The opinion of Linux desktop users (or any users really) do not count in the enterprise world. Somehow, if management bought in on the Crowdstrike rootkit bandwagon, you'll see it on corporate hardware. It doesn't matter if it's a bad plan; it doesn't matter if it gives an American company a backdoor to all you infrastructure; if the CISO decides everyone gets it, everyone get it.

The only thing you can really do as a lowly employee is keep any such device away from any personal info or network as if it's infected by malware (which I would argue is exactly what it is).

As a bytecode tinkerer, I'd say considering NOP to be global knowledge is a slippery slope.

just tag yourself as "early-access" and suddenly everyone will forgive your flaws.

As a developer, I really don't like how Wayland has fractured the ecosystem. Competing immature protocols are still all over the place while the immobility of x11 has spoiled us for years. It's getting better, but in the meantime I can still write an x11 app which will work mostly everywhere (thanks to xwayland), whereas a wayland app may not work everywhere (not on X11, and not on compositors which don't implement the right combinations of protocols).

Hacker: That's ok, we don't want you to paste stuff in there, we just want you to send us your cookies. It's not like you're eating them anyway…

Consider IEEE754 arithmetic as monadic, simple!

Someone is confusing indices and cardinality.

The dude trying to push Django in 2003

The EU is basically slapping Canadians with a reciprocal policy. Canada has the eTA (electronic travel authorization) which they have to file and pay 7$ to visit, even if they don't need a visa. This is the same in reverse.

It seems like they also have a "password grid" multi-factor option that you can print. I hate seeing custom authentication schemes (or insecure ones like SMS) instead of standards like OATH-TOTP, but I do applaud having accessibility options.

This! I see the hype around AI and it's like everyone has lost their mind. You wouldn't accept a statistical study without sampling info (dataset size, origin, selection, filtering, bias, reproductibility, etc). Why would we not ask the same with LLM or generative AI? It's like everyone got so excited about models built on large datasets that they forgot we already had procedures for handling data.

You might be surprised how inefficient banks can be when it comes to tech. As years go by I see an increase of tech workers but a decrease of experienced or competent ones. My view is those competent tech workers tend to be more expensive than Canadian companies are willing to pay, thus end up hiring 10x the staff. The banks simply have more money to waste that way and thus are doing so by hiring a lot of tech workers.