Also, there’s the cost and community aspect of games. For the price of a movie ticket and popcorn, I can buy a game that I can play with friends for easily dozens of hours instead of us silently sitting next to each other for an hour or two.

With the increasing death of third places and the increasing cost of existing outside, video games have become their own sort of third place for people to get together and just hang out.

On the one hand, yes, and Fandom is a blight on the internet.

On the other hand, AI like ChatGPT are wrong some 53% of the time. The fact that this is another “use nontoxic glue to keep your cheese from falling off of pizza” situation doesn’t mean that Google isn’t equally culpable for doing nothing to prevent these sorts of occurrences even when the sources are right (AI is as likely to make things up that aren’t even in its cited sources as it is to actually give you info from them).

There’s a train bridge like that in my hometown, but it’s directly over the base of a fairly steep hill. Pretty much anything bigger than a work van is likely to hit it, and I’ve seen a couple of box trucks with the top 6 inches or so of their roof peeled back like a half-open can of sardines.

Like a record, baby.

There’s definitely studies on it. I don’t know how they measure them, but it’s all about the number and type of cones in your eyes because there are a few different types that see different colors. This is why tigers are orange - because their prey lack the cones that see red, so the tigers look like the rest of the background foliage.

I’ve heard that women have more cones in their eyes as well, which leads to a more nuanced sense of differentiation between colors.

nice shoe laces

Any interest in anything CAD related? Generally it’s engineering/mechanical focused, but I imagine IT knowledge would be very useful (I know Gcode is useful for 3d printing, at least).

Another Millennial here, so take that how you will, but I agree. I think that Gen Z is very tech literate, but only in specific areas that may not translate to other areas of competency that are what we think of when we say “tech savvy” - especially when you start talking about job skills.

I think Boomers especially see anybody who can work a smartphone as some sort of computer wizard, while the truth is that Gen Z grew up with it and were immersed in the tech, so of course they’re good with it. What they didn’t grow up with was having to type on a physical keyboard and monkey around with the finer points of how a computer works just to get it to do the thing, so of course they’re not as skilled at it.

Me, making a donut: “Honey? Where’d you put my UV unwrapper?”

I found a couple of interesting graphs:

I dont really like how this first one divided their different groups (there’s probably a fairly major difference between the lower end of “middle class” and the top which brings up their percentage) and the way percentages work really skews the scale, but it does paint a similar picture. This second one is the more interesting, I think, because it shows that income inequality is pretty similar across many countries - before taxes. Taxes seem to be the big equalizer in other countries, with France going from slightly worse than the US before taxes to roughly two times closer to “perfect equality,” according to the metric they used, which puts it nearly on par with Sweden, who is miles ahead of every other country before taxes. This alone doesn’t say anything about wealth inequality due to how the wealthy actually live and use their wealth, but it does paint a picture of how closing tax loopholes can work.

Because we’re talking pattern recognition levels of learning. At best, they’re the equivalent of parrots mimicking human speech. They take inputs and output data based on the statistical averages from their training sets - collaging pieces of their training into what they think is the right answer. And I use the word think here loosely, as this is the exact same process that the Gaussian blur tool in Photoshop uses.

This matters in the context of the fact that these companies are trying to profit off of the output of these programs. If somebody with an eidetic memory is trying to sell pieces of works that they’ve consumed as their own - or even somebody copy-pasting bits from Clif Notes - then they should get in trouble; the same as these companies.

Given A and B, we can understand C. But an LLM will only be able to give you AB, A(b), and B(a). And they’ve even been just spitting out A and B wholesale, proving that they retain their training data and will regurgitate the entirety of copyrighted material.

Reminds me of when I read about a programmer getting turned down for a job because they didn’t have 5 years of experience with a language that they themselves had created 1 to 2 years prior.

The argument that these models learn in a way that’s similar to how humans do is absolutely false, and the idea that they discard their training data and produce new content is demonstrably incorrect. These models can and do regurgitate their training data, including copyrighted characters.

And these things don’t learn styles, techniques, or concepts. They effectively learn statistical averages and patterns and collage them together. I’ve gotten to the point where I can guess what model of image generator was used based on the same repeated mistakes that they make every time. Take a look at any generated image, and you won’t be able to identify where a light source is because the shadows come from all different directions. These things don’t understand the concept of a shadow or lighting, they just know that statistically lighter pixels are followed by darker pixels of the same hue and that some places have collections of lighter pixels. I recently heard about an ai that scientists had trained to identify pictures of wolves that was working with incredible accuracy. When they went in to figure out how it was identifying wolves from dogs like huskies so well, they found that it wasn’t even looking at the wolves at all. 100% of the images of wolves in its training data had snowy backgrounds, so it was simply searching for concentrations of white pixels (and therefore snow) in the image to determine whether or not a picture was of wolves or not.

The context that we’re talking about here isn’t somebody that you know personally and have permission from/are talking to mutual friends of. We’re talking about publicly announcing a stranger’s dead name to everybody who reads this post and the justification that it’s okay because they once had 15 minutes of internet fame from a video going viral before they transitioned. At best, it’s a paparazzi-esque invasion of privacy, and at worst, it’s straight up doxxing.

A. Hyperbole, look it up.

B. Why do you think it’s okay to dox people?

TIL the internet doesn’t understand hyperbole so long as it’s a trans person using it.

Did you miss the part about how my safety is dependent on going stealth? I moved somewhere where nobody knew me after transitioning for a reason. A stranger going around and telling random people my dead name would be like a stranger going around telling random people that a person is in witness protection and what their real name is. Again, your threat index isn’t universal.

The first rule of self-defense is that a battle not fought is a battle won. The second rule is if you have to hurt a man, you hurt him so bad that you need never fear his vengeance. If he can stand up, he can come right back at you.

Except that’s not at all what’s happening here. We’re not talking about somebody we know personally with their permission or anything, we’re talking about an actress who got into pornography after having an emotional video go viral many years ago. Her dead name has nothing to do with that, and if you had even left out the fact that she’s trans, most people probably could’ve figured it out if they even bothered to go check out the original video. Abd if they didn’t? It wouldn’t make a difference in their knowledge of the subject. They’d still know that a woman who had an emotional video go viral years ago later became a porn actress. All her dead name adds to this is a possibly paparazzi style invasion of her privacy.

Does it add any useful context, though? I don’t know either name but I do remember the “Leave Britney alone” video being a thing (and the fact that the person in the video turned out to be right all along when the truth about Britney’s situation came out years later), so the added context that she’s trans and what her dead name was is meaningless to me other than to say, “She used to be a man. She’s a woman now, but she was a man before. Did you know that? That she was once a man? Because she was. Here’s what her name was.”

As a trans woman, whose safety is so dependent on being able to go stealth in society, if I found out people were going around talking about me like this, I’d take a rusty icepick and make sure that they never think in words ever again. Lack of malicious intent doesn’t mean that no harm was caused. Your threat index is not universal.

This could have very easily been left at “Trans woman X got into porn after her viral video Y” and there would be all the context needed to figure out who they were and what video they were in without using their dead name. Hell, you probably wouldn’t even have to point out that she’s trans for people to figure it out. Cis people treat the privacy of trans people the same way that the paparazzi treats the privacy of celebrities.