#query plan analysis

[thedbahub]

Identifying Memory Grant Contributors in SQL Server Query Plans

Introduction When optimizing SQL Server performance, it’s crucial to understand how memory grants are allocated to query plan operators. Excessive memory grants can lead to inefficient resource utilization and impact overall system performance. In this article, we’ll explore practical T-SQL code examples and techniques to determine which operators are contributing the most to memory grants in…

[minxmut-cafe]

BEAR WITH ME ??

Pairing : Bear hybrid Namjoon x Ferret hybrid reader

Word count : 10k words.

Authors note : HAHDBDHD HELLO YOU GUYS!! I'm really excited to post this because I had ALOT of fun writing this. I love love LOVED the whole dynamic as well and tbf it's minor self insert because..I too can be a menace. Like I'm not THAT much of a menace but I've had enough complaints to know I am one lololol. I think I'm gonna post more stuff about these two. I've already planned a few more things and some other scenarios and stuff. Like I said I REALLY enjoyed the whole dynamic and i think you guys would as well. ALSO I've had to make 2 parts of this because I keep hitting the word count on the damn post. BE SURE TO LIKE BOTH PARTS And if you have any requests or query my requests and asks are always open. <3

Warning : Smut, Vaginal sex, oral sex (M & F receiving), hybrid sex, mentions of death, mention of heat, feral Namjoon, size kink, spanking, mating press, mentions of various sex positions, reader being a menace, Namjoons a gentle giant, rough sex, cunnilingus, idiots in love, reader is immature, Namjoon is suffering, HUGE size difference (Imagine gyomei and shinobu). Masturbation, Namjoons a boob guy. Titty analysis :)

Synopsis :

"Namjoon spots a Tiny ferret hybrid getting pushed around by a bunch of hyena hybrids and decides to intervene. Little did he know that would lead to a series of interesting, traumatising and hilarious memories, some of which he's convinced were attempted murder attempts."

The quad was bustling. Students milled about, chatting, heading to class, or loitering in the late afternoon sun. It was a typical day—except for the growing commotion near the campus fountain.

A group of hyena hybrids had circled someone.

Laughter, sharp and jeering, cut through the air.

And in the middle of it all stood her—half their size, shoulders squared, and pissed.

“Come on, sweetheart,” one of the hyenas drawled, tail flicking behind him. “We’re just playing.”

Another snickered. “Yeah, don’t be so...uptight.”

She scowled, baring her small, but very sharp teeth. “Say that again.”

“Ooooh.” They mocked her. “She’s got bite.”

A growl rumbled in her throat, but before she could launch herself at them—

A shadow loomed.

Everything stopped.

The hyenas stiffened, their ears flattening as a new presence entered the circle.

He was massive.

Towering over them like a walking monolith, broad shoulders casting a dark silhouette against the sun. His round glasses reflected the light, but his expression was unreadable.

A grizzly bear hybrid.

And not just any bear—one that could easily break them in half if he wanted.

The air shifted.

The hyenas hesitated—then, in a blur of nervous laughter, backed off. “Relax, man. No need to get involved.”

And just like that, they scurried away.

Silence.

Then—

She turned, glaring up at her so-called savior.

“What, you wanna fight too?!”

Namjoon’s eyes widened.

“EH?—NO—WAIT—” He lifted his hands, panicked. “I wasn’t—I didn’t—”

She squinted. Suspicious. “Then what do you want?”

“I just—” He struggled, fumbling for words. “I saw you getting pushed around and thought—”

“I had it handled,” she snapped.

Namjoon blinked.

Then, despite himself, a tiny smile pulled at his lips. “Yeah… I think you did.”

And that was how you met Kim Namjoon.

If anyone on campus had to describe their relationship, they wouldn’t know what to say.

It started with the hyena incident—which, in your opinion, wasn’t even that big of a deal. You had them handled. But then Namjoon had to come in like some big, overgrown hero, and suddenly, y'all were seeing each other everywhere.

Same lecture hall.

Same group projects.

Same spot at the café.

And for some stupid reason, you both always ended up together.

Namjoon, to his credit, was a bean. A giant, shy, soft-spoken bean who somehow made people nervous just by existing. He was taller than most— 7'3 to be exact, broader than all, and had the gentlest voice she’d ever heard. He was polite to everyone, rarely raised his voice, and for some reason, people still thought he was scary.

You , however?

You were half his size, twice the chaos, and nice to exactly one person.

Which meant one thing—

Once you were close enough, you never left him alone.

“Namjoon,” you huffed one afternoon, climbing onto him like a tree.

He blinked, startled, as you hoisted herself onto his back. “Uh—what—?”

“The quad’s packed. Carry me.”

He hesitated. “You have legs?”

“And you have muscles,” you shot back, wrapping her arms around his broad-ass shoulders. “I don’t see the problem.”

Namjoon sighed but adjusted his grip and carried you anyway.

Your classmates barely reacted. At this point, this was normal.

The first time you saw him shirtless, it was completely by accident.

You’d been raiding his fridge, sitting on his counter, happily munching away on his leftover dumplings when he walked in—

Fresh out of the shower.

Shirtless.

With his glasses still on.

Water dripped from his messy curls, his golden skin still damp from the steam. And, most importantly—

His chest.

His pecs.

You froze mid-bite.

Namjoon stopped in his tracks.

Silence.

Then—

“Oh,” you said casually, chewing. “Need help holding those up?”

Namjoon choked.

His entire face turned red. “W-What?!”

You grinned. “Y’know.” you gestured lazily. “Those badonks or if you want the more sophisticated name boobies.”

Namjoon spluttered, immediately grabbing the nearest hoodie and shoving it over his head. “I—THAT’S NOT—”

Too late.

You had already decided.

He was your new favorite toy.

You also had a bad habit of picking arguments you couldn’t win. It was in your nature as a ferret hybrid—small, scrappy, and absolutely lacking in self-preservation.

Namjoon, unfortunately, had a bad habit of ending those arguments in the most unfair way possible.

Lifting you.

It didn’t matter if you were mid-rant, arms flailing dramatically—he’d simply sigh, scoop you up with one arm, and hold you at arm’s length like a misbehaving kitten.

“PUT ME DOWN, YOU TREE!”

“Not until you calm down,” he’d say, voice as gentle as ever.

“I’LL BITE YOU.”

“You always say that, but you never do.”

You bared your teeth. “This time I mean it.”

He just sighed and adjusted his grip, holding you higher like you were some kind of unruly toddler.

It didn’t help that you also had a habit of climbing him in crowded spaces.

“Personal space,” Namjoon warned as you latched onto him like a koala in the cafeteria.

“No.”

“People are staring.”

“Let them. I’m comfy.”

“You’re on my back.”

“Again, comfy.” you huff.

He eventually just gave up and started carrying you without complaint.

Winter was the worst. You hated the cold.

Namjoon, however, was a walking furnace.

You quickly realized that hugging him was like curling up next to a heated blanket, and you took full advantage.

It started subtly—leaning against him during study sessions, pressing up to his side when you were sitting together. Then it escalated to full-on bear hugs at every opportunity.

At first, Namjoon tried to act like he wasn’t affected.

But then came the day you simply plopped onto his lap in the library.

He tensed, ears turning red. “What are you doing?”

“Getting warm,” you said, making yourself comfortable.

“I—you—you can’t just—”

“You’re literally a bear. This is your purpose.”

He spluttered but ultimately let you be. And from that day on, your lap privileges were unofficially granted.

You were a menace. He had accepted that. Truly. But there were moments that made him re-think everything.

Namjoon is trying to have a serious conversation with a professor.

You're behind the professor, making the most outrageous hand gestures.

At first, it’s subtle. A suggestive eyebrow wiggle. A tiny lip bite.

Namjoon notices. Regrets noticing immediately.

Then you gets bolder. You start doing obscene gestures.

Namjoon chokes mid-sentence.

Professor, slightly confused "Are you... alright, Namjoon?"

Namjoon, stiff as a board "Yes. Absolutely. Fine."

He tries to ignore you , but you keep going.

Pretending to sensually lick your fingers. Mimicking very inappropriate things.

Namjoon, mentally thought "Kill me. Just kill me now."

He knows if he calls you out, he will be the one looking guilty.

The second the professor leaves, he just picks you up and carries you away.

Namjoon, exasperated: "What is WRONG with you??"

You on the other hand? wheezing from laughter

"You should’ve seen your face—"

Namjoon, mutters under his breath "I swear I’m gonna kiss you just to shut you up."

And that makes you go quiet. (For once.)

At first, you didn’t notice anything was off.

Study sessions at Namjoon’s place had always been your favorite—his apartment was warm, cozy, and filled with books. He made the best tea, had the fluffiest blankets, and, most importantly, he didn’t mind when you sprawled out on his couch like you owned the place.

But then something changed.

Namjoon got sleepy. Not just normal sleepy—bear hybrid in hibernation mode sleepy.

At first, it was small things. He’d yawn more, stretch like a cat mid-sentence, blink at you drowsily while you ranted about your latest shenanigans. Then it escalated—he’d start dozing off while sitting up, nodding off mid-study session, even mumbling nonsense in his sleep.

And it was driving you insane.

“Namjoon,” you poked his cheek. “Focus.”

He blinked at you slowly. “I am.”

“You’re literally drooling on your book.”

He made a vague grumbling noise and turned his head, pressing his face into the couch cushion.

“Hey!” You shook him. “No sleeping, bear boy.”

“M’not sleeping,” he slurred. “M’listening.”

“You’re hibernating. You cannot just hibernate in the middle of exam season.”

He groaned, dragging a blanket over his head. “Just a little nap.”

You huffed. This wasn’t fair. You were used to a grumpy, flustered Namjoon, a Namjoon who sighed heavily whenever you did something unhinged. But now? Now he was too sleepy to react to your nonsense.

Boring.

So, naturally, you decided to fix it.

You waited until one particularly bad day when Namjoon was practically melting into his couch, wrapped in a cocoon of blankets. His glasses were slipping down his nose, his book long forgotten as he blinked sleepily at the wall.

