I would like to know: Yes, it take really a lot of compute and time to train e.g BERT. (probably 64 V100) and 3 days of training. BUT once it is trained, and yo

I would like to know: Yes, it take really a lot of compute and time to train e.g BERT. (probably 64 V100) and 3 days of training. BUT once it is trained, and you want to use it on your application. Inference time usually take a few ms, is it far longer with bert? And does a modern smartphone can easily run such inference? I've heard about mobilenets but they sacrifice too much accuracy, so I really hope BERT can be run today on a 7nm snapdragon + it's mini TPU. I can't find such data on the web but this is an elementary question, necessary for complete success of Nlp. throw compute at it because we're Google/OpenAI Sorry but for training time, neural network deep learning is far from a "smart" paradigm. It is essentially statistical brute force + a few clever math tricks. This is a part of the answer on how to create an artificial general intelligence. But where's is the research for creating a causal reasoning system understunding natural language? It mostly died in the AI winter, and except a few hipsters like me or opencog or cyc, is dead. I wonder how many decades will be needed for firms like Google to realize such an obvious thing (that real intelligence is statistical AND causal).