No one who matters cared if the devices did or did not implement the perfect, ideal memristor. The devices that were built did operate as memory. Quite good memory, too.
The concept of refresh-less, non-volatile, high speed, high capacity zero-wear low power memory is a compelling one, the manufacturers are just too busy enjoying making money out of old tech. It was quite apparent from HP that what they'd got was highly effective and manufacturable, but like the rest of the tech industry they knew that one plays one's cards only when there is no other market option. If you can make $billions selling the same old derivative tripe for a few years more, you do not bring out what you can really do. Everyone does this.
We have a lunatic situation today where there's at least 5 different memory technologies involved in just booting, well, anything (on chip SRAM and DRAM cache, DDR, BIOS eprom (often NOR?) and SSD (often NAND), 6 if you include a TPM too, and 7 if you want to include the mountain of spinning rust that we all depend on one way or other, and 8 / 9 if you're going to throw in tape / optical media too. Having just one sort of memory that can do all of those jobs would be a whole lot better and simpler, but there's a very large number of companies very happy with the current diversity of means of storage.
Apart from the floppy disk makers. We've very nearly weaned ourselves off those, now. And it's been a while since anyone has done anything serious with punched paper tape / cards, or magentic drums, mercury delay lines or cathode ray stores. But those are the only sorts of storage tech we've actually managed to retire.
Memristor and AI
A trick that has been missed is the application of memristor-type memories to AI. AI is mostly all about adding numbers up very quickly. Doing this in analogue electronics is a whole lot more power efficient and quicker; there's even companies make devices that "add up" by adding voltages. It would be possible to sum values in a memristor cell too - the resistance is the sum of the current; timeslice the current for different values, and you get the sum. Now, if one's memory could also be the computational core for AI calcs; that'd be quite convenient. Very "edge" processing too I expect.