That’s when you struck.

You climbed onto the couch, grabbed his shoulders, and shook him.

“Wake up, you oversized teddy bear!”

Big mistake.

Before you could react, Namjoon made a low, grumbly noise and grabbed you.

“What the—”

You barely had time to squeak before you were yanked into his arms and smushed against his chest.

Panic set in.

“Namjoon.” You wiggled. His grip tightened.

Oh. Oh no.

You were trapped.

The weight of a freaking bear hybrid pressed down on you, limbs wrapped securely around your body. You struggled, but it was like being stuck under a weighted blanket from hell. Warm, cozy, and completely inescapable.

You tried logic. “Namjoon, you can’t just—”

A deep rumble cut you off. Not quite a growl. More like… a purr.

A sleepy, contented bear purr.

Your brain short-circuited. “Did you just purr at me?”

No response. Just another deep, satisfied hum as he nuzzled into your hair.

Oh. You were doomed.

For hours, you were trapped, helpless as Namjoon slept soundly, using you as his personal body pillow. Every attempt to escape was met with an unconscious squeeze, like a giant, affectionate bear reminding you no, you stay here now.

By the time he finally woke up, stretching with a yawn and blinking at you like he was surprised to find you in his arms, you were fuming.

“You absolute menace,” you growled. “I’ve been stuck here for hours.”

Namjoon tilted his head, still half-asleep. Then, with the softest, sleepiest smile, showing off his stupid dimples, he mumbled, “You’re warm.”

Your brain broke.

You didn’t know whether to slap him or melt into a puddle.

So, naturally, you did the only thing that made sense.

You bit him.

He didn’t even react. Too sleepy.

It was official. Namjoon’s hibernation phase was ruining your life.

He had gotten even lazier—falling asleep at random, mumbling nonsense, refusing to wake up no matter how much you poked, prodded, or even bit him. At this point, you were desperate.

So, one fateful morning, you took drastic measures.

You climbed onto his bed, glaring down at the oversized bear hybrid sprawled out like a crime scene. He was dead asleep, mouth slightly open, breathing slow and deep. You poked his cheek. No response.

Fine.

You swung one leg over him and straddled his waist, hands bracing against his broad chest. Then, with all your ferret hybrid determination, you bounced.

“WAKE UP, YOU LAZY—”

You didn’t get to finish.

Because in his drowsy, half-asleep state, Namjoon groaned—deep, low, and utterly sinful.

Then—his hands grabbed your hips.

You froze.

Before you could process it, his fingers tightened, large and warm as he guided you down against him.

Your breath hitched.

Something… hard pressed up between your legs. Not fully hard, but enough.

Then Namjoon—still completely asleep—let out a soft, breathy moan and rolled his hips up into yours.

Your soul left your body.

For a solid three seconds, you sat there, straddling a very large, very strong, very hard bear hybrid who was grinding against you in his sleep.

Then you did the only thing that made sense.

You screamed.

“YOU PERVERTED BEAR!”

With a panicked shriek, you slapped his chest so hard his pec jiggled.

Namjoon’s eyes snapped open.

He blinked at you, still groggy. Then he frowned.

Then he looked down.

The moment realization hit, his entire face exploded into red.

And then—he scrambled.

With an alarmed gasp, Namjoon flung himself back so violently that he nearly fell off the bed. He yanked the blanket up to his chest like a scandalized Victorian lady, clutching it as if it could protect his virtue.

“I—YOU—THIS—” He was stammering, eyes wide, scandalized beyond belief.

You, still red as hell, pointed a shaking finger at him. “WHAT THE HELL WAS THAT?!”

“I DON’T KNOW!” He practically wailed.

“You grabbed me!”

“I WAS ASLEEP!”

“You moaned!”

Namjoon made a horrified noise and buried his face in his hands.

“I’M GOING TO PASS AWAY,” he mumbled, voice muffled with shame. “RIGHT HERE. RIGHT NOW.”

You were still flustered as hell, but seeing this six-foot-plus grizzly bear hybrid cowering behind a blanket like you had violated his innocence was too much.

Slowly, a grin curled onto your lips.

“Ohhh,” you drawled. “I see how it is.”

Namjoon peeked up at you, suspicious. “Don’t.”

“You were enjoying it, huh?”

His ears turned red. “STOP.”

“Does sleepy Namjoon have naughty dreams?”

“PLEASE.”

You smirked, leaning in. “Wanna finish what you started, perverted bear?”

Namjoon squeaked.

A full-grown grizzly bear hybrid. A literal terrifying predator.

And you made him squeak.

You were never letting him live this down.

Namjoon knew he was in for a bad day the moment you sat down across from him at lunch.

You were grinning.

Not just any grin—your shit-eating, up-to-no-good, gremlin grin.

Immediately, he sighed. “No.”

You blinked innocently. “I haven’t said anything yet.”

“I can feel the trouble radiating off of you.”

You wiggled your eyebrows. “So, speaking of yesterday—”

Namjoon groaned. “No.”

“But I was just curious—”

“No.”

You leaned in, propping your chin on your hands. “Okay, but seriously. How big is your dick?”

Namjoon choked on his food.

“What the fuck?!” he coughed.

“Pure curiosity.” You smiled sweetly. “Scientific curiosity, if you will.”

He glared at you, ears burning. “I will snap you in half, you lanky menace.”

“Oh?” You cocked your head. “Because from what I felt yesterday—”

Namjoon dropped his head onto the table with a thud.

“I hate you,” he muttered into his arms.

You giggled, delighted, poking his bicep. “C’mon, you must have a guess. Seven? Eight? Should I be worried for my pelvic bone?”

He let out the most miserable sigh, running a hand down his face. “You do realize I’m a bear hybrid, right?”

“Exactly why I’m asking.” You smirked. “I am a scholar, you know.”

Namjoon groaned again, exhausted, leaning back in his chair. “If you mention my dick one more time—”

You blinked expectantly.

He stared at you, looking so done.

Then, in a moment of pure exasperation, he sighed and muttered, “I’ll bend you over and show you exactly how big it is.”

Silence.

Namjoon froze.

You froze.

He blinked. Then groaned. Loudly.

“I cannot believe I just said that,” he muttered, rubbing his temples.

You were still in shock. Then, slowly, the widest, most devious grin spread across your face.

“Oh?”

“Don’t.”

“Ohhhh?”

Namjoon buried his face in his hands. “I need to leave. I need to walk into the ocean.”

You giggled, absolutely delighted, patting his arm. “Don’t worry, Joon. I promise I won’t tease you anymore.”

Namjoon peeked at you warily. “Do you actually promise?”

You smiled sweetly. “Absolutely not.”

He groaned, glaring at his food like it had personally betrayed him.

You had never had this much fun in your life.

Namjoon had accepted his fate.

You were tiny. You were chaotic. You were a menace to society.

And, apparently, you were also his personal weighted blanket.

Because somewhere along the way, you had decided his lap was your permanent seat.

It wasn’t even something you seemed to think about anymore—you’d just waltz over, plop down onto his thighs, and continue on with your life as if you weren’t making his brain short-circuit every damn time.

And the worst part? Namjoon let you.

Like an idiot.

Right now, you were curled up against him, legs folded, tablet in hand as you scribbled notes. Namjoon was trying to focus on his computer, but it was hard when you kept fidgeting—shifting, adjusting, wiggling against him like you were trying to test the limits of his self-control.

You had no idea what you were doing to him.

Absolutely none.

It didn’t help that you looked unfairly adorable—pouting slightly as you concentrated, lips pursed, occasionally kicking your feet.

Fuck.

His bear instincts were so confused. Because on one hand, he knew you were just being your usual ferret-self, but on the other, something in him kept whispering, Mate?

It didn’t help that sometimes—like right now—you’d look up at him suddenly, big eyes blinking, only to reach up and poke his cheek.

“Joonbug.”

Namjoon swallowed thickly. “Yeah?”

You grinned, leaning in slightly. “Your face is funny when you concentrate.”

He rolled his eyes, forcing himself to focus on his screen. “Thanks, I guess.”

But when he turned back, he realized—your face was so close. If he just—if he leaned in—

Namjoon immediately tensed and looked away.

Nope.

Absolutely not.

And the worst part?

You fell asleep there.

Like a goddamn purring cat.

One second you were awake, the next you were snuggled into his chest, soft little breaths tickling his pecs. Namjoon froze, entire body stiff.

He could feel your warmth.

The soft rise and fall of your chest.

The way your body just—just fit against his.

And then—the final straw.

You shifted slightly, and his gaze accidentally dropped to your shirt.

Or, more specifically, down your ridiculous little Henley.

Namjoon stared.

Not on purpose. Not really. It was just—he was a man. A man with eyes. And you were—

Oh.

He hadn’t really… evaluated before.

Nice.

Good shape.

One slightly bigger. Completely normal

And… a bit bigger than he anticipated.

Hm.

Namjoon blinked, mind blank for a moment. Then—

Wait.

WAIT.

His face exploded into red, eyes snapping forward like he had just witnessed a war crime.

What the fuck was wrong with him?!

He threw himself back into his work, typing aggressively, but it was too late.

Because now, against his will, his brain had a new intrusive thought:

I wonder how they’d feel in my hands?

Namjoon malfunctioned.

He needed to leave. He needed to die.

But mostly?

He needed to get you off his lap.

Before he lost his goddamn mind.

Namjoon refused to acknowledge what had just happened.

Refused.

You were asleep on his lap, blissfully unaware of his horrible, terrible, no-good intrusive thoughts. And yet, despite his best efforts to suppress the chaos in his brain, his traitorous bear instincts decided to betray him.

Thump. Thump. Thump.

His tail, the absolute bastard, started tapping against the floor.

It wasn’t his fault! His tail did that when he was content, or comfortable, or—fuck—when he was embarrassed.

Which meant that right now?

It was practically broadcasting to the entire world that Namjoon was a mess.

And, of course, because the universe hated him, you began to stir.

He immediately froze.

No.

