Amid the many uncertainties in the artificial intelligence field, one thing has always seemed clear: bigger and more expensive systems produce better results. Hence the relentless fundraising of model developers like $157 billion OpenAI and the mammoth capital expenditures of Big Tech groups. Now, however, that kernel of certainty seems to be disintegrating. Having run out of novel data on which to train the software, researchers are struggling to get smarter outputs simply by throwing more resources at the problem. The gold rush phase may be ending, opening the field for nimbler new competitors.