One thing it taught me was how the different sub circuits come together to make a power or operational amplifier. Long tail pair aka differential amplifier, current mirrors, current sources, Vbe multiplier, class A stages, Class AB stages, etc. Another great article which builds on it is https://sound-au.com/amp_design.htm. This is where you get to see how these building blocks come together. This basic topology is present in most amps be they little op amp chips or big beefy audio power amps: input -> diff amp -> class A gain -> class AB buffer -> output.
Interesting to learn that there isn't much difference between a little TL071 and my Rod Elliott P3A.
BTW, NwAvGuy, the audio guru who have vanished, has some interesting criticisms on the dismissal of opamp in the audiophile community. https://nwavguy.blogspot.com/2011/08/op-amps-myths-facts.htm...
That said, there are claims that analog computers will make a comeback: https://spectrum.ieee.org/computing/hardware/not-your-father...
It’s like how a city contains many buildings, but it also contains roads etc.
One of my projects at my day job was an analog front end for a digital system, where part of the analog circuit was attached to a sensitive optical detector held at liquid nitrogen temperature. But the majority of signal processing was done in the digital domain.
After spending a lot of time looking at parts and considering multiple approaches, the simplest answer was to do the slower aspects in the CPU and use a 4-quadrant Multiplying Digital/Analog Converter (MDAC) to do the heavy lifting (signal multiplication).
ISTR that doing it all digitally would have required a processor with at least a 40MHz clock and probably a separate 200MHz clock to implement a 1-bit DAC. And I would still have needed extra circuitry since one of the inputs (and both outputs) could swing +/-10V.
Not to say that the all-digital approach wouldn't have worked, but the development cost would have been overwhelming for something that probably won't sell more than 200 units or so. By using an MDAC and a couple of opamps, the design was reduced to an Arduino "shield."
Have to say, it works pretty damn nice :-)
(Work on better manufacturing is still relevant for digital computers, of course. But the work leads to lower-power devices, not more accurate computations. Years ago, we used 5V logic because the average manufacturing tolerances gave acceptable differentiation between 5V and 0V. As manufacturing got better, 3.3V worked fine, then 1.2V, and now even lower. The result is wasting less power.)
There are certainly physical processes at work that limit how "good" of a digital computer we can build... the question is whether or not there is something about manufacturing analog computers that scales better than digital computers, and when we get to the limits of die size or how small features can be with lithography, if analog computers will become competitive again. I kind of doubt it. But I know pretty much nothing about this area.
I imagine that there are some analog circuits that would directly solve complex polynomials or perhaps differential equations without iteration, which would not suffer the error amplification problem. I don't know how common the equations or systems that those circuits solve for are in most scientific or other application use.
That's currently already a challenge, tiny changes have large differences in performance of the network.
For example, drawing a simple anti-aliased line on a computer produces results that depend (at the pixel-level) on the software stack and or graphics card used. Nobody ever complained (much) about that.
(Then again, it may allow your computer to be fingerprinted more easily).
I'd imagine any hypothetical implementation of a NN will be fairly difficult because of that.
Also achieving linearity cheaply (especially multiplication) is very difficult.
(Don't forget that analog systems have limited gain-bandwidth and noise immunity)
I've read this before used disparagingly; quantum is "just analog." Is that really the case? Is quantum computing is simply the ultimate miniaturization of analog computing?
Reading the recently disclosed "quantum superiority" paper from Google that was somehow leaked by NASA one could be convinced that quantum is "just analog." The paper deals in "resonance", "coupling", "filter" and "attenuator"; it reads like the description of a superheterodyne transceiver; analog RF.
This reverse-engineering story points out that the speed of analog computation is due to the effectively parallel processing of the op amps. This aligns with the description of qubits also working in parallel.
One thing is certain; classical analog computers are vastly easier to understand. An op amp is simply an electrical function. So now I'm really intrigued; Is quantum computing really "just" faster and smaller analog?
 The actual PDF has appeared: https://drive.google.com/file/d/19lv8p1fB47z1pEZVlfDXhop082L...
This is the scaffolding for measuring and manipulating quantum states. Quantum computing itself is not "analog" in the original, signal processing meaning of the word: the states are not isomorphic analogies for modelled physical processes.
Quantum computing is (somewhat) analog in nature, but it's not "just analog". In theory, taking advantage of quantum physics in the computer gives you an improvement in asymptotic complexity (not just a constant factor speedup), one that you can't get any other way.
Some early tilt rotor aircraft used analog computers for stability control.
I know BB well thanks to tinkering with their isolation amplifiers for an old data acquisition project. also familiar with them due to working on equipment from the 70's/80's with the really old BB 3451 monoblock isolation amplifiers.
There is a big memory hole, at least in the people I interact with about the personalities around the various semiconductor companies. Nerdy (Maxim,XMOS) dorky (Green Arrays) serious (ST) irreverent (Fairchild), sloppy and fun (Microchip). Companies like TI are in it for the money, others have a passion for engineering and solving civilization's problems.