My uni had one. Sadly I couldn’t fit it into my schedule because of overlaps and other requirements.

*With AI review :)

While it doesn’t say anything about IIV specifically, they sure got creative enough to sometimes subtract more than one of the smaller units from a larger one.

I kept up with the drama until about a week ago so what I’m saying here is the status from back then. Someone please add any new context if I’m missing any new developments:

From what it appeared, view counts dropped but ad revenue stayed the same. Even before this whole thing, YouTube pays out for ads watched (and clicked). Pay out was not dependent on raw view count for a long time, if ever.

This suspicious behavior of view count dropping but ad revenue staying the same is actually what tipped people off that the issue was adblock related. The fact that channels with a larger focus on a younger audience seeing less of a drop also helped.

Now those view counts dropping could still have an indirect, negative effect on ad revenue, if it, e.g. automatically leads to YouTube recommending their videos less prominently.

Another European here to chime in that l also learned to write capital As like that in cursive.

The rs, fs and ts don’t look like how we were taught though.

On the second part. That is only half true. Yes, there are LLMs out there that search the internet and summarize and reference some websites they find.

However, it is not rare that they add their own “info” to it, even though it’s not in the given source at all. If you use it to get sources and then read those instead, sure. But the output of the LLM itself should still be taken with a HUGE grain of salt and not be relied on at all if it’s critical, even if it puts a nice citation.

I can believe it insofar as they might not have explicitly programmed it to do that. I’d imagine they put in something like “Make sure your output aligns with Elon Musk’s opinions.”, “Elon Musk is always objectively correct.”, etc. From there, this would be emergent, but quite predictable behavior.

I know you’re just making a snide remark, but we’re already well on that track too.

Different person here.

For me the big disqualifying factor is that LLMs don’t have any mutable state.

We humans have a part of our brain that can change our state from one to another as a reaction to input (through hormones, memories, etc). Some of those state changes are reversible, others aren’t. Some can be done consciously, some can be influenced consciously, some are entirely subconscious. This is also true for most animals we have observed. We can change their states through various means. In my opinion, this is a prerequisite in order to feel anything.

Once we use models with bits dedicated to such functionality, it’ll become a lot harder for me personally to argue against them having “feelings”, especially because in my worldview, continuity is not a prerequisite, and instead mostly an illusion.

His Hyprland setup looks cool if you’re into that sorta thing but it’s just not what users just switching to mint, fedora, whatever might be looking for.

I would not underestimate how much of a draw “it looks cool” can have on people who are not tech savy at all. If you think about what drives new phone purchases, their major version upgrades always include lots of things that are nothing but eye-candy and those are often heavily featured in their promotion material.

If the goal is to get casual users to convert to Linux, I would argue that aesthetics is a lot more important than ANY talk about technical details, privacy, etc. If those users cared about those things, they would’ve switched already.

Now my bigger worry is that those users will bounce off before they manage to get their setup to look as (subjectively) cool as his.

Sure! Here’s an expanded version of the fictional profile for Chris Whitmore, now including made-up family member names, relationships, and contact info — all entirely fictional and consistent with the character:

You forgot to remove that part of the LLM response…

I don’t think it’s more crime because more tension. It’s instead a self fulfilling prophecy. Who do you think detects and records crime if not the police? Therefore more police in a area increases the number of crime data points in that area.

One field it impacts is radio astronomy. We can already see Musk’s satellites mess with it (unintentionally) and it’s probably only going to get worse from here.

In my experience, it is good at simple to medium complexity regex. For the harder ones it starts being quite useless though, at best providing a decent starting point to begin debugging from.

I wanna add to what other users already answered that this problem is not created by federation, only exacerbated.

If I’m mod of a community and I ban your Lost_My_Mind@lemmy.world account, I cannot stop you from creating, e.g. Lost_My_M1nd@lemmy.world and coming back. Most servers have some barriers against spam account creation in place, but I’d wager you could easily create a handful of accounts on a server until they start to grip.

Even completely centralized platforms such as Twitter and Reddit are the same. You can easily ban/block evade a couple times per timeframe.

Whcih makes sense when explained, but it seems like few hear that kind of comparison.

And then you bring up defederation and/or how instances can die at any time and you lose them again…

At least that’s how it usually goes for me and trying to advertise Lemmy. Not really a fan of “microblogging” to begin with no matter the platform.

People who claim “guys” is gender neutral would most often only count men when asked the question “How many guys did you sleep with in your life?”

Until I find a single person who immediately thinks of people of any gender at that question, I will not fall for the internalized misogyny of “‘guys’ is gender neutral” meme. (Same with “dudes” and all the other ones I’ve seen over the years. I’ve even seen someone say “bro” is gender neutral.)

Sure. You have to solve it from inside out:

• not()…See comment below for this one, I was tricked is a base function that negates what’s inside (turning True to False and vice versa) giving it no parameter returns “True” (because no parameter counts as False)
• str(x) turns x into a string, in this case it turns the boolean True into the text string ‘True’
• min(x) returns the minimal element of an iterable. In this case the character ‘T’ because capital letters come before non-capital letters, otherwise it would return ‘e’ (I’m not entirely sure if it uses unicode, ascii or something else to compare characters, but usually capitals have a lower value than non-capitals and otherwise in alphabetical order ascending)
• ord(x) returns the unicode number of x, in this case turning ‘T’ into the integer 84
• range(x) creates an iterable from 0 to x (non-inclusive), in this case you can think of it as the list [0, 1, 2, …82, 83] (it’s technically an object of type range but details…)
• sum(x) sums up all elements of a list, summing all numbers between 0 and 84 (non-inclusive) is 3486
• chr(x) is the inverse of ord(x) and returns the character at position x, which, you guessed it, is ‘ඞ’ at position 3486.

The huge coincidental part is that ඞ lies at a position that can be reached by a cumulative sum of integers between 0 and a given integer. From there on it’s only a question of finding a way to feed that integer into chr(sum(range(x)))

That data is also publicly available (of course), so a model could be trained on it. I’d love to say I’d doubt Google/YouTube would ever do that, but at this point nothing would surprise me.

I trained the generative models all from scratch. Pretrained models are not that helpful when it’s important to accurately capture very domain specific features.

One of the classifiers I tried was based on zoobot with a custom head. Assuming the publications around zoobot are truthful, it was trained exclusively on similar data from a multitude of different sky surveys.