At this point, we should just be looking at IPC improvements at the same frequency/voltage and power consumption to see if there are any improvements.
And yes, sure, more cores are nice, but tons of useful software is still bottlenecked by single core speed. So is general computer responsiveness.
I refuse to believe at current high end intel/amd levels (i7-9 & ryzen 7-9) & even mid-range that lack of responsiveness is due to the CPU rather than windows/mac.
You are right, of course, in that the fault lies with software. But holding the software as constant, the only way to improve responsiveness is to up your core speed and IPC.
It's not as if the average user can email Microsoft of the Chrome browser team and ask them to make the OS/Browser more responsive for their older hardware. But they _can_ go to the store and buy a faster CPU, most of the time.
The situation was probably reversed a few decades ago, when hardware was actually expensive and multi-core was not a thing.
 - I’m talking about Office 365 which runs in a web browser (yet somehow is no slower than the “native” version that runs on my desktop computer).
Again the "poster boy" for responsive interaction is probably BeOS - the original BeBox used dual ppc 603 CPUs at 66mhz: if you consider IPC, Mhz & number of cores a modern CPU probably has 1000x the computation power at its disposal & RAM is also generally 1000x more plentiful (we have as many GBs as we used to have MBs back then). I'll bet with GPUs the difference is even bigger.
Typical RAM module (DDR-266) in late 90s could only provide ~2.1GB/s, leaving almost no room to perform any compute on a single 4k screen, and simply insufficient to run two of them.
PC66 of early 90s could only do 0.5GB/s.
DDR3, commonly used now in integrated GPUs does 13GB/s.
What I am getting at, is that the task to just copy pixels to a screen became proportionally harder as RAM progressed forward (26x faster per module since 1990, 6.5x per module since 1999 vs 60x more work per screen since 1990 (256 colors), 10x per screen since 1999).
And that is just screen rendering. Same happened to source code, documents, images, everything.
It's interesting to see approaches like Apple's where more and more of computationally heavy work is moved onto what are essentially special purpose purpose ASICs (I think you can generously expand the definition to even include GPUs). Specific examples include video decoding, graphics, and increasingly ML computation. Once those things become "free" what is left? I'd say mostly just many layers of abstractions atop basic computation.
As more and more software stacks become ergonomic w.r.t. multithreading & multiple execution contexts, single core becomes less of a bottleneck. IMO that's the ultimate solution to the hard physical constraints of Moore's Law. Short of a new type of compute substrate.
Originally the law relates to the transistor density of an IC, but this was strongly correlated with Power Consumption, Clock Speed, and a bunch of other metrics. As we reach smaller scales these parameters are no longer tightly coupled. I recall seeing a plot to the effect that Power Efficiency tapped out at 14 nm. Likewise clock speed has not been increasing at the original clip for the better part of a decade (it went up ~50% in 10 years, which in any other area of engineering would be astounding, but I could sure use a 32GHZ processor).
Anyway, having trade offs makes things more interesting and perhaps we are going to see an era with more cleverness chip architecture soon.
And I'm not counting the circuit paths - this would be on a straight line of copper.
People will like to show you graphs, especially with 10 - 50 years time scale. Well you will still see a straight line, because only the end tip of that graph is beginning to curve.
Assuming a perfect execution, TSMC will get you ~1.8x transistor density improvement every 2 years all the way till 2030.
You may also want to read  David Kanter on Transistor Density. But TD;LR not all transistor shrink at the same ratio, 1.8x is the best case scenario.
I've also got an NVIDIA performance graph, since GPUs scale well with transistors: https://docs.google.com/spreadsheets/d/1dukdlqkh-zPkhmjUVuUL...
For context, the last entry is the T4 (aws g4dn), which is 12nm
Not exactly doubling every two years, but not far off. Moore's Law is dead, long live Moore's Law!
We are not on track, haven't been on track.
Though it was "number of components per integrated circuit" https://wikipedia.org/wiki/Moore's_law
So... larger chips areas could continue it... I've thought that huge wafers, at slower clocks, would make sense. In a PC, tablet or even phone, there is plenty of physical room.
Not sure if the barrier is technical or just present usage and economics.