> The cars don't have to increase ISO to get detail, that's for human eyes. Increasing ISO only works because we can't see details in shadows, but computers don't have that limitation. A neural network wouldn't have to add 100 to each pixel to make out detail, like a human would.

I'm not an expert on this stuff but I think you're misunderstanding or mixing up the ISO value with exposure compensation. The ISO value corresponds to the sensor's sensitivity, and even RAW photos (which are more or less dumps of the raw sensor data) are captured with specific ISO values, and look different at different ISOs.

Yes, the ISO is the amplifier gain, essentially.

You are confusing two things:

i) what human eyes need to do to get details from a dark image (increase ISO and risk washing out bright areas); and

ii) what human eyes do when looking out at the real world (rely on the huge dynamic range that the human visual system is capable of, which dynamic range is about an order of magnitude larger than any video camera sensor);

It's worth pointing out however that humans can't make use of that whole order of magnitude range at the same time. The visual system has to gain up and down as the average light in the field of view changes. This takes several minutes or even a half hour to fully dark adapt.

That's ISO and not dynamic range. Dynamic range is what you can see (detect) at the same ISO setting.

This is not how the term is typical used in vision science which is why I thought it was worth pointing out

Sorry, in short you're wrong, yes they do. I'm on my phone so I will be brief.

The ISO determines the sensitivity of the sensor in the camera to the photons hitting each bucket in the "sensor array". This sensitivity combined with frequency of the photon hits determines the data that makes up the actual image. If you could theoretically dump the RAW data from an image recorded for a different ISO for the same image, it would be different for each one.

You can't "boost" an image's ISO post-capture, because the sensor data is already captured. What you can do is increase the values of those pixels that are appreciably close to buy not equal to zero, but for which data exists, giving the impression of pulling out data from the shadows, but the limitations/complexities are too much to go into here. When you do so in practice, you do not have as much relative detail in those extremes.

What we interpret as "noise", typically in high ISO low light photography, is a real thing that the computer cannot perfectly compensate for, because it's a fundamental property of both the hardware, but more importantly, of background light/radiation and the probability/quantum nature of light...