This is just wrong. I wish you would pay more attention to what you don't know than what you do know.
You are mssing several key things:
1) all waveforms can be represented as the sum of a series of sinusoids. The more sinusoids in the series, the more accurate the model of the original waveform (even if it was not composed of any sinusoids to begin with. This is the basis of both Fourier analysis and Fourier synthesis, which are key concepts in the abstract representation of wave data. There are a few complications with this model, but for the purposes we are discussing here, it is 100% complete and accurate.
2) Nyquist's theorem proves (and note that I said *proves*, not "asserts") that sampling at a given sample rate provides enough data to reconstruct **PERFECTLY** any signal made up frequencies up to the sample rate divided by two.
2) the interpolation done by digital-to-anlog converters is based on a combination of points (1) and (2), and results in **PERFECT** reproduction of the original waveform (if (and only) the clocking is identical). In reality, there is no "low-res". See Monty's example of 8kHz sampling rate in the video.
Your comparisons with letter shapes is actually somewhat apropos, but only for letter shapes formed by band-limited waveforms. You can, in fact, synthesize letter shapes (or any other shapes) using fourier synthesis, but it is slow and generally not how typography works. If you do know how it actually works (e.g. the specific spline algorithms that will be used by a font renderer) then you can, in fact perfectly "sample" a font with a handful of points per letter that will feed the spline rendering algorithm. The data is generally called a TTF (TrueType Font) file, and is used by your computer all the time.
Speculating on interesting ways to abuse/use points (1), (2) and (3) has been a rich source of ideas for audio engineering and processing for about a hundred years. It doesn't do a lot, however, to carry out this speculation without a basic background in signal processing in general and digital signal processing in particular.