Somewhere in the net of tubes of our AC we have a machine that produces rocks. They randomly shoot of the air vents, please install ballistic shields in front of the vents to stop them from hitting our customers.
Same here, there are some pain points with swaywm (notably screen sharing is only per display, DisplayLink support and screen mirroring is a pain). Most of these points however are IME a worthwhile tradeoff. Sway has also been astoundingly stable (compared to gnome or KDE)
Maybe this is just a question of taste but I never could get along with Javas (or Kotlin's) tooling.
Primarily working in Vim/Helix works for most languages from Nix to Typescript or Rust and C, but Java just never worked quite right. It also generally felt like it had a worse story around tooling from a DX perspective, something like Golang or even npm feels a lot lighter than the molasses of JDK management and gradle et al.
No, I'm not. Through university (and even before) I have access to their full suite. I have tried to use PyCharm, GoLand and Idea.
Idea was useful for Java but felt quite slow and even with vim bindings was a pain to navigate. Learning the shortcuts helped but it never got quite as fast as helix/vim for general editing (especially as my work usually is a polyglot). It might be the best for Java (compared to eclipse or bluej) but that does not mean it fits my workflow/way of work.
PyCharm/GoLand both are "nice" but it did not feel better/more efficient than pylance/pyright)/gopls + vscode/helix. The only I still occasionally use is DataStorm as it is quite a nice SQLite/PostgreSQL client.
Besides doing yourself a disservice of not using a proper IDE, what exactly makes Java not writeable in vim or the like? Like it's a pretty simple language with not much magic going on.
It is there to ensure an animal is not experimented on unnecessarily or with excessive pain. Discussing a process like this might require you to slightly look further than one mostly clear cut case.
Part of his filings will be actually stating the "terminally ill" part and having this approved by an ethics committee. Making a moral judgment here is the committee's actual role as not all cases are so "simple".
It could have been a single informal paper that says "the animal is terminally ill, my judgement call is that this is unlikely to cause excessive suffering and might help instead, even if the chances are low, and if my judgement is proven wrong and this appears to cause excessive suffering the animal will be put down humanely". Signed by the veterinarian and the owner.
Because the system is high speed low drag, and trusts the veterinarian and the owner to make reasonably good calls about pet health and suffering - unless proven otherwise by overwhelming evidence. The system trusts people by default, and that 3 months long process and an ethics board come into play when there's a suspicion that this trust may have been abused.
Of course, that's not the world we live in. Which is why we're having this conversation.
A solar farm isn't a few panels on your roof, it's a large installation in a field.
Also in the UK it would probably be a civil lawsuit, which doesn't have a jury, although if you violate a civil court order you can still get a jail sentence.
That is not really accurate? Linux traffic control (tc, [0]) exists since Kernel 2.2. It can introduce traffic latency and a few other network conditions, like packet loss.
Hmm kind of... I was referring to the fact that dummynet models pipes with a fixed bandwidth and centralized scheduler. Packets are released according to very high precision transmission timing. This means that serialization delay, queue buildup, and link behavior are simulated in a way that resembles real network conditions. Dummynet can provide a highly deterministic timing and queue behavior, which made it popular in networking research and WAN emulation experiments. TC cannot do that with the same accuracy.
I think much like other tools, think SELinux vs OpenBSD (unveil, etc) TC is more flexible (does more things) but there are _some things_ that can't do, and even for things both can do *BSD solutions are much simpler.
The curriculum in my university mostly didn't change. Most CS topics didn't change through ML research.
The main change was in testing/exams. There was a big effort towards regular testing assisted by online tools (to replace the system with one exam at the end in favor of multiple smaller tests). This effort is slowly being winded down as students blatantly submit ChatGPT/Claude outputs for many tasks. This is now being moved back to a single exam (oral/written), passing rates are down by 10-20% iirc.
Going into CS as a career will be interesting but the university studies/degree are still likely worth it (partly spoken from a perspective where uni fees are less than 500€ per semester). Having a CS degree also does not mean you become a programmer etc. but can be the springboard for many other careers afterwards.
Having a degree and going through the effort of learning the various fundamentals is valuable, regardless of everything being directly applicable. There is also the social aspects that can be very valuable for personal development.
> The problem occurs when you place them all in one school, and force them to learn everything, even things they don't want to learn about
A difficult part is that children aren't really in the position to know what they want to learn most of the time.
Sure, many prefer sports over math but covering a broad spectrum in pre-teen and teenager education is quite important to get them develop these preferences and themselves as a person. They are given more agency/choice (electives etc.) as they grow up.
There are also topics you need to learn that aren't fun/engaging (especially as fun/engaging is quite subjective and depends on the individual). Especially when those topics are prerequisites to other potentially fun topics (you will have to learn the fundamentals before engaging with advanced topics in most subjects)
Regulatory capture through a higher barrier to entry. Any social media platform that wants to compete with Meta's portfolio will now also need to have an age-verification system in place (which is guaranteed to introduce higher costs). Meta can likely afford to eat the costs here as a tradeoff for the higher impact on smaller players.
It also gives them more information on users as a bonus. Further, verification with a real ID is also a quite effective barrier against excessive bots.
Look beyond the CA law, states have already passed laws that put the liability on app and website developers to ensure users aren't kids, there's no passing the buck to Apple or Google.
This one notably also explains the design considerations for golangs M:N:P in comparison to other schemes and which specific challenges it tries to address.
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