I assume the development fizzled out after several rounds of investment and no interesting results demonstrated. Not to sound dismissive, but I just see this pervasive pattern of failure in AI projects which aren't built from the ground up for learning.
If your basic system cannot learn solving at least some problems initially, it drastically lowers the probability of it acquiring learning capability later in development lifecycle.
Disclaimer: I don't have specific AI/ML expertise, but I've known the founder (Ben Goertzel) for close to 20 years now.
OpenCog never got huge amounts of money. Ben believes strongly in developing AGI (he actually coined the term). There are a few core researchers and developers that have worked with him for decades, also mission-focused. So I don't see development "fizzling out". There are also newer efforts such as SingularityNET.
Development seems alive and well, based on activity at https://groups.google.com/g/opencog, though it is mostly done by a single person these days (the author of the OP)
A general criticism about results may have some validity - When I added cross-platform capability to a part of the project back in 2016, I found an obscene amount of technical debt.
That said, I don't think your criticism is necessarily a good one to make. I'm not aware of any projects that have much in common with OpenCog or Ben's other work. The approach is very different, but again, I'm not an AI/ML expert and only understand this based on comments from others in the AGI community. My gut feeling here is that there's more to the story, or something otherwise doesn't add up, as you are attributing the project with a failure mode apparently shared by the majority of AI projects.
Can you name some examples of projects which are doing the right thing in regard to learning? I'd be genuinely interested in checking them out.
I'd also encourage posting your criticisms to the OpenCog mailing list and I'd expect someone there to address them in good faith. In any case, if you're enough of an expert to be able to make those sorts of criticisms correctly, there would certainly be value to be found in your complete argument.
If your basic system cannot learn solving at least some problems initially, it drastically lowers the probability of it acquiring learning capability later in development lifecycle.