If a lemmy.ml user types ‘bitch’ in a comment it will actually get replaced with ‘removed’. They just won’t notice it until they check their own comments. That might be the reason why you see ‘removed’ even though your instance doesn’t have an active slur filter.
The Pirate Bay also doesn’t host content, just links to torrents. Why has it been taken down then several times already?
When you directly link pirated content it becomes a liability. Doesn’t matter if the actual content is on your own server or hosted with a third party.
Yeah, show me how to not get into debt and be able to afford both land and a house. People usually don’t have half a million+ lying around burning a hole in their pockets.
I personally like to keep it on. Most of my messaging is with family and friends and it’s good to know if someone read or hasn’t read my message.
Especially if things are time critical. Picking someone up? Asking if they need anything from the supermarket? If I see that they read the message I know that they are going to reply in a moment. If they didn’t even read the message I won’t have to wait around / can guess that they are currently in the car or wherever.
Sometimes you also have a spotty connection, so the received + read receipt can tell you if they actually got your message.
In general if someone sends me a message and I read it… I’m going to fucking reply to it (if I’m not super busy, and even then I might send a quick message back). I seriously don’t get people who just leave things on read and then forget about it.
And oh shit, when you say you built it yourself: Did you use the Motherboard Standoffs (if they weren’t already in place in your case)? If you didn’t use them you might get random short circuits.
Have you actually checked that all the cables are firmly in each socket? On both sides, at the back of the PSU and on each device (Motherboard, GPU, …)?
But the NAS is in your house… which basically means if it gets flooded/burns down all your data is gone too.
I already have my data on my PC, a second backup inside the same house isn’t worth that much. But instead of relying on a cloud service I just rent a virtual server (for various things) and use Seafile to keep my data in sync.
PC breaks? House burns down? My data is on my own server in a datacenter. My server gets cancelled? My data is on my PCs.
So even with your NAS you are 100% reliant on a cloud backup still, so why did you get the NAS when you already have a copy of your data on your devices?
Are you sure you properly deleted them? Reddit rate limits you to about one edit/delete every 3 seconds. If you go faster than that the deletes fail.
All the comments I have overwritten stayed that way, it was just difficult to reach them all (as different comments show up under “Top”, “Controversial”, “New” and so on).
On the other hand you can lose your email address at any time if you don’t own the domain. So if Google decides they don’t like something you wrote your @gmail.com address could be gone tomorrow. And with it all your accounts you set up (as you need email usually to login or do changes).
The whole e-mail ecosystem sucks :-/
My self-hosted mail server works fine for now, but that could change at any moment.
Without knowing the actual implementation:
I’d wager comments are preserved and don’t get cleaned up over time. Because if content gets deleted the instance has to federate the deletion to other instances to clean everything up (like an event system). If the instance just vanishes there would be no deletion request happening.
If deletion was automatic when an instance goes down we’d have already lost thousands of comments due to the outages lately :)
That’s the case when an instance just straight up shuts down, right?
But if a user deletes their comment this also gets propagated to other instances. Do instance admins have a nuke button to initiate a delete for all content?
Where do you find that this CPU “only has 6 3D cores”?
It’s common knowledge. 7800X3D = 8 3D cores, 7900X3D = 6 3D cores and 6 normal cores (= 12), 7950X3D = 8 3D cores and 8 normal cores (= 16).
So if you mostly game and don’t need the CPU for productivity tasks you should 100% grab the 7800X3D. If you need a lot of cores then grab the 7950X3D. The 7900X3D is garbage in the middle.
Someone already pointed out that a 4090 is a massive upgrade over a 4080, no clue what benchmarks you looked at.
So another suggestion: Why pick a 7900X3D? It’s the worst of both worlds. It only has 6 3D cores for gaming, which might not be enough in the near future (Look up performance benchmarks between a 5600X vs a 5800X for example, there are already games that benefit from more than 6 cores).
If gaming is a focus: Pick a 7800X3D so you get a full 8 3D cores to work with. If productivity is a focus (with gaming on top) splurge for a 7950X3D. You’re already spending an insane amount of money, you might as well get a decent CPU.
Besides that: You are wasting a ton of money on the SSDs. Grab a fast one like that for your Windows drive and for gaming, but for storage there’s much cheaper options (that still deliver 3-6 GB/s, if you even need that). 128 GB of RAM is excessive too, except you have a very clear use-case for it.
TDD is great when you have a very narrow use case, for example an algorithm. Where you already know beforehand: If I throw A in B should come out. If I throw B in C should come out. If I throw Z in an error should be thrown. And so on.
For that it’s awesome, which is mostly algorithms.