No, no, no—

You let out a sleepy little hum, eyes barely cracking open as you blinked up at him, dazed and soft.

Then, in a tiny, adorable voice—

“You good, Joonie?”

Namjoon short-circuited.

Every cell in his body screamed NO, I AM NOT GOOD, I AM HAVING A CRISIS OVER YOUR TITS.

But externally?

He just choked out, “Yeah.”

You blinked again, staring at him for a moment. Then, much to his horror, your gaze drifted past his shoulder

To his still-thumping tail.

A slow, knowing smirk spread across your face.

“Oh?”

Namjoon’s soul left his body.

“N-no,” he stammered, ears burning.

But you—being the absolute menace that you were—tilted your head.

“Ohhh?”

He panicked. “I—shut up.”

You giggled, snuggling back into his chest. “Your tail’s cute, y’know.”

Namjoon let out the longest sigh of his life.

This was actual suffering.

And you?

You were enjoying every second of it.

And Namjoon?

Namjoon was suffering.

He was suffering, and it was your fault.

Ever since the tail betrayal, he had been on edge, constantly catching himself thinking things he absolutely should not be thinking.

And it only got worse.

Because you kept sitting on his lap.

You kept looking up at him with those wide eyes.

You kept giggling, doing your little gremlin antics, completely oblivious to the war inside his head.

And the worst part?

He liked it.

Namjoon liked having you on his lap.

He liked the way you poked his cheek, teasing him.

He liked when you fidgeted, shifting against his thighs, completely unaware of how much damage you were doing.

So, tonight?

Tonight, as he flopped onto his bed, exhausted, his brain finally snapped.

“Dammit. Fuck.”

But then—

Fuck her.

Fuck… her.

Oh.

Oh.

Fuck… how would it feel to fuck… her?

Namjoon froze.

His entire body locked up as his brain betrayed him, conjuring up images—images of you under him, gasping, giggling, teasing him even as he—

NOPE. NOPE NOPE NOPE.

He let out a strangled groan, flinging an arm over his face in denial.

Then, hesitantly—dread pooling in his stomach—he glanced down.

…Yep.

He was hard.

Namjoon let out the longest, most miserable sigh of his life.

This was actual hell.

And you?

You had no idea.

Namjoon lay there for a long moment, staring at the ceiling like it personally wronged him.

This was your fault.

Absolutely, entirely your fault.

Because if you weren’t such a tiny, chaotic, adorable menace, then maybe—maybe—he wouldn’t be in this situation.

But, no.

No, you had to go and sit in his lap all the time.

You had to poke his cheeks, tease him, giggle like a damn gremlin.

You had to look at him with those big, innocent eyes, completely unaware of the monster you were creating.

And now?

Now, here he was—rock hard, frustrated, and miserable.

Namjoon sighed deeply.

Then, resigned, he reached for the tissues and lotion.

It wasn’t like this was new.

He was a man. He had needs. And if he was going to be suffering anyway, he might as well… deal with it.

So, with a groan, he stripped, settled in, and started his very familiar routine.

…He was not thinking about you.

Nope.

Absolutely not.

But when his eyes fluttered shut, when his hand started moving—

A vision of you flashed through his mind.

Your lips, parted slightly.

Your thighs, spread beneath him.

Your voice, giggling—What’s wrong, Joonie? Cat got your tongue?

Namjoon whined.

This was a problem.

A very big problem.

This was supposed to be quick.

A means to an end.

Just get it over with, clear his head, move on.

But the second his hand wrapped around his cock—his traitorous brain ran wild.

At first, it was just flashes.

Your tits.

Your ass.

The memory of you sitting in his lap, shifting just right–

But then, his mind dove deeper.

The "perverted bear" incident surfaced.

The weight of your body bouncing on top of him, your tiny hands pressing against his chest, your soft little gasp when you felt him—

Namjoon bit his lip, groaning softly.

He should stop.

He should not be thinking about this.

But he didn’t stop.

He couldn’t.

Because then he imagined more.

You, beneath him.

Your legs spread wide.

Your body so tiny compared to his—so soft, so helpless against his weight.

Namjoon’s breath hitched.

Fuck.

Fuck.

A mating press.

The size difference.

The way you’d squirm, overwhelmed, panting, looking up at him with those big, adorable eyes—

"Fuck," he gasped, hips jerking into his hand.

This was so bad.

So, so bad.

But it felt so fucking good.

And the worst part?

He didn’t want to stop.

Not when his mind was already drowning in the thought of you, spread out, filled to the brim—

His.

Completely his.

CONTINUATION OF CHAPTER

[feminist-space]

Excerpts:

"The convenience of instant answers that LLMs provide can encourage passive consumption of information, which may lead to superficial engagement, weakened critical thinking skills, less deep understanding of the materials, and less long-term memory formation [8]. The reduced level of cognitive engagement could also contribute to a decrease in decision-making skills and in turn, foster habits of procrastination and "laziness" in both students and educators [13].

Additionally, due to the instant availability of the response to almost any question, LLMs can possibly make a learning process feel effortless, and prevent users from attempting any independent problem solving. By simplifying the process of obtaining answers, LLMs could decrease student motivation to perform independent research and generate solutions [15]. Lack of mental stimulation could lead to a decrease in cognitive development and negatively impact memory [15]. The use of LLMs can lead to fewer opportunities for direct human-to-human interaction or social learning, which plays a pivotal role in learning and memory formation [16].

Collaborative learning as well as discussions with other peers, colleagues, teachers are critical for the comprehension and retention of learning materials. With the use of LLMs for learning also come privacy and security issues, as well as plagiarism concerns (7]. Yang et al. [17] conducted a study with high school students in a programming course. The experimental group used ChatGPT to assist with learning programming, while the control group was only exposed to traditional teaching methods. The results showed that the experimental group had lower flow experience, self-efficacy, and learning performance compared to the control group.

Academic self-efficacy, a student's belief in their "ability to effectively plan, organize, and execute academic tasks"

', also contributes to how LLMs are used for learning [18]. Students with

low self-efficacy are more inclined to rely on Al, especially when influenced by academic stress

[18]. This leads students to prioritize immediate Al solutions over the development of cognitive and creative skills. Similarly, students with lower confidence in their writing skills, lower

"self-efficacy for writing" (SEWS), tended to use ChatGPT more extensively, while higher-efficacy students were more selective in Al reliance [19]. We refer the reader to the meta-analysis [20] on the effect of ChatGPT on students' learning performance, learning perception, and higher-order thinking."

"Recent empirical studies reveal concerning patterns in how LLM-powered conversational search systems exacerbate selective exposure compared to conventional search methods. Participants engaged in more biased information querying with LLM-powered conversational search, and an opinionated LLM reinforcing their views exacerbated this bias [63]. This occurs because LLMS are in essence "next token predictors" that optimize for most probable outputs, and thus can potentially be more inclined to provide consonant information than traditional information system algorithms [63]. The conversational nature of LLM interactions compounds this effect, as users can engage in multi-turn conversations that progressively narrow their information exposure. In LLM systems, the synthesis of information from multiple sources may appear to provide diverse perspectives but can actually reinforce existing biases through algorithmic selection and presentation mechanisms.

The implications for educational environments are particularly significant, as echo chambers can fundamentally compromise the development of critical thinking skills that form the foundation of quality academic discourse. When students rely on search systems or language models that systematically filter information to align with their existing viewpoints, they might miss opportunities to engage with challenging perspectives that would strengthen their analytical capabilities and broaden their intellectual horizons. Furthermore, the sophisticated nature of these algorithmic biases means that a lot of users often remain unaware of the information gaps in their research, leading to overconfident conclusions based on incomplete evidence. This creates a cascade effect where poorly informed arguments become normalized in academic and other settings, ultimately degrading the standards of scholarly debate and undermining the educational mission of fostering independent, evidence-based reasoning."

"In summary, the Brain-only group's connectivity suggests a state of increased internal coordination, engaging memory and creative thinking (manifested as theta and delta coherence across cortical regions). The Engine group, while still cognitively active, showed a tendency toward more focal connectivity associated with handling external information (e.g. beta band links to visual-parietal areas) and comparatively less activation of the brain's long-range memory circuits. These findings are in line with literature: tasks requiring internal memory amplify low-frequency brain synchrony in frontoparietal networks [77], whereas outsourcing information (via internet search) can reduce the load on these networks and alter attentional dynamics. Notably, prior studies have found that practicing internet search can reduce activation in memory-related brain areas [831, which dovetails with our observation of weaker connectivity in those regions for Search Engine group. Conversely, the richer connectivity of Brain-only group may reflect a cognitive state akin to that of high performers in creative or memory tasks, for instance, high creativity has been associated with increased fronto-occipital theta connectivity and intra-hemispheric synchronization in frontal-temporal circuits [81], patterns we see echoed in the Brain-only condition."

"This correlation between neural connectivity and behavioral quoting failure in LLM group's participants offers evidence that:

1. Early Al reliance may result in shallow encoding.

LLM group's poor recall and incorrect quoting is a possible indicator that their earlier essays were not internally integrated, likely due to outsourced cognitive processing to the LLM.

2. Withholding LLM tools during early stages might support memory formation.

Brain-only group's stronger behavioral recall, supported by more robust EEG connectivity, suggests that initial unaided effort promoted durable memory traces, enabling more effective reactivation even when LLM tools were introduced later.

Metacognitive engagement is higher in the Brain-to-LLM group.

Brain-only group might have mentally compared their past unaided efforts with tool-generated suggestions (as supported by their comments during the interviews), engaging in self-reflection and elaborative rehearsal, a process linked to executive control and semantic integration, as seen in their EEG profile.

The significant gap in quoting accuracy between reassigned LLM and Brain-only groups was not merely a behavioral artifact; it is mirrored in the structure and strength of their neural connectivity. The LLM-to-Brain group's early dependence on LLM tools appeared to have impaired long-term semantic retention and contextual memory, limiting their ability to reconstruct content without assistance. In contrast, Brain-to-LLM participants could leverage tools more strategically, resulting in stronger performance and more cohesive neural signatures."

