I think this article was a very good article. The two women are very similar, and different in their own way. I love how hard they fought and how important their jobs and information is, and as soon as something happens they do not like, it wouldn't push them down it would make them want to achieve more to prove everyone wrong.

This whole article teaches about the fundamentals of ChatGPT's language and how to generates to make perfect answers. While people think the transform method is easy, it comes in handy when wanting to use ChatGPT to find answers or are just curious how everything seems to always be correct on ChatGPT.

I think the big picture of the article is implying that with the prediction and language of AI start to get more complicated and complex, it gives it abilities that match humans. While people argue for this, people also argue against the idea and imply that AI is just mimicking human reasoning and pattern.

[[Jorge Arango]] interviews Veronica Erb on Annotating Books

Anecdotal evidence that dyslexia has an overlap with creating links to see a "bigger picture"

Example of someone (u/HerrRey) who defines zettelkasten as "concept oriented, atomic notes that are linked to each other", but who doesn't use or exclude "IDs or the folgezettel method". Interestingly they feel like they're not getting the "big picture" of their work.

Is there an affordance in these missing pieces that prevents them from seeing the big picture because of what they're missing? Is it just neurodiversity? Are they not creating outputs which connect the small to the big, and thus missing it that way?

SQL: experimenting with table-free data

Objectives: Motivations students have for college. Identify personal motivations as pathways to goals.