That’s already pretty cool! It surely does generate very random numbers. I still think you can take it a step – or a random number of steps, hah! – further by repeating the process a random number of times! Maybe this way we can reach maximum randomness. Probably need to reroll the number until it’s big enough for that.
I would also check if the result is 4. If it’s 4, it should be discarded. 4 is not an actual random number but a joke random number from a comic.
And group people based on how loud their snacks are.
Also, am I the only one hating that person who keeps talking how the seating is suboptimal while everyone else tries to watch the movie?
That might be the unfunniest xkcd I’ve seen so far. It pretty much reads like a table “things which are so and so hot”.
Then null will be returned, as the value of b.
That causes problems with culture/language/communication.
Like the saying “from 9 to 5” could not be applied to other timezones anymore. Or when reading direct speech in a book, “Let’s meet at 15:00”, you wouldn’t be able to tell anymore what time of the day that means.
Since both approaches have pros and cons, I think we would need overwhelmingly good arguments to justify a change.
Let’s jump straight to decimal time then.
1h23m45s is 1 decimal hour, 23 decimal minutes, and 45 decimal seconds, or 1.2345 decimal hours, or 123.45 decimal minutes or 12345 decimal seconds; 3 hours is 300 minutes or 30,000 seconds. This property also makes it straightforward to represent a timestamp as a fractional day, so that 2023-10-26.54321 can be interpreted as five decimal hours and 43 decimal minutes and 21 decimal seconds after the start of that day, or a fraction of 0.54321 (54.321%) through that day (which is shortly after traditional 13:00)
And this wasn’t just any but fuck man. It was the “perfect but fuck man I love”!
Falling in is only “definitely fatal” if it’s too big. For all we know, black holes can be tiny and light. We can debate if you can still “fall in” one of those. Maybe the process is more like passing by, or some mote of dust sticking to your clothes.
Make a comment with your conclusion and how you arrived at it.
If applicable, report the post.
signs may only apply to the road after them, so you could validly stop just before it.
My thoughts exactly; problem solved. Just do what the first sign says before the others apply.
I don’t think we were talking about the same thing. You’re talking about restricting your behaviour, “focus on your niche”, “stay away from propaganda media”. My proposal was to use an instance which makes it unecessary for you to restrict yourself to certain areas, if their moderation policy aligns with your default behaviour.
Of course it ultimately comes down to similar things, since instances which do not care wether you’re nice aren’t allowed in all places which require you to be nice. The key difference is still that you don’t have to be wary yourself. It sounded as if you would not like that.
I’ve seen it fairly often by now; many people seem to enjoy posts with moderately long comment sections. I believe this is what contributes to a more wholesome experience.
Similar to how groups meet a natural breaking point when they grow too big and people cannot know each other anymore, I imagine huge comment sections create a sense of being meaningless and unheard. This discourages sensitive voices, and may appeal more to people who don’t care anyways, which isn’t exactly a great attitude for social encounters.
I can further imagine large comment sections create FOMO for the reader, and can overall be more stressful, which leads to aggression.
Just guesses and impressions. No idea if true. Also no clue how to foster that environment in a growing network.
Agree to everything but the doom. Yes, most people will only give 1 chance to a platform, but we haven’t churned through most people yet. Most people are yet to honor Lemmy with their first visit, at some point in the future. We will be better prepared than ever. This wil be true for a long while. So I think we should make (reasonable) haste, but nothing is lost yet. In the long run, we’re still growing.
This place bans you for “not being nice”, which is an arbitrary metric that changes from mod to mod and let’s all be honest, being nice is exhausting.
Lemmy is many places (individual instances with individual moderation policies). If it’s important to you, you can find a server which matches your expectations, or host your own.
Right, thanks for the corrections.
In case of GAN, it’s stupidly simple why AI detection does not take off. It can only be half a cycle ahead (or behind), at any time.
Better AI detectors train better AI generators. So while technically for a brief moment in time the advantage exists, the gap is immediately closed again by the other side; they train in tandem.
This does not tell us anything about non-GAN though, I think. And most AI is not GAN, right?
As with other AI-enhanced jobs, that probably still means less jobs in the long run.
Now one artist can make more art in the same time, or produce different styles which previously had required different artists.
And this is why AI detector software is probably impossible.
What exactly is “this”?
Just about everything we make computers do is something we’re also capable of; slower, yes, and probably less accurately or with some other downside, but we can do it. We at least know how.
There are things computers can do better than humans, like memorizing, or precision (also both combined). For all the rest, while I agree in theory we could be on par, in practice it matters a lot that things happen in reality. There often is only a finite window to analyze and react and if you’re slower, it’s as good as if you knew nothing. Being good / being able to do something often means doing it in time.
We can’t program software or train neutral networks to do something that we have no idea how to do.
Machine learning does that. We don’t know how all these layers and neurons work, we could not build the network from scratch. We cannot engineer/build/create the correct weights, but we can approach them in training.
Also look at Generative Adversarial Networks (GANs). The adversarial part is literally to train a network to detect bad AI generated output, and tweak the generative part based on that error to produce better output, rinse and repeat. Note this by definition includes a (specific) AI detector software, it requires it to work.
Right? A self-assessed skill which is never tested is a funny thing anyways. It boils down to “I believe I’m good at it because I believe my belief is correct”. Which in itself is shady, but then there are also incentives that people rather believe to be good, and those who don’t probably rather don’t speak up that much. Personally, I believe people lack the competence to make statements like these with any significant meaning.
“Monad” is a shorter term though. “Structured data type” reads almost as bulky as “Curve of constant normal intersection points”.
That was an unexpected dark turn. Glad you live to tell their story!