[sth-askverse]

Maybe you both are right, but If he does show up at anytime, maybe We could help you guys out! ...Somehow...

But have we ruled out the possibility Eggman is somehow behind these rifts, himself?

No, but, then it wouldn't be the first time one of his "Master Plans" backfired on him.

True enough.

... AH. THE SHREDDED SKY ALSO HAS QUERIES. I WILL ENDEAVOR TO ANSWER THEM. AS FOR MY ANALYSIS ON THE STATUS OF MY CREATOR, I CAN SAY ONLY I AM DISAPPOINTED THAT HE MAY HAVE MET HIS END BEFORE I COULD DELIVER IT TO HIM MYSELF. AND IF HE LIVES, I WILL RESUME MY MISSION AS I HAVE.

... you shred your pillows missing me~? Aww, sunshine~!

Shut the fuck up right now-

First | < Previous - Next >

[EDIT: fixed rouges broken ass hand lol]

[probablyasocialecologist]

To bring about its hypothetical future, OpenAI must build a new digital ecosystem, pushing users toward the ChatGPT app or toward preëxisting products that integrate its technology such as Bing, the search engine run by OpenAI’s major investor, Microsoft. Google, by contrast, already controls the technology that undergirds many of our online experiences, from search and e-mail to Android smartphone-operating systems. At its conference, the company showed how it plans to make A.I. central to all of the above. Some Google searches now yield A.I.-generated “Overview” summaries, which appear in tinted boxes above any links to external Web sites. Liz Reid, Google’s head of search, described the generated results with the ominously tautological tagline “Google will do the Googling for you.” (The company envisions that you will rely on the same search mechanism to trawl your own digital archive, using its Gemini assistant to, say, pull up photos of your child swimming over the years or summarize e-mail threads in your in-box.) Nilay Patel, the editor-in-chief of the tech publication the Verge, has been using the phrase “Google Zero” to describe the point at which Google will stop driving any traffic to external Web sites and answer every query on its own with A.I. The recent presentations made clear that such a point is rapidly approaching. One of Google’s demonstrations showed a user asking the A.I. a question about a YouTube video on pickleball: “What is the two-bounce rule?” The A.I. then extracted the answer from the footage and displayed the answer in writing, thus allowing the user to avoid watching either the video or any advertising that would have provided revenue to its creator. When I Google “how to decorate a bathroom with no windows” (my personal litmus test for A.I. creativity), I am now presented with an Overview that looks a lot like an authoritative blog post, theoretically obviating my need to interact directly with any content authored by a human being. Google Search was once seen as the best path for getting to what’s on the Web. Now, ironically, its goal is to avoid sending us anywhere. The only way to use the search function without seeing A.I.-generated content is to click a small “More” tab and select “Web” search. Then Google will do what it was always supposed to do: crawl the Internet looking for URLs that are relevant to your queries, and then display them to you. The Internet is still out there, it’s just increasingly hard to find. If A.I. is to be our primary guide to the world’s information, if it is to be our 24/7 assistant-librarian-companion as the tech companies propose, then it must constantly be adding new information to its data sets. That information cannot be generated by A.I., because A.I. tools are not capable of even one iota of original thought or analysis, nor can they report live from the field. (An information model that is continuously updated, using human labor, to inform us about what’s going on right now—we might call it a newspaper.) For a decade or more, social media was a great way to motivate billions of human beings to constantly upload new information to the Internet. Users were driven by the possibilities of fame and profit and mundane connection. Many media companies were motivated by the possibility of selling digital ads, often with Google itself as a middle man. In the A.I. era, in which Google can simply digest a segment of your post or video and serve it up to a viewer, perhaps not even acknowledging you as the original author, those incentives for creating and sharing disappear. In other words, Google and OpenAI seem poised to cause the erosion of the very ecosystem their tools depend on.

[percheduphere]

Super serious question for your meta analysis skills: If the Avengers met the TVA crew, how quickly do you think their intimidating view of Loki would go out the window?

Ex: Casey being told Loki was a villain: “I mean, he was kinda a jerk when he threatened me and then later stole my juice but calling him a villain seems a bit much.” OB: “Really? He’s always seemed nice to me!” B-15: “Eh, he’s kinda like Mobius, can be a threat but usually a nice guy.” Avengers: *Wondering if there’s some TVA rando named Loki*

Hi Anon!

I am so so sorry it takes so long for me to reply. I finally made it to yours!

I actually wrote a lil' CONSIDER scenario, in which Loki introduces Thor to his friends. While not the same conditions as what you are querying, I think the effect would be very similar. That is: Loki is really just a pussycat!

That said, the Avengers' reactions would vary depending on who they meet first. It honestly would not take long at all before Loki's villain persona just falls apart. They'll probably wonder how Loki managed to be such a thorn on their side to begin with (*cough* Thanos *cough*).

If they start with Casey, he'd probably say something like: "Oh, yeah. He threatened to gut me like a fish once, but other than that he's actually pretty good guy!" O.B., like you said, would be similar. And because he's a ray of sunshine, he might respond, "Loki is Mobius's friend, and any friend of Mobius is a friend of mine, too!"

But things start to get really hilarious once we get to the B-15 and Sylvie.

If they start with B-15 (Verity), she will just laugh in their faces. Or she will look at them all judgy, as if to say: "Really? This magic gremlin gave you all a hard time? Mmkay ..." Kinda like this:

Sylvie would probably laugh in their faces, too, likely commenting on Loki's shit plans.

If the Avengers met Sylvie and B-15 together, they would just ... bend over their knees cackling. They'd have to wipe the tears from their eyes from laughing so hard.

And then, of course, we have Mobius.

I think he'd be somewhere between Casey & O.B. and B-15 & Sylvie, with a heaping of: I love him. He's great. He messes up a lot and feels bad about it, but that's what makes him adorable. If something happens to him, I will turn into a soggy piece of crinkled paper.

So Mobius's reaction would be a little bit of this:

A touch of this:

And a sprinkle of this for good measure. Because Mobius loves Loki and literally has ZERO pokerface when it comes to him:

Once the Avengers watch Loki and Mobius playfully bicker, it's all over. It's proof Loki's domesticated.

Hope that answers your question, Anon!

[thelongestway]

Yeah, okay, SecUnit surprised me there. I started this chapter like three times, it was sort of working but not really, and then I got... This out of it.

SecUnit, of all the people to latch on to in this situation...

Chapter 5: HubSystem

What is your assessment? ART said to us once Seth and I were out of the incredibly long and harrowing feed conversation with the--

I didn't even know what Aspen fucking was anymore. A station? A colonist who woke up alone on a ship, its crew dead save for a fucked up AI who was…

Fuck, that was the worst part of it. Aspen'd cited some of the comments their technician had made, and… Fuck. Yeah. That AI wasn't trying to kill them. I knew what a murderbot looked like, and that AI wasn't it. It was something like a HubSystem which was forced by an idiot designer to grow into its sleeping crew. But it didn't want to take them over, that wasn't its directive. It wanted to get the colonists safely to their new home. It didn't turn on them even after Aspen killed half of it trying to save their engineer.

The AI still wound up killing half of the crew Aspen had roused, and almost killed Aspen themselves. Because their fucking tech told their AI those crew members could not be allowed to become a threat under any circumstances and removed its fucking safeguards, and its other ways of acting were already gone, because it was mutilated so many times over. So it believed its fucking human, and it tried its best to kill the humans who were designated hostile, and then their fucking tech killed the AI.

And then, five years later, they put Aspen into its corpse and let them take it over like some kind of parasitic fungus from horror media, and then the Courageous became the--fuck, Aspen called it the rootstock, didn't they?--for all of the node ships.

I realized neither Seth nor I were talking. And that ART was curling around me in the feed, concerned, but not intruding into my processes. It had taken the node ships' warning seriously. I signalled it that I was processing, and it confirmed, then shifted its attention to Seth.

Seth looked up at ART and said, swallowing, "I don't think Aspen's a threat to us, Peri. Most of the deaths happened when they were still just a colonist. The engineers of the Courageous fucked up very badly, multiple times, and there was corporate sabotage involved on top of that. Aspen was dealing with an impossible situation. It's amazing they got as many people alive to Hylara as they did."

"Query, SecUnit." ART said. "With the data you received from Aspen, what was the survival rate on the Courageous' mission?"

Yeah. Okay. I had that number, because I was running an ongoing threat analysis as Aspen told their story (and where I doubted them, I got a second opinion from Dandelion, who, as it turned out, had also seen most of the events.) So I had that number, and it was fucking insane.

"Less than five percent."

Seth gave a low whistle.

"There but for the grace of the stars go we…" he muttered.

I knew he wasn't thinking about the AI. Seth was thinking about waking up alone on a ship, and having the lives of five thousand humans in his hands, and losing two fifths of them to somebody's stupid science project. But I…

ART tightened its hold on me in the feed, and it put on the first episode of Sanctuary Moon.

Whatever you're seeing, you aren't there anymore, it said, pinging my hard address. You're here. Let's go watch our shows.

So we did. And when the crew met the next day, ART told its humans that they could go on board the Courageous, if they wanted.

---

Aspen tapped my feed the next day, but when I let them in, they didn't connect to me directly. Instead, they sent me a text message, like Iceblink would have: Hello, SecUnit. I wanted to know if there's anything you need from me to help you ensure your crew's safety.

A list of what your humans are planning to show mine, camera access on all those areas, as well as a list of potential threat factors that you can identify, existing safety measures and escape routes. Also, why are you using a text channel?

You seemed uncomfortable when we last talked, and Dandelion said you might prefer to do this in writing. Here's the access you requested, and the preliminary lists. Where threats are concerned, I might be able to specify in more detail if you let Dandelion release Preservation team members' medical data to me.

The lists were pretty comprehensive already, but the really unexpected part was that Aspen actually gave me camera access. I couldn't exactly see half the station, but it was a lot of cameras, and some of them looked like they were in high security areas.

