Of course, it would be great if EK suddenly returns, and syclone buys him a tesla or two...
Apart of this... Some unrelated thoughts below.
Finished reading some of the ePL docs. They are pretty good btw.
In general, it looks like not many people (if any) have read those docs, as though the doc (for example
https://docs.xel.org/learn-epl.html) is quite good and is written pretty well, it clearly lacks proofreading. It contains big number of typos, some mistakes, and some (though small) parts are not understandable, probably they are edited in a hurry. All this shows the real interest in the project was never high among followers... There were people who spent their time writing a good doc, but no people to spend some time to read it and provide feedback :/
Anyway, after spending some more time thinking on the topic, I'll try to address some of the issues Ismail123456 raised.
In my opinion there is basically no chance that this project will be revived.
From the point of view of computer science (CS), there is no use for this approach. In theoretical CS we learn how to classify problems in terms of their computational complexity (P, NP, EXP, NEXP,...). We think that some problems in NP are intractable (but we don't know for sure).
Tractable problems (the ones in P) can be solved in reasonable time, while intractable problems cannot be solved in reasonable time in general, no matter how much computational power you throw at those problems (not considering quantum computing). In general there is no hope in trying to solve an intractable problem by guessing, which is what this project is aiming at.
In short: From the point of view of computer science, this is a hopeless approach.
(1) First of all, the expression "In general there is no hope in trying to solve an intractable problem by guessing" is not correct. There is definitely a
hope to solve intractable problem by guessing, but there is no
guarantee it will be solved in polynomial (reasonable) time. So the conclusion "From the point of view of computer science, this is a hopeless approach." is not correct as well. It is not hopeless approach at all, it is just an approach which doesn't provide
guarantee of solution.
The practice shows that though even if in general case the solution cannot be guaranteed, in many (and very often - in most of) practical cases solution can be quite easily found either by so called 'guessing', by brute force, or exhaustive search, or by other selective search methods.
One example from practice
Long time ago when still learning in university, I was offered a task to develop a program to automate the timetable generation for the several university departments. Usually the process of compiling the schedule takes a lot of time from department management, so the higher management decided automating it could save valuable resources of department staff. This is a typical JSP (Job shop scheduling problem), and of course I was told by our computer science experts, who were proficient on JSP theory (and in general were much better in
theory than
practice) that task to generate optimal timetable is intractable and in general case has no solution. Well, but who cares about general case? I was well aware that this task was successfully completed by university staff two times per year for many years, and though it was a bit time consuming, it was perfectly solvable. So long story short, I developed that program, and it worked very well. It was generating a timetable by 'directed' search, starting from the seemingly the most promising variants. To get a more or less acceptable solution it needed to work just under one minute, but the longer it worked, the better timetable it generated. Now I recall that this task is an ideal task for solving with XEL (with some needed enhancements in storage capacity, sure).
(2) Secondly, some study of the documentation show this project is not solely aiming at solution of a problem by guessing. Yes, the example in the doc finds prime numbers by guessing and testing, but this is not the only use. Except random guessing, this approach is good for brute-force search, and for some other search strategies too.
(3) Thirdly, though I didn't work in a scientific research for very long time, and so I do not know all the cases where the XEL's approach could be applicable, I see at least one case where XEL's capabilities fit very well: those are the problems solvable by a whole class of methods - Monte Carlo ones (
https://en.wikipedia.org/wiki/Monte_Carlo_method). In my opinion (as a person, who personally used this method for problem solution in computational physics), it is a perfect match. You can perfectly parallelize such tasks, run them on computers of very different capacities, and bring the results together then. The more samples you generate and analyze, the more precise your solution will be.
In short, in my humble opinion - though intractable problems are not solvable for general case, in most practical cases solution can be found. And random guessing is by far not the only way this platform could be used.
I find this approach far from being hopeless, and platform far from being unusable. It just needs to be used correctly; for right set of tasks. And of course, it needs people willing to work on it, not purely speculate...
