It probably has to do with strict character limits and the habit spreading. Twitter is only, what, 156 characters? I know text messages used to be something similar, and early on, they cost around 3 cents a letter and you had to hit the numbers multiple times to cycle through to the letter or punctuation that you wanted. It’s where stuff like l33t speak came from, at least.

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).

But according to the story, he was buying at full price. No bulk discount. Jim was demanding more than his regular price. And, depending on when in the day he showed up, the price that Jim demanded fluctuated.

There’s gotta be more to this.

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.

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).

It’s not about what humans “like,” it’s about the human bodies’ internal operating temperature and using that as a reference point, the same way that Celsius is about the states of matter of water . Fahrenheit is useful in medicine for that reason, while Celsius is useful anytime a comparison to water is helpful, and beyond that, it’s really just whatever you grew up with. Using a system based on what water “likes” is equally as useless unless you grew up using it as your reference point for temperature in your daily life. Neither 75 Fahrenheit or 23.8889 Celsius tell me whether or not I’m going to need a jacket today unless I’ve already experienced said temperature and use that scale in my daily life.

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.

And similarly, Fahrenheit seems to be tied to the internal temperature of the human body, with 100 degrees being the maximum that the average person can handle before their organs start to be damaged.

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.

I think it also had to do with the fact that they’re bottom feeders, as most fish spoil fairly quickly without proper care (though some are definitely worse than others - I think shark starts going bad literally as soon as the shark dies).

Like your second point, many bottom feeders are more likely to have parasites and, therefore, probably built up a reputation as being unfit for eating (though lobsters don’t have any parasites that I’m aware of).

This is literally how the furries got started. Won’t be long before they commission a $5,000 cosplay suit of their ice elemental.

I think (I hope) by overnight revolution, they mean the tipping point from civil unrest into actual change. It took a decade of protesting for Civil Rights to get popular support, but the law was drafted, written, and signed in less than a week due to the destruction wrought across the country after MLK was assassinated.

I don’t disagree, but I think the attitude comes from exhaustion at the Democrats spending 50 years meeting Republicans in the middle and telling more left leaning groups that their desires aren’t as important or that they’re at fault for Democrats losing because they scared off some mythical right leaning centrist who would have otherwise voted for the Democrats.

Plus, I’m not convinced that a large part of the not voting bloc that you hear online isn’t actually just a disenfranchisement campaign.

I think this misses 2 possibilities. The first one being the unlikely scenario where a species’ space travel program outpaces the ecological collapse of their planet, necessitating a jump into an interplanetary civilization, and the second being the rarity of certain materials required for a technological civilization to continue to exist. The Rare Earth metals are so named because of their rarity on the planet, with most deposits being the result of meteorite impacts, and even things like iron only exist in finite quanities. There’s been talk for years now of capturing asteroids in orbit around the planet for mining purposes and atmospheric “scooping” to harvest gases from the gravity wells of other planets for gases such as hydrogen.

Unless a civilization achieves 100% efficiency in a closed cycle of material use, they will need to look to the stars by necessity eventually.