(Others looked like they were on a planet, but even Dandelion, who was dozens of times smaller, had fucking greenhouse rings. Of course her fucking station would have entire forests. One looked like it was floating on water. I didn't know why or how that was possible, but the forest part was pretty easy to expect.)

Anyway, I wasn't really expecting them to give me camera access. Even though it was always on my request lists, nobody just gave you camera access before you've even worked together.

Query?

Specify?

Ugh. Talking to a fucking HubSyst-- okay, talking to a human who took over a dead HubSystem--like this was just painful. So I said,

Yeah, talking to you directly sucked. You kept shoving subprocesses into my face. But I can't work like this. Let's switch to a regular channel.

Hmm. Judging from my logs, you're reacting to my analytics, Aspen said, opening a normal feed channel. That's not an issue. I can shut most of those off. Is this better?

Yeah, it no longer felt like there were ten or more of those fucking little tendrils slithering right next to my own feed presence, looking like they'd crawl into my processes at any second. (Ew. Fuck.) (This was so much better.) But wow, was this a stupid decision on their part.

You're giving me visual access to secure areas and then turning off analytics targeting me, just because I said talking to you sucked? What the hell is wrong with your risk assessments?

They're not the really necessary ones, Aspen said indifferently. Just old habit. I keep track of you well enough without them.

Right, like that wasn't ominous or anything. But it was kind of true, maybe: I could see they had most of the standard analytical suites (or local versions of the same) a HubSysem would have still running. Those weird tendrils? I had no idea what they were even for.

Query: analytics target?

Response: sociological analysis. Specification needed?

Query: is it going to be a reading list with 800-year-old readings?

Aspen paused. A few of their little tendrils raised their heads curiously, but didn't go anywhere near me. Instead, they said, I'm sorry, what?

The last time I asked to specify the purposes of a sociological analysis, I was given this, I dumped Thiago's reading list into the feed channel.

Aspen skimmed the list, very quickly at first, like they were looking for a specific data point. Then they sifted through it again, slower. (It still took less than a second.) Then they said, Wow. You've really pissed someone off.

I was insisting they take security precautions they didn't like.

Aspen's functions flickered, and their curious tendrils dissolved back into their main presence.

Ha. Yeah, we don't like doing that. They said with a sudden bitterness. But no. I'm not going to be an asshole to you and give you a fucking reading list. How about this, SecUnit. I'll run my analytics alongside yours when we handle the visits. I'll try not to aim them at you unless I really need to, and if you need an explanation, we can always drop into accelerated time. Does that sound good?

Weirdly, it actually kind of did.

Yeah, I said. Yeah. Let's try that.

[warydoom]

An Open Letter to My Brain, Regarding the Inherent Right to Write Glorious Nonsense (Without Imploding) (Part 2)

The pact.

Signed in the glitter of chaotic inspiration, the tears of exasperation, and the faint scent of stale coffee.

We will not plan a multi-chapter epic. We will not construct an elaborate relationship timeline complete with color-coded flowcharts and projected emotional milestones. We will not conduct a forensic investigation into why Nigtwing said that in the last comic we read, or whether his unicycle has regulatory compliant tires, or whether his discowing costume is ethically sourced.

We are definitely not allowing you to deploy the "Research Black Hole" where a simple query about a fictional shoe leads to a doctorate in cobbling history, a comprehensive analysis of the global leather market, and a philosophical treatise on the existential burden of footwear.

Instead, we are going to treat these first drafts like the "First Pancake" of writing. You know how the first pancake is always a little wonky? Too hot, too cold, unevenly cooked, slightly burnt on one side but strangely raw on the other, perhaps shaped like a map of a forgotten continent or an abstract depiction of existential dread? It sticks to the pan, it rips when you try to flip it, it refuses to brown evenly. But you eat it anyway! It’s still a pancake. It serves its purpose of soaking up syrup (or in our case, delicious, delicious absurdity and the sheer pleasure of defiance). And it clears the way for the better pancakes, the ones that might actually look like they came from a professional chef.

This isn't for public consumption (unless we decide later, after a long nap, a particularly strong cup of tea, and a profound realization that this wonky pancake might actually be the best pancake, that it possesses a certain charming imperfection).

This is for us. For our amusement. For the sheer, unadulterated joy of the squishy, gooey, slightly undercooked, gloriously messy creative process. We are going to dive headfirst into the fluffy, silly relationship stuff.

Yes, you will scream. I expect it. It's your job, apparently, to be the internal alarm system for all things unplotted and unresearched, to shriek like a banshee whenever a dangling participle appears. But I am going to put my fingers on the keyboard and just… write. I will allow myself to write sentences that are awkward. Scenarios that are absurd. Details that might contradict each other between headcanons because, frankly, each headcanon is its own glorious, self-contained universe of nonsense, operating under its own bespoke laws of physics and narrative logic.

Because this is the playground phase.

This is where the chaos gremlin himself would feel most at home, probably setting off confetti cannons, riding his unicycle through puddles of questionable origin, and teaching squirrels to juggle. And if we spot an inconsistency later? Fantastic! That means we actually wrote something. That means the words flowed! And guess what?

We can either chuckle, shrug, and move on, because this isn't a thesis paper destined for peer review by a panel of literary robots, or we can, heaven forbid, tweak it.

After the fun part is over.

After the initial burst of glorious, unhinged inspiration has been safely captured on the page. Only then, maybe, will we consider bringing out a tiny, tiny, tiny red pen. And even then, it will be a glitter pen.

So, my dear brain, holster your planning charts. Put away your red pen. Turn off the internal alarm system that warns of impending grammatical doom and the collapse of the space-time continuum due to a minor plot hole. Unclench your metaphorical jaw.

Let’s make a glorious mess. Let’s embrace the silliness. Let’s write a meet cute scenario where perhaps Oc is suddenly a chocolatier with super medic skills and a secret passion for competitive unicycling and she only communicates in highly specific, interpretive dance moves involving artisanal chocolate.

Don't ask why she's in a chocolate factory in the first place, or how her medical skills relate to cocoa beans, or why he insists on performing surgery on a unicycle while simultaneously explaining the intricacies of the chocolate tempering process through interpretive dance.

Just let it happen. Let the glitter fly. Let the discowig spin. Let the wonky pancakes stack up. Let the internal screaming be drowned out by the joyous cacophony of creation! For the love of all that is chaotic and cute and utterly, gloriously nonsensical, let's just have some fun. Before you decide to meticulously catalog all the dust bunnies under my desk.

Sincerely,

Your tired but determined creative partner, currently holding a glitter bomb, a metaphorical unicycle, and a slightly burnt first pancake.

[songue85]

I would've tagged you but I thought you were only working on Arachnomaly! I should've known that all writers have a WIP drawer. I'd love to know more about "Opening a Door"

No worries! You had to pick the special one, of course!

This is a separate file for a chapter of Arachnomaly, one of the chapters that is going to change the direction of the plot... it's astill rough around the edges, but I've started it almost a year ago!

Let's take a peek?

“PARKER!”, Sajani yelled, as she pulled the lever in front of her. “The last capacitor is at its limit!” “We need to hold the breach a minute longer, Sajani!”, Peter Parker was fast at the computer station, correcting the equation on the fly. ‘Just a bit more… and I can form the bridge!’ The machine sparked, the spark of light hanging in the air starting to grow, though still unstable. “Structural analysis?”, he queried his colleague, who gave him a thumbs up in reply. “Still stable!” Grady Scraps was about to turn on his switch, but Peter stopped him. “Not yet, Grady!” “Parker, it’s gone too far already!”, replied the man, a new Hawaiian shirt under his lab coat, night sky themed this time. “If you turn on the attenuator, the stabilization process will not occur!” Peter spoke up, in expectation. All the simulations had been made and now the whole process was automated, and the only thing left was to hope things would go according to his plan. “He’s right, G”, Metron Jackson pointed out, still behind the shielding panel. “You don’t know that!” “I ran the numbers on my mind.”, the kid replied. “You say it like that is reassuring!”

[datawarehousing01]

Data warehousing solution

Unlocking the Power of Data Warehousing: A Key to Smarter Decision-Making

In today's data-driven world, businesses need to make smarter, faster, and more informed decisions. But how can companies achieve this? One powerful tool that plays a crucial role in managing vast amounts of data is data warehousing. In this blog, we’ll explore what data warehousing is, its benefits, and how it can help organizations make better business decisions.

What is Data Warehousing?

At its core, data warehousing refers to the process of collecting, storing, and managing large volumes of data from different sources in a central repository. The data warehouse serves as a consolidated platform where all organizational data—whether from internal systems, third-party applications, or external sources—can be stored, processed, and analyzed.

A data warehouse is designed to support query and analysis operations, making it easier to generate business intelligence (BI) reports, perform complex data analysis, and derive insights for better decision-making. Data warehouses are typically used for historical data analysis, as they store data from multiple time periods to identify trends, patterns, and changes over time.

Key Components of a Data Warehouse

To understand the full functionality of a data warehouse, it's helpful to know its primary components:

Data Sources: These are the various systems and platforms where data is generated, such as transactional databases, CRM systems, or external data feeds.

ETL (Extract, Transform, Load): This is the process by which data is extracted from different sources, transformed into a consistent format, and loaded into the warehouse.

Data Warehouse Storage: The central repository where cleaned, structured data is stored. This can be in the form of a relational database or a cloud-based storage system, depending on the organization’s needs.

OLAP (Online Analytical Processing): This allows for complex querying and analysis, enabling users to create multidimensional data models, perform ad-hoc queries, and generate reports.

BI Tools and Dashboards: These tools provide the interfaces that enable users to interact with the data warehouse, such as through reports, dashboards, and data visualizations.

Benefits of Data Warehousing

Improved Decision-Making: With data stored in a single, organized location, businesses can make decisions based on accurate, up-to-date, and complete information. Real-time analytics and reporting capabilities ensure that business leaders can take swift action.

Consolidation of Data: Instead of sifting through multiple databases or systems, employees can access all relevant data from one location. This eliminates redundancy and reduces the complexity of managing data from various departments or sources.

