via gradual evolution of surviving models, models that use "dense associative memories," of which transformers are only one special case, and future deep learning methods that have not yet been discovered. And yes, some very big assumptions are required! FWIW, your comments did not come across as standoffish to me :-)