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And that is very strange for me. Under the news about AI-search from OpenAI I asked about comparison with AI-search from Kagi, but got a lot of downvotes and a link to the post where the author express his negative opinion about AI.

My question was about benefits of openai search compared to kagi search. How is this link related to my question?

What are benefits of using openai search when we already have Kagi that is much more privacy a friendly, is ads free and provides the same functionality?

What do you think, how long should we wait until the overflow in the debts database makes the value negative?

I think it can be done like a NFTs on top of Bitcoin. In this case evey archived page is NFT and all the blockchain is available, so there is no centralized cite. If each action will require some computations (PoW) then ddos attack or spam attack will be very hard to implement.

I think that proof-of-work approach to blockchain can make ddos attacks much harder, but I’m not an expert too :)

Sounds like a potential application for a blockchain techs, that allows to do verifications, voting and consensus.

https://github.com/1RandomDev/showly-oss

As I can understand from EFF articles, the problem is not only in MAGA guys and their conspiracy but in KOSA proposal itself.

https://www.eff.org/deeplinks/2024/09/new-us-house-version-kosa-doesnt-fix-its-biggest-problems

For me the problem is more in GPL violation: they distribute blobs under GPL3, user made a request of the source code by creating an issue, but they ignored that request. It is not only about “you have to fix it” versus “just fork it” imo.

Problem of Proton Drive is not only in the missing linux client. There is no support of WebDAV that makes integration with many open source tools (like note taking apps or photo management tools) almost impossible. Nextcloud is much better for me. Without a WebDAV (or one of other popular APIs) it looks like an attempt to create “walled garden” with vendor-lock on Proton, imo.

I asked the same question in c/privacy, you may find some answers useful: https://lemmy.ml/post/15694049 For myself I chose plausible

No, I have two different things:

• org-mode files with schedule, diary, tasks, etc.
• knowledge base, org-roam (orgnote). I have a single base but it contains graphs about topics and these graphs are not connected

I like that approach, because I use orgzly-reviwed on Android with a notifications. And because it is simpler to maintain knowledge base.

Yes… org-mode is more than 20 years old… It is a price of flexibility: I have a strong feeling that one can adjust org-mode to any workflow. But I do not use even a third of the org specification. There are a lot of cool blog posts like “org mode quick start” or “org mode basics”, I would recommend to start from such posts, not from a documentation.

For me one of the most flexible and mature way to knowledge base, tasks and notes is an org-mode.

I have two main workflows. The first one is task management. I have a lot of recurring tasks with tags, deadlines, schedules, etc. All of them are living in org-files in my Nextcloud. On Android I’m using orgzly-reviwed for sync via WebDAV, on my work I’m using organice (via WebDAV) as a “web-version” and also I’m editing my notes in emacs on my laptop (but actually any text editor could be used).

The second one is a knowledge base. I’m using org-roam locally (and with a localhost web server, built in into emacs) and orgnote for Android/Web + synchronization. My knowledge base is Zettelkasten-based.

Orgzly-reviewed: https://github.com/orgzly-revived/orgzly-android-revived

Organice: https://github.com/200ok-ch/organice

Orgnote: https://github.com/Artawower/orgnote

Orgnote provide a way to encrypt all notes by your own key/password. With orgzly I’m relying on Nextcloud encryption.

If I already use Pandas for processing my data in-memory, CoW can significantly improve the performance. That was my point.

If you are doing data processing in pandas CoW allows to avoid of a lot of redundant computations on intermediate steps. Before CoW any data processing in Pandas required manual and careful working with code to avoid the case described in the blog post. To be honest I cannot imagine the case of offloading each result of each operation in the pipeline to the storage…

deleted by creator

Written in Scala ❤️

The title is very click bait imo. It is not about any private data. It is a very specific case of deleted fork of the public repository. It is a bug, of course. But it doesn’t look so serious as I was thinking when saw the title.