This seems very theoretical, just a lower bound on space required, without talking about what is being computed. Does it have any import on real algorithms?
It's a reduction from multitape Turing machine to tree evaluations. If your "real algorithm" is straightforwardly modeled by a multitape TM, then it might be possible to use this proof to reduce the space. Otherwise, I don't think so.
It does have an impact. It wont give you stackoverflow like code to copy-paste though.
Analogy is thermodynamics says how efficient a heat engine _could_ be. If your engine is way below that you know there how much of an improvement there _could_ be, that it's not an impossible problem. That will get people to build better stuff.
Upper bound on the space required. Anything, that is computable.
> Does it have any import on real algorithms?
It depends on the constants, but if the constants are good, you can have VMs for example that make memory usage smaller.
> Does it have any import on real algorithms?
As-in algorithms you'll care about if you're a programmer and not overly interested in theory? Not really, no.
Lower bound tells you how much it's worth to improve the SOTA. It gives you a hint that you can do better.
So it's more like polar star. Maybe not directly practical, but it will lead tons of people in the right direction.