I found an old Computer Shopper from the late 1990s and had forgotten how ridiculously expensive computer equipment was - the real sub-$1000 market wasn't even a thing for PCs until 1997, and the range between a sub-$1000 computer and an expensive one was astounding even for day-to-day tasks.
I won an AT&T Safari NSX/20 laptop [1] in 1992 in the ACM Programming Competition. RRP was $5749 then, for a 386SX processor running at 20MHz, 4MB RAM and a monochrome screen. $10,200 in today's money. It was actually a beautifully made machine.
A year later, I switched to a Dell with 386DX and a 387 math coprocessor because my PhD needed the number crunching. That cost twice as much (i.e. around $20k in today's money), paid by the military lab sponsoring my research.
In our current times of cheap compute, it is easy to forget how much top-end computers cost 25-30 years ago.
>the real sub-$1000 market wasn't even a thing for PCs until 1997
YES! I was at intel when they were doing the initial research to even see if a <$1,000 machine was feasible. With the celeron... and this is when they were literally paying millions to companies to optimize to the intel processors so they had software that would be subjectively digestible by the market to purchase software and machines thinking that they were getting compute power for their buck.
I sometimes laugh to myself when people complain about the price of GPUs. Yes, $10,000 is a lot, but in historical context, it's pretty reasonable for top of the line technology.
Beyond graphics, I think of all the "terascale" talk in the high-performance computing world when I was in school. Now your consumer GPU does multiple Tflops instead of hoping a supercomputer to maybe possibly reach 1 Tflop some day for a few lucky users.
The same thing has happened with RAM and storage. My first Linux PC had 20 MB of RAM and 80 MB of disk and was sufficient to do most of my CS projects at university in the early-mid 1990s. Now, a sub $200 smartphone has over 100x the space, while desktops are commonly 2000x.
The research side not only moved on 1000x to "petascale" but that's now boring and there is real talk of "exascale" with the same gleam in the eye. One million times the performance we dreamed of at the beginning of my career, though I think this is partly by expanding the scope of one machine to larger and larger distributed systems as well as scaling up the capacity of individual elements.