Thanks for the references, I'll have a look. I can tell you what I don't want: books that throw theorems one after the other without any context, like Baby Rudin[1] for instance.
I tried once to read Terence Tao's Analysis I[2], it's really good but my main problem was that I wasn't able to know if my proofs are correct when I do an exercise. So maybe the solution is to get a teacher.
I'm looking for mathematics books that take the time to explain with words and sentences what is actually going on when they introduce a new theorem, something that focuses on meaning.
Honestly I understand OP, I also run GrapheneOS but most of my social life happens on whatsapp and I know it's stupid but I can't change dozens of people's choice to install Signal, even though most of them know the issues with Meta.
My hope is that one day or another whatsapp will enshittify so bad that people will be more prone to move to Signal in the same way that recently Windows got so bad that many users moved to Linux.
I recently talked with a researcher in social sciences, he told me that the point of political systems like citizen assemblies is about making good decision as much as teaching people how to discuss difficult topics in non violent ways.
Why store "childhood memories" on an online service though? Those websites get hacked all the time, you're lucky if your privates pictures don't endup in the wrong hands...
Do you all use local models only for coding? What about using them as decision assistant? For instance, I work in science and sometimes I have many scattered ideas that I'd like to feed into an LLM so I can refine them and extract a meaningful research question. Are local LLM suited for that task?