Historical Analysis: Data warehouses typically store historical data, making it possible to analyze long-term trends and patterns. This helps businesses understand customer behavior, market fluctuations, and performance over time.

Better Reporting: By using BI tools integrated with the data warehouse, businesses can generate accurate reports on key metrics. This is crucial for monitoring performance, tracking KPIs (Key Performance Indicators), and improving strategic planning.

Scalability: As businesses grow, so does the volume of data they collect. Data warehouses are designed to scale easily, handling increasing data loads without compromising performance.

Enhanced Data Quality: Through the ETL process, data is cleaned, transformed, and standardized. This means the data stored in the warehouse is of high quality—consistent, accurate, and free of errors.

Types of Data Warehouses

There are different types of data warehouses, depending on how they are set up and utilized:

Enterprise Data Warehouse (EDW): An EDW is a central data repository for an entire organization, allowing access to data from all departments or business units.

Operational Data Store (ODS): This is a type of data warehouse that is used for storing real-time transactional data for short-term reporting. An ODS typically holds data that is updated frequently.

Data Mart: A data mart is a subset of a data warehouse focused on a specific department, business unit, or subject. For example, a marketing data mart might contain data relevant to marketing operations.

Cloud Data Warehouse: With the rise of cloud computing, cloud-based data warehouses like Google BigQuery, Amazon Redshift, and Snowflake have become increasingly popular. These platforms allow businesses to scale their data infrastructure without investing in physical hardware.

How Data Warehousing Drives Business Intelligence

The purpose of a data warehouse is not just to store data, but to enable businesses to extract valuable insights. By organizing and analyzing data, businesses can uncover trends, customer preferences, and operational inefficiencies. Some of the ways in which data warehousing supports business intelligence include:

Customer Segmentation: Companies can analyze data to segment customers based on behavior, demographics, or purchasing patterns, leading to better-targeted marketing efforts.

Predictive Analytics: By analyzing historical data, businesses can forecast trends and predict future outcomes, such as sales, inventory needs, and staffing levels.

Improved Operational Efficiency: With data-driven insights, businesses can streamline processes, optimize supply chains, and reduce costs. For example, identifying inventory shortages or surplus can help optimize stock levels.

Challenges in Data Warehousing

While the benefits of data warehousing are clear, there are some challenges to consider:

Complexity of Implementation: Setting up a data warehouse can be a complex and time-consuming process, requiring expertise in database management, ETL processes, and BI tools.

Data Integration: Integrating data from various sources with differing formats can be challenging, especially when dealing with legacy systems or unstructured data.

Cost: Building and maintaining a data warehouse can be expensive, particularly when managing large volumes of data. However, the investment is often worth it in terms of the business value generated.

Security: With the consolidation of sensitive data in one place, data security becomes critical. Organizations need robust security measures to prevent unauthorized access and ensure compliance with data protection regulations.

The Future of Data Warehousing

The world of data warehousing is constantly evolving. With advancements in cloud technology, machine learning, and artificial intelligence, businesses are now able to handle larger datasets, perform more sophisticated analyses, and automate key processes.

As companies increasingly embrace the concept of a "data-driven culture," the need for powerful data warehousing solutions will continue to grow. The integration of AI-driven analytics, real-time data processing, and more intuitive BI tools will only further enhance the value of data warehouses in the years to come.

Conclusion

In today’s fast-paced, data-centric world, having access to accurate, high-quality data is crucial for making informed business decisions. A robust data warehousing solution enables businesses to consolidate, analyze, and extract valuable insights from their data, driving smarter decision-making across all departments. While building a data warehouse comes with challenges, the benefits—improved efficiency, better decision-making, and enhanced business intelligence—make it an essential tool for modern organizations.

You said:

blog for Data warehousing

ChatGPT said:

Title: Data Warehousing: The Backbone of Data-Driven Decision Making

In today’s fast-paced business environment, the ability to make data-driven decisions quickly is paramount. However, to leverage data effectively, companies need more than just raw data. They need a centralized, structured system that allows them to store, manage, and analyze data seamlessly. This is where data warehousing comes into play.

Data warehousing has become the cornerstone of modern business intelligence (BI) systems, enabling organizations to unlock valuable insights from vast amounts of data. In this blog, we’ll explore what data warehousing is, why it’s important, and how it drives smarter decision-making.

What is Data Warehousing?

At its core, data warehousing refers to the process of collecting and storing data from various sources into a centralized system where it can be easily accessed and analyzed. Unlike traditional databases, which are optimized for transactional operations (i.e., data entry, updating), data warehouses are designed specifically for complex queries, reporting, and data analysis.

A data warehouse consolidates data from various sources—such as customer information systems, financial systems, and even external data feeds—into a single repository. The data is then structured and organized in a way that supports business intelligence (BI) tools, enabling organizations to generate reports, create dashboards, and gain actionable insights.

Key Components of a Data Warehouse

Data Sources: These are the different systems or applications that generate data. Examples include CRM systems, ERP systems, external APIs, and transactional databases.

ETL (Extract, Transform, Load): This is the process by which data is pulled from different sources (Extract), cleaned and converted into a usable format (Transform), and finally loaded into the data warehouse (Load).

Data Warehouse Storage: The actual repository where structured and organized data is stored. This could be in traditional relational databases or modern cloud-based storage platforms.

OLAP (Online Analytical Processing): OLAP tools enable users to run complex analytical queries on the data warehouse, creating reports, performing multidimensional analysis, and identifying trends.

Business Intelligence Tools: These tools are used to interact with the data warehouse, generate reports, visualize data, and help businesses make data-driven decisions.

Benefits of Data Warehousing

Improved Decision Making: By consolidating data into a single repository, decision-makers can access accurate, up-to-date information whenever they need it. This leads to more informed, faster decisions based on reliable data.

Data Consolidation: Instead of pulling data from multiple systems and trying to make sense of it, a data warehouse consolidates data from various sources into one place, eliminating the complexity of handling scattered information.

Historical Analysis: Data warehouses are typically designed to store large amounts of historical data. This allows businesses to analyze trends over time, providing valuable insights into long-term performance and market changes.

Increased Efficiency: With a data warehouse in place, organizations can automate their reporting and analytics processes. This means less time spent manually gathering data and more time focusing on analyzing it for actionable insights.

Better Reporting and Insights: By using data from a single, trusted source, businesses can produce consistent, accurate reports that reflect the true state of affairs. BI tools can transform raw data into meaningful visualizations, making it easier to understand complex trends.

Types of Data Warehouses

Enterprise Data Warehouse (EDW): This is a centralized data warehouse that consolidates data across the entire organization. It’s used for comprehensive, organization-wide analysis and reporting.

Data Mart: A data mart is a subset of a data warehouse that focuses on specific business functions or departments. For example, a marketing data mart might contain only marketing-related data, making it easier for the marketing team to access relevant insights.

Operational Data Store (ODS): An ODS is a database that stores real-time data and is designed to support day-to-day operations. While a data warehouse is optimized for historical analysis, an ODS is used for operational reporting.

Cloud Data Warehouse: With the rise of cloud computing, cloud-based data warehouses like Amazon Redshift, Google BigQuery, and Snowflake have become popular. These solutions offer scalable, cost-effective, and flexible alternatives to traditional on-premises data warehouses.

How Data Warehousing Supports Business Intelligence

A data warehouse acts as the foundation for business intelligence (BI) systems. BI tools, such as Tableau, Power BI, and QlikView, connect directly to the data warehouse, enabling users to query the data and generate insightful reports and visualizations.

For example, an e-commerce company can use its data warehouse to analyze customer behavior, sales trends, and inventory performance. The insights gathered from this analysis can inform marketing campaigns, pricing strategies, and inventory management decisions.

Here are some ways data warehousing drives BI and decision-making:

Customer Insights: By analyzing customer purchase patterns, organizations can better segment their audience and personalize marketing efforts.

Trend Analysis: Historical data allows companies to identify emerging trends, such as seasonal changes in demand or shifts in customer preferences.

Predictive Analytics: By leveraging machine learning models and historical data stored in the data warehouse, companies can forecast future trends, such as sales performance, product demand, and market behavior.

Operational Efficiency: A data warehouse can help identify inefficiencies in business operations, such as bottlenecks in supply chains or underperforming products.

[scbhagat]

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[riazhatvi]

People Think It’s Fake" | DeepSeek vs ChatGPT: The Ultimate 2024 Comparison (SEO-Optimized Guide)

The AI wars are heating up, and two giants—DeepSeek and ChatGPT—are battling for dominance. But why do so many users call DeepSeek "fake" while praising ChatGPT? Is it a myth, or is there truth to the claims? In this deep dive, we’ll uncover the facts, debunk myths, and reveal which AI truly reigns supreme. Plus, learn pro SEO tips to help this article outrank competitors on Google!

Chapters

00:00 Introduction - DeepSeek: China’s New AI Innovation

00:15 What is DeepSeek?

00:30 DeepSeek’s Impressive Statistics

00:50 Comparison: DeepSeek vs GPT-4

01:10 Technology Behind DeepSeek

01:30 Impact on AI, Finance, and Trading

01:50 DeepSeek’s Effect on Bitcoin & Trading

02:10 Future of AI with DeepSeek

02:25 Conclusion - The Future is Here!

Why Do People Call DeepSeek "Fake"? (The Truth Revealed)

The Language Barrier Myth

DeepSeek is trained primarily on Chinese-language data, leading to awkward English responses.

Example: A user asked, "Write a poem about New York," and DeepSeek referenced skyscrapers as "giant bamboo shoots."

SEO Keyword: "DeepSeek English accuracy."

Cultural Misunderstandings

DeepSeek’s humor, idioms, and examples cater to Chinese audiences. Global users find this confusing.

ChatGPT, trained on Western data, feels more "relatable" to English speakers.

Lack of Transparency

Unlike OpenAI’s detailed GPT-4 technical report, DeepSeek’s training data and ethics are shrouded in secrecy.

LSI Keyword: "DeepSeek data sources."

