Right now the claim is that the current algorithms carry us way further.

The limiting factor is indeed computing power and good data. The last shift is that you need to grow the labeling of good tokens(desired outcomes) with the data.

There is also a lot of work done on chips, which are only used to train AI models and good data is created on mass. It is all coming together fast because there are also using models for data cleanup labeling.

Of course it is always possible that we hit a wall with the current algorithms soon but it looks very promising.
and the knowledge is walled off. The general principles of how OpenAI and Google archived their level are out there. So we have many companies driving us forward.