[sligocki]

Counting the number of distinct TMs is not a simple task. The way you count it is the most broad (the count of all tables of values where each cell can have any (symbol, direction, state) combination). But this is a significant overcount of the bits needed to describe an arbitrary TM. for the BB(3, 4) case, there are only about 600B distinct TMs using the Tree Normal Form aka Brady's algorithm (https://nickdrozd.github.io/2022/01/14/bradys-algorithm.html) which comes out to <40 bits.

[tromp]

Similarly, 2^n would be a huge overcount of the number of n-bit closed terms, which is given by OEIS sequence A114852 [1]. There are 36140122614 ~ 2^35 closed terms of size 49 bits (length of a straightforward self-delimiting encoding). So in that sense it's still a smaller lambda term computing an incomprehensibly larger output.

[1] https://oeis.org/A114852

[jonahx]

Do you know of any (hand-wavy is ok) intuitive explanation for why this machine will halt, beyond the inductive proof's given in your article? Just watching the machine run, I would guess at some kind of infinite behavior. It is remarkable that this is not the case.

[addaon]

> Do you know of any (hand-wavy is ok) intuitive explanation for why this machine will halt, beyond the inductive proof's given in your article?

If the Halting problem could be solved by intuition, it wouldn't be much of a problem.