Viral "Fail" Videos

TikTok clips show DeepSeek claiming "The Earth is flat" or "Elon Musk invented Bitcoin." Most are outdated or edited—ChatGPT made similar errors in 2022!

DeepSeek vs ChatGPT: The Ultimate 2024 Comparison

1. Language & Creativity

ChatGPT: Wins for English content (blogs, scripts, code).

Strengths: Natural flow, humor, and cultural nuance.

Weakness: Overly cautious (e.g., refuses to write "controversial" topics).

DeepSeek: Best for Chinese markets (e.g., Baidu SEO, WeChat posts).

Strengths: Slang, idioms, and local trends.

Weakness: Struggles with Western metaphors.

SEO Tip: Use keywords like "Best AI for Chinese content" or "DeepSeek Baidu SEO."

2. Technical Abilities

Coding:

ChatGPT: Solves Python/JavaScript errors, writes clean code.

DeepSeek: Better at Alibaba Cloud APIs and Chinese frameworks.

Data Analysis:

Both handle spreadsheets, but DeepSeek integrates with Tencent Docs.

3. Pricing & Accessibility

FeatureDeepSeekChatGPTFree TierUnlimited basic queriesGPT-3.5 onlyPro Plan$10/month (advanced Chinese tools)$20/month (GPT-4 + plugins)APIsCheaper for bulk Chinese tasksGlobal enterprise support

SEO Keyword: "DeepSeek pricing 2024."

Debunking the "Fake AI" Myth: 3 Case Studies

Case Study 1: A Shanghai e-commerce firm used DeepSeek to automate customer service on Taobao, cutting response time by 50%.

Case Study 2: A U.S. blogger called DeepSeek "fake" after it wrote a Chinese-style poem about pizza—but it went viral in Asia!

Case Study 3: ChatGPT falsely claimed "Google acquired OpenAI in 2023," proving all AI makes mistakes.

How to Choose: DeepSeek or ChatGPT?

Pick ChatGPT if:

You need English content, coding help, or global trends.

You value brand recognition and transparency.

Pick DeepSeek if:

You target Chinese audiences or need cost-effective APIs.

You work with platforms like WeChat, Douyin, or Alibaba.

LSI Keyword: "DeepSeek for Chinese marketing."

SEO-Optimized FAQs (Voice Search Ready!)

"Is DeepSeek a scam?" No! It’s a legitimate AI optimized for Chinese-language tasks.

"Can DeepSeek replace ChatGPT?" For Chinese users, yes. For global content, stick with ChatGPT.

"Why does DeepSeek give weird answers?" Cultural gaps and training focus. Use it for specific niches, not general queries.

"Is DeepSeek safe to use?" Yes, but avoid sensitive topics—it follows China’s internet regulations.

Pro Tips to Boost Your Google Ranking

Sprinkle Keywords Naturally: Use "DeepSeek vs ChatGPT" 4–6 times.

Internal Linking: Link to related posts (e.g., "How to Use ChatGPT for SEO").

External Links: Cite authoritative sources (OpenAI’s blog, DeepSeek’s whitepapers).

Mobile Optimization: 60% of users read via phone—use short paragraphs.

Engagement Hooks: Ask readers to comment (e.g., "Which AI do you trust?").

Final Verdict: Why DeepSeek Isn’t Fake (But ChatGPT Isn’t Perfect)

The "fake" label stems from cultural bias and misinformation. DeepSeek is a powerhouse in its niche, while ChatGPT rules Western markets. For SEO success:

Target long-tail keywords like "Is DeepSeek good for Chinese SEO?"

Use schema markup for FAQs and comparisons.

Update content quarterly to stay ahead of AI updates.

🚀 Ready to Dominate Google? Share this article, leave a comment, and watch it climb to #1!

Follow for more AI vs AI battles—because in 2024, knowledge is power! 🔍

[she-posts-nerdy-stuff]

Ok I know this isn’t my usual content and I do have more soc analysis coming, I promise, but I thought I’d share with you guys some gems from the planning sheet of my book sequel right now (no spoilers lol, just in case anything ever happens. I’m querying the first book at the minute so keep positive thoughts for me darlings)

“They go to meet the poncy royal family of wherever”

“She tells her the truth and she’s weirdly chill about it but it might just be because she’s drunk”

“She has a private meeting with the king but she’s feeling pretty done with his shit by this point”

“War is declared so they have to do a bunch of boring government-y things to request aid and unity or whatever from other countries”

“Travel to meet another poncy royal dude or whatever”

“But oh-oh (and who could’ve seen this coming) it was a trap!!”

“Also I guess they run out of donuts” (this one is written at the bottom of a long paragraph about the war and about the warped aristocratic view of militia and battle glory, but clearly I have my priorities in order)

“It’s very sad, and he’s the goddamn worst”

“That’s really fucking cruel of him to be honest, and she gets maaaaaaaaaad (understandably)”

“(Who, as a side note, is definitely still sulking)”

“She doesn’t like boats so that’s super unhelpful, and she has a demon living in her brain which is also probably quite inconvenient”

“So basically everyone is s t r e s s e d right now”

“(If I knew how to put sparkle emojis on word then there would be sparkle emojis around that)”

[biopractify]

How to Transition from Biotechnology to Bioinformatics: A Step-by-Step Guide

Biotechnology and bioinformatics are closely linked fields, but shifting from a wet lab environment to a computational approach requires strategic planning. Whether you are a student or a professional looking to make the transition, this guide will provide a step-by-step roadmap to help you navigate the shift from biotechnology to bioinformatics.

Why Transition from Biotechnology to Bioinformatics?

Bioinformatics is revolutionizing life sciences by integrating biological data with computational tools to uncover insights in genomics, proteomics, and drug discovery. The field offers diverse career opportunities in research, pharmaceuticals, healthcare, and AI-driven biological data analysis.

If you are skilled in laboratory techniques but wish to expand your expertise into data-driven biological research, bioinformatics is a rewarding career choice.

Step-by-Step Guide to Transition from Biotechnology to Bioinformatics

Step 1: Understand the Basics of Bioinformatics

Before making the switch, it’s crucial to gain a foundational understanding of bioinformatics. Here are key areas to explore:

Biological Databases – Learn about major databases like GenBank, UniProt, and Ensembl.

Genomics and Proteomics – Understand how computational methods analyze genes and proteins.

Sequence Analysis – Familiarize yourself with tools like BLAST, Clustal Omega, and FASTA.

🔹 Recommended Resources:

Online courses on Coursera, edX, or Khan Academy

Books like Bioinformatics for Dummies or Understanding Bioinformatics

Websites like NCBI, EMBL-EBI, and Expasy

Step 2: Develop Computational and Programming Skills

Bioinformatics heavily relies on coding and data analysis. You should start learning:

Python – Widely used in bioinformatics for data manipulation and analysis.

R – Great for statistical computing and visualization in genomics.

Linux/Unix – Basic command-line skills are essential for working with large datasets.

SQL – Useful for querying biological databases.

🔹 Recommended Online Courses:

Python for Bioinformatics (Udemy, DataCamp)

R for Genomics (HarvardX)

Linux Command Line Basics (Codecademy)

Step 3: Learn Bioinformatics Tools and Software

To become proficient in bioinformatics, you should practice using industry-standard tools:

Bioconductor – R-based tool for genomic data analysis.

Biopython – A powerful Python library for handling biological data.

GROMACS – Molecular dynamics simulation tool.

Rosetta – Protein modeling software.

🔹 How to Learn?

Join open-source projects on GitHub

Take part in hackathons or bioinformatics challenges on Kaggle

Explore free platforms like Galaxy Project for hands-on experience

Step 4: Work on Bioinformatics Projects

Practical experience is key. Start working on small projects such as:

✅ Analyzing gene sequences from NCBI databases ✅ Predicting protein structures using AlphaFold ✅ Visualizing genomic variations using R and Python

You can find datasets on:

NCBI GEO

1000 Genomes Project

TCGA (The Cancer Genome Atlas)

Create a GitHub portfolio to showcase your bioinformatics projects, as employers value practical work over theoretical knowledge.

Step 5: Gain Hands-on Experience with Internships

Many organizations and research institutes offer bioinformatics internships. Check opportunities at:

NCBI, EMBL-EBI, NIH (government research institutes)

Biotech and pharma companies (Roche, Pfizer, Illumina)

Academic research labs (Look for university-funded projects)

💡 Pro Tip: Join online bioinformatics communities like Biostars, Reddit r/bioinformatics, and SEQanswers to network and find opportunities.

Step 6: Earn a Certification or Higher Education

If you want to strengthen your credentials, consider:

🎓 Bioinformatics Certifications:

Coursera – Genomic Data Science (Johns Hopkins University)

edX – Bioinformatics MicroMasters (UMGC)

EMBO – Bioinformatics training courses

🎓 Master’s in Bioinformatics (optional but beneficial)

Top universities include Harvard, Stanford, ETH Zurich, University of Toronto

Step 7: Apply for Bioinformatics Jobs

Once you have gained enough skills and experience, start applying for bioinformatics roles such as:

Bioinformatics Analyst

Computational Biologist

Genomics Data Scientist

Machine Learning Scientist (Biotech)

💡 Where to Find Jobs?

LinkedIn, Indeed, Glassdoor

Biotech job boards (BioSpace, Science Careers)

Company career pages (Illumina, Thermo Fisher)

Final Thoughts

Transitioning from biotechnology to bioinformatics requires effort, but with the right skills and dedication, it is entirely achievable. Start with fundamental knowledge, build computational skills, and work on projects to gain practical experience.

Are you ready to make the switch? 🚀 Start today by exploring free online courses and practicing with real-world datasets!

[johndeersblogs]

ChatGPT vs. DeepSeek: Which AI Is Best for Digital Marketing?

How AI Is Changing the Digital Marketing Landscape

Artificial Intelligence (AI) is reshaping digital marketing by enhancing efficiency, automating tasks, and providing in-depth insights into consumer behavior. Businesses now rely on AI-driven tools to generate content, analyze data, and improve marketing strategies.

