It’s so fucking stupid. We don’t need an AI water shortage. The water exists, it’s just not in fucking tax havens like Texas elon.

Course, can’t blame the corpos that governments wont do their damn job protecting citizens water supplies.

Also, aren’t these places pretty hot!? Capitalism is weird.

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Lol they get a capable chatbot that blows everything out of the water and suddenly they are like “yeah, this will be the last big thing”

Link?

That might be worth it. Is bitwarden self hosted FOSS?

They have given me errors when trying to register with a hidden iCloud email.

People have still blocked my iCloud.

If it’s an unknown or less popular service they are less likely to add it to a blacklist IME

That’s impossible, the email aliases are under their domain. You’d have to change all your accounts. I’m not doing that again. Hopefully they just change their tune.

Well since in proton the email alias feature is integrated into the password manager (which is really useful) I don’t see them as that unlinked. It would be like having a password manager without the ability to make random passwords, basically pointless. One compromised service and my email will be spammed across the internet until the end of time.

Every account I have on the internet has a unique randomly generated email that forwards to my real email.

iCloud and Proton are the two big names that support this. It’s invaluable.

Yeah but without email aliases it would not be worth it

I did weeks of work migrating every password and email address to proton. Sucks the stances they are taking but now I’m kinda stuck, and it’s still better than Google.

Embrace zettelkasten as your note taking workflow. It’s more organized 😅

It’s insane obsidian isn’t open source, since it’s just a fancy vscode plugin or fork basically (idk how they developed it obviously but that’s all you’d need to do). That’s why I don’t use it. It’s too simple not to be OSS

Yeah Logseq is actually a much better knowledge management tool than obsidian. It’s literally built for that, whereas obsidian requires you to force structure onto it.

Just because other tools use # in other ways doesn’t mean they aren’t useful the way they are now in Logseq. It’s just a one character shorthand rather than four characters. I find tags as they are in Evernote and Obsidian exceedingly worthless for all but the most strictly organized individuals, not so in Logseq. Call them what you will.

A query is helpful when you need it, but rarely needed.

Well I think the first thing is just simply that documents aren’t notes, so you wouldn’t write those things in Logseq.

What you are writing in Logseq is a zettlekasten, which is just a personal knowledge graph. And in a knowledge graph, everything needs to relate somehow to everything else, that’s why it has to be an outline.

So things can relate to the journal date they were written on, to their parent and children concepts, and to the links that they contain. Every idea has at least a relationship to the date you wrote it, but hopefully you can link that idea to more than just that relationship. You want to organically rediscover that next time you make a cake, that eggs are bad for your allergies, and be able to trace that you discovered that at this doctors appointment on this date.

Otherwise, how would you ever find anything? And more importantly, how would you rediscover it organically when researching other concepts in your graph?

Obsidian purports to help you create organized knowledge graphs, but it makes you plan your organization up front. Logseq lets it evolve naturally and organically, by giving you the necessary tools and constraints.

I actually find the lack of distinction between a tag and a wiki link a breath of fresh air. So many other apps make a meaningless distinction between them and make you choose ahead of time a styleguide for how you plan to use both. Logseq makes a queryable style enforced and then you adapt to using it. Very different

Minhash might be able to produce a similarity metric without needing exactness and without revealing the training data.