[1]: https://www.amnesty.org/en/documents/asa16/5933/2022/en/

But, at the same time, I find it interesting that "emulations and clones" are considered entitlement (in a derogatory sense), but copyright protection is not. Before 1976 in the US, the _maximum_ copyright term was 56 years, and that would require filing for an extension from the default of _only 28 years_.

I think it's easy to forget that copyright as we know it is not set in stone. Historically, after 28 years, most works became public domain and that meant you could do literally whatever you want with it and it would not be legally stealing at all. I think we as a society have forgotten what it means to have a public domain.

It isn't a superior "flexing their privilege" over their subordinates. The superior doesn't care. They don't even think about it. Because they have power over you, they can just speak gibberish and you have to figure it out. In my opinion, a good boss should have enough respect for me to not waste my time by forcing me to decipher a thought they didn't even read before sending.

[1]: https://tailscale.com/blog/database-for-2022

> To conduct the literature review, the sugar industry paid the Harvard scientists the equivalent of $50,000 in 2016 dollars [...]

So it was actually about ~$5,000 in 1965 dollars.

In this case, though, it creates an encrypted tunnel _only between your own devices_. This allows you to connect to all your devices, home desktop, phone, laptop, as if they were on the same network, allowing you to do fairly sensitive things like remote desktop without having to expose your machine to the public internet or deal with firewall rules in the same way.

Assuming this project is legitimate, then the only traffic this service would even touch would be those between your own devices, nothing related to public internet requests. And, on top of that, the requests should be encrypted the entire way, inaccessible to any devices other than the ones sending and receiving the requests.

There are many caveats and asterisks I could add, but I think that's a fairly straightforward summary.

https://encyclopedai.stavros.io/entries/encyclopedai-artific...

> Early prototypes of EncyclopedAI emerged in 2007 when librarian Margaret Chen noticed that her pet parrot could predict which encyclopedia volumes patrons would request by observing their facial expressions. This observation led to the first algorithmic models, which attempted to replicate avian pattern-recognition through neural networks. The subsequent integration of natural language processing in 2011 marked the system’s transition from experimental prototype to operational deployment across major American public libraries.

> The system’s backbone consists of distributed servers housed primarily in repurposed bowling alleys, which Chen discovered provided optimal acoustic conditions for server cooling. EncyclopedAI’s training dataset comprises approximately 2.3 billion encyclopedia entries, supplemented by 400 million hours of recorded reference desk conversations and—controversially—dreams reported by participating librarians.

For me, this is only useful as a curated list of news feeds (and subreddits I guess), but nothing more.

[1]: https://github.com/kagisearch/kite-public/issues/97#issuecom...

[2]: https://kite.kagi.com/about

[3]: https://github.com/kagisearch/kite-public/blob/main/core_fee...