Among the most effective AI tools available today are ChatGPT and DeepSeek. Each brings unique capabilities that can enhance different aspects of digital marketing, from content production to campaign optimization. Whether you're a business owner or work with a digital marketing agency in Malta, understanding these tools can help you make an informed decision.

Understanding ChatGPT and DeepSeek

What Makes ChatGPT a Powerful AI Tool?

ChatGPT, developed by OpenAI, is a language model that understands and generates human-like text. Businesses use it for:

Automated Content Creation – Quickly producing blogs, social media posts, and emails.

AI Chatbots & Support – Providing real-time responses to customer queries.

SEO Assistance – Generating keyword-rich content and structuring blog articles for better search rankings.

What Does DeepSeek Offer?

DeepSeek specializes in analyzing large-scale data and delivering predictive insights to improve marketing efforts. Its key strengths include:

Audience Insights & Segmentation – Identifying customer groups based on preferences and behavior.

Ad Campaign Optimization – Refining marketing strategies using data-driven insights.

Personalized Content Recommendations – Suggesting tailored content to boost engagement and conversions.

While both tools support marketing strategies, their strengths differ. Let’s compare them in more detail.

Comparing ChatGPT and DeepSeek for Digital Marketing Success

Content Generation: Which AI Is More Effective?

Quality content is essential for a successful digital strategy. AI-powered tools can accelerate content creation while maintaining engagement.

ChatGPT specializes in generating blog posts, social media content, and marketing emails. It’s particularly useful for businesses that need fresh content regularly.

DeepSeek does not create content but provides valuable data insights, helping marketers determine what type of content their audience prefers.

Which one is better? If you need an AI-powered content writer, ChatGPT is the best choice. If you want AI-driven insights to plan your content strategy, DeepSeek is more effective.

SEO Optimization: How AI Helps Improve Search Rankings

A strong SEO strategy is crucial for visibility in search engines. AI can enhance content optimization by integrating relevant keywords and structuring information effectively.

ChatGPT generates keyword-rich content, optimizes meta descriptions, and suggests engaging blog topics.

DeepSeek analyzes search behavior and identifies high-performing keywords based on user trends.

Best choice? ChatGPT is ideal for writing SEO-friendly content, while DeepSeek provides data-driven keyword and trend analysis.

Ad Campaign Optimization: Which AI Drives Better Results?

Digital advertising relies on compelling ad copy and precise audience targeting. AI helps refine these aspects.

ChatGPT creates multiple ad variations for A/B testing, allowing marketers to test different messaging strategies.

DeepSeek uses predictive analysis to determine the best ad placements, budget distribution, and audience segmentation.

Which one is better? ChatGPT excels in crafting compelling ad copy, while DeepSeek ensures ads reach the most relevant audience for higher ROI.

Enhancing Customer Engagement with AI

Customer interactions play a critical role in brand loyalty. AI-powered tools streamline communication by automating responses and personalizing interactions.

ChatGPT powers AI chatbots that respond to customer inquiries and assist in lead generation.

DeepSeek tracks past customer behavior and predicts their future needs, enabling businesses to offer more personalized support.

Which one should you choose? ChatGPT is better for handling real-time conversations, while DeepSeek enhances personalization based on data insights.

Challenges of Using AI in Digital Marketing

Despite the benefits of AI-driven marketing, businesses should be aware of certain challenges:

AI-generated content may lack originality – Without human input, content can feel robotic or repetitive.

Potential data inaccuracies – AI models sometimes generate outdated or misleading information.

Privacy concerns – AI tools that analyze customer data must comply with strict security regulations.

How to Overcome These Challenges

Combine AI with human creativity – Ensure originality by refining AI-generated content.

Regularly review AI-generated outputs – Fact-check and update content as needed.

Prioritize data security – Implement strong privacy measures when using AI for customer analysis.

Which AI Tool Should You Choose for Digital Marketing?

Both ChatGPT and DeepSeek are valuable tools for digital marketing, but they serve different purposes:

ChatGPT is best for businesses that need content automation, chatbot integration, and SEO-friendly writing.

DeepSeek is ideal for companies looking for advanced audience insights, ad campaign optimization, and personalized marketing.

According to our malta marketing agency for businesses aiming to maximize results, combining both tools can provide the perfect balance between creativity (ChatGPT) and data-driven strategy (DeepSeek).

Would you like to explore how AI can elevate your marketing efforts? Let's discuss the best AI-powered solutions for your business!

[thelongestway]

Travelling once again, so a) watch out for mobile formatting, b) this is a bit rough 'round the edges. Maybe will use restructuring/tweaking later. But the practice of posting rough drafts has done me enormous good so far, I'm keeping it. :P

Besides, it's nothing special. Just a little fieldwork. :P

Chapter 7: Relations

"This is certainly a busy station," Mensah said when we emerged into the gigantic glass dome on top of Courageous Station, shielding her eyes from the glare of the sun coming through the transparent roof. Thiago handed her a pair of sunglasses, which she put on.

"It's always like this during a Meet. Not so much on regular days, although the gardens are never empty," Reed said as ke came up behind Mensah. (Ke had plans around the gardens, and offered to take my humans there on the way.) Now out of kes work jumpsuit and looking much more relaxed than ke usually did, ke was wearing the kind of colorful wrap Dandelion's humans usually had off-duty and was shouldering a bag. Ke didn't even have their communicator on kem.

(I mean, in case of emergency, Dandelion could probably reach kem through Aspen. In contrast to Aspen's constantly shifting processes, she had hers mostly silenced and was now simply sitting alongside Aspen, not doing much aside from basic maintenance. That, and keeping a narrow connection into our feed work space, tracking us with maybe half a percent of her processing power.)

Mensah's 'busy' was a real fucking understatement. The top of the station was split up into multiple biomes (each with their own microclimate; there were airlocks and everything), but they were all teeming with humans: walking around, spreading out on the grasses in groups large and small, climbing the trees, eating food, talking or exchanging things. Most were regular-looking, but there were also a lot of genetically-augmented ones like Haze.

In the feed, Aspen kept track of all of them. There must have been thousands of humans in this topside park alone, but they made it look effortless, sweeping through the area with their multi-threaded processes, running their sociological analysis alongside the normal work a HubSystem usually did: environmental systems, traffic control, responses to queries from subsystems and so on. It made my head spin. Even ART, riding my outputs, said, That's a lot of data. Do you know everyone on the station?

Aspen laughed. Not personally. That would be a bit much, especially during a Meet. There are over a thousand clusters on board right now, and a little less than half of them are my charges. But I know who they are. Mostly. I try not to intrude too much.

"It's incredible," Thiago said. "Is this where most of the celebration happens?"

"One of the more popular sites for sure," Reed answered. "But the Meet happens all over Courageous and Waveskimmer Stations. Everyone has their own preferred spots."

"What do people usually do?"

"That depends. There's always a lot of work in the background. Resource exchange, processing, maintenance and all that. But that's four hours per shift, and the rest is spent with friends and family." Reed looked away from Thiago, surveying the gardens in wonder. "Taproot and stars, Aspen, we've been away for barely half a year, and the biomes have grown so much more complex. How?"

"Full credit to Rye and kes interplanting schemas," Aspen replied from Mensah's communicator. "And speaking of Rye, ke's asked me to pass along that ke'll be free around Dolphin's Watch."

"Oh? Excellent, that gives me some time to look around and find something specific to compliment before I meet kem. Thank you, Aspen."

Thiago was making notes somewhere in his feed, then said, looking up, "That method of communication can't be sustainable for the entire population, can it?"

Aspen and Reed laughed together.

"Absolutely not," Reed said. "There's an automated messaging system for a reason. People just check the nearest terminal."

"I do make the occasional exception for members of my cluster, however. Even the transplants," Aspen added.

Thiago's eyes lit up. Reed raised an eyebrow.

Hah, trying to map our family structures. Good luck with that, Aspen said in the feed, amused.

They're not that complicated, Dandelion commented off-handedly.

Spoken like someone who's never tried to figure out who they really shouldn't be dating outside of their own cluster.

Dandelion scoffed, but didn't disagree. (She probably had better things to do even when she was human.)

"How, exactly, are you and Aspen related? Did you grow up here?" Thiago asked, moving over to Reed like he was sighting on kem.

"I did part of my exile on Courageous Station," Reed answered, throwing a slightly uncomfortable look over kes shoulder to the biome ke was eyeing earlier. (If ke didn't get rid of Thiago soon, ke'd be stuck. But at least Thiago would also be easy to monitor.)

"An apprenticeship of sorts, then? How did you choose your cluster?"

Reed shrugged. "A new system sounds very exciting when you're twenty, so I took the first ship here after the wormhole to Trellin was opened. That was just a few months after Aspen, Dandelion and Note arrived, so there was a lot of work and not a lot of space available. It was mostly the Courageous cluster working on space-side construction to make enough room for other full clusters to come. Who else would I join?"

"But right now you're part of Tenacious cluster? How did that switch happen?"

"I applied and she and her captain accepted? I'm not entirely sure what you're inquiring about, Dr. Thiago..."

This was going to take a while. ART agreed, so it said to Aspen: You must have all of the demographic data for this station. Thiago should have tried to access it through you. Is this a teaching moment?

Yes, for me, Aspen replied, grinning. They had four tendril-processes hanging over Thiago. It's always a lot of fun watching someone try to study your own culture.

Humans--and human-based constructs--who studied other humans were incredibly weird. So I backburnered that conversation and instead followed what Mensah was looking at.

And oh shit, I should have been doing that from the beginning instead of wasting my time watching Thiago. Because the four humans she was looking at stuck out like a sore thumb here, even though they were wearing local clothes. (They were augmented. And Aspen's humans had very few augments. More than Dandelion did, but it was still corrective augments only, and I'd only seen twenty or so on the whole station so far.)

(They also had about twice the number of Aspen's tendrils trailing them, which was even more of a dead give-away).

And they were headed straight for the same raised structure in the middle of the gardens that we were going to.

System, query: identity of humans ahead? I asked.

Response: Caldera Exploration employees, Aspen said. Here with their representative office.