If you consider transformer models progress towards AGI, then I think the answer is hardware.

There really isn't anything too shocking or new about the transformer architecture, it is derived from statistics and ML concepts that have been around for a while.

Of course advancing the architecture and training methods is important but the only reason these models did not exist sooner seems to be hardware cost efficiency.