I've seen a lot more of these types of visualizations pop up in blogs recently but they don't feel as high quality as the ones on this site.
But on the other hand, I also wonder if those that get pumped out now, also uses up all the oxygen in the room for the really great ones.
Like, someone shoddily slaps together one for concept X. It's not great, has some misunderstandings, and what it visualizes is mostly random and not the vision of the maker. But it goes semi-viral, and beat everyone else to the punch. So it ruins someone else's motivation to do it properly.
Anyway, the motivation here is just that the existing explanations are already bad, and AI helps with motivation here because it makes it super easy to do a better explanation if you know what you want. I doubt that the it really sunk in and that she could properly wrap her head around it yet, but I'm sure that whenever she's ready to really think about that, it's a much better explanation than any of the ones that exist today.
I am in awe of your Daddying, whether nature or nurture.
You should reproduce more!!!
Accessibility with AI is hit-and-miss; if you don't tell it to make things accessible, it either will or it won't, and then it'll just continue with whatever trajectory it chose. If you tell it to do accessibility initially, it'll see its own ARIA later and continue in a similar vein.
From very anecdotal experience, I find OpenAI models more likely to consider accessibility for greenfield projects, even when not asked to, but this might just be an accident of statistics.
Because he's writing the WebGL code by hand. It was crafting these entries, not merely producing them for internet points.
(also tufte: https://en.wikipedia.org/wiki/Edward_Tufte)