This can be considered good news. If all data is exhausted people will be actually forced to research better data-efficient algorithms. We humans don't ingest 100 GBs of arXiv papers to do research and we don't need billions of images to paint a cat sitting on a sofa. Until we figure out how to run GPT-3 on smartphones (maybe using neuromorphic computing?), we shouldn't be too worried about the trend of using bigger and bigger datasets, because small(er) networks can be successfully trained without that much data.