Everything in SDR has an analog equivalent, from local oscillators to PLLs to filtering. In fact most of it simply is a direct implementation of decades-old analog concepts.
But the underlying math is what I found most incredible, where the "true" representation of a signal is complex, and that every real (both in the ordinary and mathematical sense) signal is actually the sum of a positive and negative frequency, such that the complex component cancels out. Phase becomes much more comprehensible as simply the angular component of the signal, and frequency is the derivative of phase. All of this had the indirect effect of improving my understanding of complex numbers as well.
This always strikes me in the "oh no look at all the cheating!" anti-ai takes.
Like, the cheating only blew up because there was/is the gap in teacher/professor/moderator understanding of the tools. Kids were copying wikipedia back in the day, and if the kid had a decent vocab, went completely undetected for a time. Then everyone thought they could do it and scorers got suspiscious enough to create a demand for an "is this wikipedia" software such that companies made them and scorers implemented them. We even saw reversions to written exams, and have had continuous use of written exams in 'critical' tests like SAT et al.
And of course, the only reason that the teacher's ensure that the students aren't cheating is because they know the students are heading for tests they can't cheat. So, there's new cheating, there will need to be new detection.
A motivated learner today has unprecedented capabilites compared to a motivated learner of even 10 years ago.
Assuming, of course, that the learner is practicing universally accepted study/research methods such as never implicitly trusting single sources, especially when they're third hand summaries of unverified sources.
I've had proffesors give me incorrect information with every bit of certainty an LLM offers, but it wouldn't be their fault if I just nodded along with either of them.