Earlier quoted context omitted.
Even if the hypotheses hold, a sequence x, f(x), f(f(x)), ... doesn't have to diverge even with f(x)>x for all x. A chain of super intelligences could feasibly have a small upper bound not much greater than that for a single person. That idea even lines up with some crude experimental data -- vast additional resources barely make a dent in the frontier for chess, image recognition, a breadth of graph problems, etc...…
The problem of how to win at chess is bounded in complexity in a way that maximizing computation isn't. To provide an analogy there is a maximum speed anything can move at but it would be laughable if a medieval scholar had wondered if the falcon was near the maximum speed possible. It seems similarly ridiculous to imagine that the human brain just happens to be close to the maximum computational power because it was…
While we're on the topic though, no it doesn't have to be unlikely or strange for people to be near-supremal, and throwing more hardware at the problem doesn't necessarily make it go away:
On some level that idea comes down to defining what we mean by "intelligence." Suppose we can only measure intelligence by proxy by measuring performance on specific tasks. Then the composition of those tasks plays into any final intelligence score. If they're all fully parallelizable then you're totally right that people almost certainly aren't anywhere near the "top," and moreover a "top" probably wouldn't even exist. In standard parlance though, intelligence is something more than the ability to add a lot of numbers quickly, and most of our current measures of intelligence have exponentially (or worse) diminishing returns as more hardware is added.
In that latter case where intelligence is measured by performance on algorithms which are fundamentally hard, people wouldn't be near the top because of some rare process which accidentally made us that way. People would be near the top because _anything_ displaying a modicum of thought would be near the top because of the vastly diminishing returns of additional hardware. As a crude ballpark, if you mustered every atom on earth into its own processor running at 4GHz then you could solve a fully parallelizable exponential problem roughly 4x bigger than what one of Google's newest TPU's can manage.