Not necessarily. The bloom model (a GPT competitor and similarly sized) was trained on 1.5T of text, which reduces down to 350B unique tokens. If you took a histogram of those unique tokens, it would have a very long tail with probably 1% or less being well represented. That leaves 350M common tokens to serve as the basis for token tuples being fed into crowdsourcing. There are probably ~2-5B very common token sequences, if you had 5 people view each token sequence and give it a few scores, and that process took ~1-2 minutes (these sequences are short), that leaves a conservative estimate of 50 billion person minutes, or ~34 million person days. If you paid these workers $15/hour, that comes out to $12.5 billion dollars, which is not prohibitively expensive for any big tech company when spread out over several years, particularly when it provides a massive competitive advantage.