Nanashi Jones: Personally Anyone

Because the moths themselves don’t eat and only live long enough to mate and then starve to death, the entire culture is made up of children and adolescents. The older children raise the younger ones, with families being made up of hatchmates from different years.

Because molts and eventual transformation into a short lived adult happen on a set schedule, families have a cycle— when your oldest set of siblings cocoon to become adults, you wait at the mating grounds and try to adopt their newborns after they pass. If that fails, you take any ‘orphans’ you can find.

Because death and birth are nearly simultaneous, they have a religion based around reincarnation, and infants with markings similar to a parent are often given their name. Claiming the offspring of a beloved family member is vitally important, because you want to be able to protect their soul and keep them close.

Because it’s hard to track the offspring of your male family members, there are sometimes major fights when a family sees an infant with familiar markings in another family’s clutch.

I keep forgetting to post these here

I gave myself a soft project of ‘Me as X Type Gym Leader’ whenever I need a break from my comic and want to draw for fun. Just to keep my design muscles limber using something familiar but still creative. [and I know the sinestea line isn’t fairy but the shiny tea set fit my color theme and I thought it was a cute easter egg]

“You mean you locked up a pack of curious, highly competitive persistence predators with NO enrichment in the enclosure? You FOOLS! If you had bothered to throw a basketball or half a box of Legos in there, KE-X9 would still be alive!

Like they’re totally unable to figure out what’s happening because the cameras keep going out, but every night things get moved, or stolen, exhibits are disappearing, WHAT IS GOING ON, they’ve moved facilities twice and it’s still happening, are they haunted, are the ancestors angry, WHAT IS HAPPENING!?

And then a weary humanologist is all ‘… your humans are getting out’. 

“That is impossible.” 

“They’re getting out.” 

“That enclosure is COMPLETELY SECURE.” 

“And yet somehow they’re getting out.” 

“THE HUMANS ARE NOT GETTING OUT.” 

“Oh yeah? I bet you twenty glarks they’re getting out. Stay after closing time with me and I’ll show you.” 

*next day*

“… the humans were getting out.” 

“… why did they keep going back in, then?!”

1 - at our own zoos the MOST notorious jail breakers are the orangutans, who exploit all manner of methods, including literal lock picking. One orangutan, Ken Allen escaped several times WHILE THE ZOO WAS OPEN TO THE PUBLIC without getting caught by watching Zoo employees, even when they tried to disguise themselves as tourists to catch him at it. While he was being “secretly” surveilled, he managed to escape AND show the other orangutans how to escape. They finally found out he was doing some thought-to-be-impossible rock climbing to escape. To fix it, they brought in a team of human rock-climbers to locate all possible methods of climbing out. So. Humans would absolutely be the worst to try to keep contained. Like, “escape rooms” are currently seen as a fun date idea. I’m sayin.

2 - animals that escape most often return to their own enclosure (after all that’s where their beds and dinners are, and if the zoo is any good it is the place best suited to their species-specific needs for miles and miles) after they have had sufficient excitement. Ken Allen the orangutan would escape and wander around the zoo looking at the animals like he’d bought a ticket. So if the keepers were nice, and formed a bond, and the set up was comfy, once the human knew they could get out if they really wanted, they’d probably go back, depending on how uncomfortable/dangerous the alien environment was.

“Rescued” humans who weren’t thriving in the wild. (Aka dire medical debt.)

Made sure to take an entire social troop instead of lone individuals. (Your closest friends/family members are there.)

Offered VERY good care and enrichment.

2cool4skool

The finished in the nick of time to print in a compilation I'll be selling at Anthrocon 2026! (Say hi if you're around Saturday or Sunday!)

CeCe Rogers on Facebook writes: "Two Black Tennessee lawmakers were physically escorted out of chambers this week while Republicans quietly held a hearing to approve gerrymandered maps that would eliminate the state's only majority-Black congressional district.

No referendum. No special election. No public vote.

Because they know what happens when voters actually get a say — just look at Virginia, where the people spoke so loudly that Republicans had to drag the courts in to override them.

This isn't new. During Reconstruction, Black Americans held more congressional seats than at any point in the prior 90 years of American history. And white supremacists spent the next several decades tearing that down, through gerrymandering, poll taxes, and voter intimidation.

150 years later, the same tools. Different suits.

The audacity of escorting Black lawmakers out of their own chambers while dismantling Black political representation, and then telling us the courts aren't political, is breathtaking. These are the same courts they're counting on to make it stick.

Not sometimes. Not until the next update. Always. They proved it with math.

Even with perfect training data and unlimited computing power, AI models will still confidently tell you things that are completely false. This isn't a bug they're working on. It's baked into how these systems work at a fundamental level.

And their own numbers are brutal. OpenAI's o1 reasoning model hallucinates 16% of the time. Their newer o3 model? 33%. Their newest o4-mini? 48%. Nearly half of what their most recent model tells you could be fabricated. The "smarter" models are actually getting worse at telling the truth.

Here's why it can't be fixed. Language models work by predicting the next word based on probability. When they hit something uncertain, they don't pause. They don't flag it. They guess. And they guess with complete confidence, because that's exactly what they were trained to do.

The researchers looked at the 10 biggest AI benchmarks used to measure how good these models are. 9 out of 10 give the same score for saying "I don't know" as for giving a completely wrong answer: zero points. The entire testing system literally punishes honesty and rewards guessing.

So the AI learned the optimal strategy: always guess. Never admit uncertainty. Sound confident even when you're making it up.

OpenAI's proposed fix? Have ChatGPT say "I don't know" when it's unsure. Their own math shows this would mean roughly 30% of your questions get no answer. Imagine asking ChatGPT something three times out of ten and getting "I'm not confident enough to respond." Users would leave overnight. So the fix exists, but it would kill the product.

This isn't just OpenAI's problem. DeepMind and Tsinghua University independently reached the same conclusion. Three of the world's top AI labs, working separately, all agree: this is permanent.

Spoiler:

it's that most wonderful time of the year again - time for a 2025 headline wrap-up!