In real CRUD apps though? You have to write the actual implementation before the tests. Because in the tests you have to mock all the dependencies you used. Come up with fake test data. Mock functions from other classes you aren’t currently testing and so on. You could try TDD for this, but then you probably spend ten times longer writing and re-writing tests :-/
After a while it boils down to: Small unit tests where they make sense. Then system wide integration tests for complex use-cases.
Multi-threading is difficult, you can’t just slap it on everything and call it a day.
There are languages where it’s easier (Go, Rust, …) but parallelism is an advanced feature. Do it wrong and you get race conditions or dead locks. There is a reason you learn about this later in programming, but you do learn about it (and get to use it).
When we’re being honest most programmers work on CRUD applications, which are highly sequential, usually waiting on IO and not CPU cycles and so on. Saving 2ms on some operations doesn’t matter if you wait 50ms on the database (and sometimes using more threads is actually slower due to orchestration). If you’re working with highly efficient algorithms or with GPUs then parallelism has a much higher priority. But it always depends on what you’re working with.
Depending on your tech stack you might not even have the option to properly use parallelism, for example with JavaScript (if you don’t jump through hoops).
At this point you’re just arguing to argue. Of course this is about the math.
This is Amdahl’s law, it’s always about the math:
https://upload.wikimedia.org/wikipedia/commons/thumb/e/ea/AmdahlsLaw.svg/1024px-AmdahlsLaw.svg.png
No one is telling students to use or not use parallelism, it depends on the workload. If your workload is highly sequential, multi-threading won’t help you much, no matter how many cores you have. So you might be able to switch out the algorithm and go with a different one that accomplishes the same job. Or you re-order tasks and rethink how you’re using the data you have available.
Practical example: The game Factorio. It has thousands of conveyor belts that have to move items in a deterministic way. As to not mess things up this part of the game ran on a single thread to calculate where everything landed (as belts can intersect, items can block each other and so on). With some clever tricks they rebuilt how it works, which allowed them to safely spread the workload over several cores (at least for groups of belts). Bit of a write-up here (under “Multithreaded belts”).
Teaching software development involves teaching the theory. Without that you would have a difficult time to decide what can and what can’t benefit from multi-threading. Absolutely no one says “never multi-thread!” or “always multi-thread!”, if you had a teacher like that then they sucked.
Learning about Amdahl’s law was a tiny part of my university course. A much bigger part was actually multi-threading programs, working around deadlocks, doing performance testing and so on. You’re acting as if the teacher shows you Amdahl’s law and then says “Obviously this means multi-threading isn’t worth it, let’s move on to the next topic”.
You still don’t get it. This is about algorithmic complexity.
Say you have an algorithm that has 90% that can be done in parallel, but you have 10% that can’t. No matter how many cores you throw at it, be it 4, 10, or a billion, the 10% will be the slowest part that you can’t optimize with more cores. So even with an unlimited amount of cores, your algorithm is still having to wait on the last 10% that runs on a single core.
Amdahl’s law is simply about those 10% you can’t speed up, no matter how many cores you have. It’s a bottleneck.
There are algorithms you can’t run in parallel, simply because the results depend on each other. For example in a cipher where you first calculate block A, then to calculate block B you rely on block A. You can’t do block A and B at the same time, it’s not possible. Yes, you can use multi-threading to calculate A, then do it again to calculate B, but overall you still have waiting times while you wait for each result, which means no matter how fast you get, you always have a minimum time that you’ll need.
Throwing more hardware at this won’t help, that’s the entire point. It helps to a certain degree, but at some point the parts you can’t run in parallel will hold you back. This obviously doesn’t count for workloads that can be done 100% in parallel (like rendering where you can split the workload up without issues), Amdahl’s law doesn’t apply there as the amount of single-core work would be zero in the equation.
The whole thing is used in software development (I heard of Amdahl’s law in my university class) to decide if it makes sense to multi-thread part of the application. If the work you do is too sequential then multi-threading won’t give you much of a benefit (or makes it run worse, as you have to spin up threads and synchronize results).
There’s this Computer Science 101 concept called Amdahl’s Law that was taught wrong as a result of this - people insisted ‘more processors won’t work faster,’ when what it said was, ‘more processors do more work.’
You massacred my boy there. It doesn’t say that at all. Amdahl’s law is actually a formula how much speedup you can get by using more cores. Which boils down to: How many parts of your program can’t be run in parallel? You can throw a billion cores at something, if you have a step in your algorithm that can’t run in parallel… that’s going to be the part everything waits on.
Or copied:
Amdahl’s law is a principle that states that the maximum potential improvement to the performance of a system is limited by the portion of the system that cannot be improved. In other words, the performance improvement of a system as a whole is limited by its bottlenecks.
Yep! It only gets censored in two cases:
You are on an instance that censors words like this (e.g. lemmy.ml)
The user who wrote the comment is on an instance that censors this word (which actually replaces it in the comment), everyone sees it censored then