

Again: What is the percent “accurate” of an SEO infested blog
I don’t think that’s a good comparison in context. If Forbes replaced all their bloggers with ChatGPT, that might very well be a net gain. But that’s not the use case we’re talking about. Nobody goes to Forbes as their first step for information anyway (I mean…I sure hope not…).
The question shouldn’t be “we need this to be 100% accurate and never hallucinate” and instead be “What web pages or resources were used to create this answer” and then doing what we should always be doing: Checking the sources to see if they at least seem trustworthy.
Correct.
If we’re talking about an AI search summarizer, then the accuracy lies not in how correct the information is in regard to my query, but in how closely the AI summary matches the cited source material. Kagi does this pretty well. Last I checked, Bing and Google did it very badly. Not sure about Samsung.
On top of that, the UX is critically important. In a traditional search engine, the source comes before the content. I can implicitly ignore any results from Forbes blogs. Even Kagi shunts the sources into footnotes. That’s not a great UX because it elevates unvetted information above its source. In this context, I think it’s fair to consider the quality of the source material as part of the “accuracy”, the same way I would when reading Wikipedia. If Wikipedia replaced their editors with ChatGPT, it would most certainly NOT be a net gain.
Joplin is great. I have its data stored locally with encryption, and I sync across devices with Syncthing. It also has built-in support for some cloud providers like you mentioned, and since it supports local encryption, you don’t need to depend on the cloud provider’s privacy policy.
Setting it up on multiple devices was a bit complex, but the documentation is there. Follow the steps, don’t just waltz through the setup assuming it will work intuitively. I made that mistake and while it was not the end of the world, it would’ve saved me 15 minutes if I’d just RTFM.