It's quite a bold claim, as scientists and ML engineers are also working on making simpler models (for example, compare GPT-Neo to GPT-3, or Stable Diffusion to Dalle-2), building interpretability methods (such as SHAPley), and pushing forward systems that focus on using extracted covariates from models as a source of insight for decision-making, instead of using the algorithmic itself to make the decision. Who knows what approach will approach will be dominant when "true" AI emerges.